From insight to action - data analysis that makes a difference! - Heena Jethwa

Editor's Notes

• #2: Thanks for your time today. We’re here to talk to you about how you can optimize your processes and how IBM’s SPSS Predictive Analytics can help you do that. By the end of this session you should have a solid sense of how SPSS Predictive Analytics forms a critical piece of the IBM approach to driving Operational Excellence. Before we get started, I want to show you a quick video, which will give you a sense of what we will discuss today.
• #4: In the past year and 2, IBM has conducted Global CEO and CIO studies to better understand their concerns and issues. One of the main issues that came about is the fact that the world and the company’s problems are becoming much more complex and those companies that are capitalizing on that complexity are those that embody creative leadership, reinvent customer relationships, and build operational dexterity. This mirrors a book that was written back in 1995 called The Discipline of Market Leaders, by Michael Treacy and Fred Wiersema. In this book, the authors outline the 3 core business value disciplines or strategies. No matter what the wording of a company’s mission statement, it all boils down to one of these 3 concepts: Product Leadership, Operational Excellence, or Customer Intimacy. When we think about Product Leadership, we think about a company like Apple, who is constantly innovating and coming to market with the newest and best gadgets. Walmart is a great example of a company that excels operationally. The do whatever they can to eliminate unnecessary waste so as to deliver the lowest cost and the highest value for their customers. Finally – customer intimacy. This all about the satisfaction of your customers – building trusted advisor relationships and using that information to better understand who they are and what they want. In this discussion, we will focus on the Operational dexterity or Operational Excellence – what you can do to reach the goal of Operational Excellence. Embody creative leadership creativity as the most important leadership attribute. invite disruptive innovation, encourage others to drop outdated approaches take balanced risks. open-minded and inventive in expanding their management and communication styles in order to engage with a new generation of employees, partners and customers. Reinvent customer relationships CEOs prioritize customer intimacy as never before. Globalization, combined with dramatic increases in the availability of information, has exponentially expanded customers’ options. ongoing engagement and co-creation with customers produce differentiation. the information explosion is the greatest opportunity in developing deep customer insights. Build operating dexterity stay ready to act when opportunities or challenges arise. simplify and sometimes mask complexity that is within their control and help customers do the same. Flexible cost structures and partnering capabilities to rapidly scale up or down. Build operating dexterity stay ready to act when opportunities or challenges arise. simplify and sometimes mask complexity that is within their control and help customers do the same. Flexible cost structures and partnering capabilities to rapidly scale up or down.
• #5: There are three disruptive forces that are driving the urgency for analytics. The emergence of Big Data and more importantly the emergence of organizations ability to harness its potential in a meaningful and cost-effective way. The second is the shift in power to the consumer driving our organizations to innovate around how to acquire, grow and satisfy clients or see them move like a flash mob. The third is the pressure to do more with less. This pressure has been around for a while and everyone everywhere has been asking more of people and existing processes but now it is increasing exponentially and pushing to the breaking point of the capacity of their people and their processes – again forcing innovation
• #6: These pressures on organizations are at a point where analytics has evolved from business initiative to business imperative. As you can see on the chart… a recent study conducted by the IBM Institute of Business Value and MIT Sloan Management Review revealed that the number of enterprises using analytics to create a competitive advantage jumped almost 60% in just one year… Nearly 6 out of 10 organizations now differentiate through analytics. We found that the overall increase in advantage went almost exclusively to organizations who were already experienced users of analytics… so the early adopters are extending their leadership and the laggards need to worry. Essentially the market is splitting into the Analytic have’s and the Analytic have nots in terms of performance These organizations who are achieving competitive advantage through analytics are seeing real mesaurable benefits in key financial measures… 1.6 times greater revenue growth 2 times greater EBITDA growth 2.5 times stock price appreciation
• #7: Now we move on to the last of the four high-value initiatives, operational and threat & fraud analytics. When we speak with organizations, many bring up Operations as an area of focus for them – primarily to reduce costs and to really leverage it as an asset within the organization. Take for example, that up to 7% of product revenues are associated with warranty expenses or that up to 15% of sales margins are reduced by poor assortment planning processes or that up to 80% of insurance premium revenues accounts for claims expenses. It is evident that these costs affect both big and small corporations and affect the operations of organizations across many industries. These organizations are not alone. All organizations, no matter if they are a product or services organization, has to go through processes around planning, development, distribution, and support, which affects every department within an organization. When we talk about Operations we are talking about all the employees, assets, and processes that exist to support its primary function – which is to ensure that the customers’ needs are met. And when we looks at Operations, we must view it as an enterprise concern. In order to truly differentiate from the competition, organizations must learn to view their operations across all the individual silos.
• #8: So what are our surroundings looking like? Speaking Tips: This slide needs to get to the point fairly quickly. Make it interactive by giving an example in a trend area such as ‘customer demands’ and then ask for audience for other additional examples. If you spend more than 5 minutes on this slide it’s too long Remember to answer the ‘SO WHAT?’ questions so that this does not come off as an interesting but ultimately inapplicable overview of the market. So what that this is a market trend? How can I use this as a seller? What does this mean for the opportunities I can find and how I work them? Speaking Points: What is making our world so complex? Complex Supply Chain- Supply chains now much more global rather than local. Increasingly complex. Any one area in the chain can impact other areas. (Example: Japan tsunami impacted the ability of Honda and Toyota to get car parts to different markets, slowed down sales) Price volatility: Example: Cost of gasoline in the airline industry where Southwest locked in gas rates 5-6 yrs earlier near $60 a barrel as opposed to the other airlines that were paying over $100 a barrel. Compliance and scrutiny: Everyone is looking at costs and operations like never before. Sweat shops for Nike in the 90s, even currently with Apple’s supplier in China, Foxconn, having high suicide rates. Fraud: is not limited to one industry or type, examples are credit card fraud, tax fraud, insurance/healthcare claims fraud, energy/utility, retail – shrinkage, etc. Lean operations: Refer to McKinsey study from two years ago. The number #1 department where budget cuts occurred was in Operations. So, everyone is already doing more with less. IBM IOD 2012 11/22/12 Drury Design Dynamics
• #9: As professionals that care about Operations, as part of knowing our surroundings, we must define it - what we mean by Operations, first. Usually, when I say the word Operations, many think of a production line ro supply chain. Here we can see most of the departments of most organizations. When we talk about Operations we are talking about all the employees, assets, and processes that exist to support its primary function – which is to ensure that the customers’ needs are met. And when we looks at Operations, we must view it as an enterprise concern. In order to truly differentiate from the competition, organizations must learn to view their operations across all the individual silos. As a consumer, many times we take for granted how a product actually became to be in our hands when we purchase it. For example, I just recently bought an iPhone. I went to the Apple store and bought it. Other than spending money, the experience was fairly easy for me. After researching which phone I wanted, I walked in the store, went up to the counter, paid money, had the phone activated, and done! But from Apple’s standpoint, Procurement had to manage suppliers who created the components that make up the phone, Product Development had ensure it was assembled to specifications, Supply Chain had to ensure the products reached their destinations on time and with the correct quantity. If there were any issues, Apple had to ensure that their customer service processes met the customers’ needs. HR had to ensure that the right employees had to have the right skill set to help the customers. Finance has to ensure that Apple is not overspending on this entire process. As you can see, all of these processes can make one pull their hair out, but more importantly, it truly is everyone’s business. Now that we’ve defined Operations, lets go into more detail. IBM IOD 2012 11/22/12 Drury Design Dynamics
• #10: The situation we now find ourselves in, the era of the empowered customer, brings challenges as well as opportunities for organizations to optimize the customer experience… A major challenge surrounds the increasing complexity that accompanies today’s buying experience. Formerly, a customer would purchase a product, use it, and then if needed, reach out to customer service. Now, the buying process has become significantly more complicated, driven by the customer’s ability to research extensively before purchasing. What separates an average company from one that can differentiate from their competition, is the ability to ensure that they are present in all channels with meaningful messages during this time of research. But even more important, is the ability to determine when that customer is actually ready to make a purchase decision. With business analytics, organizations can understand and anticipate customer behaviors and needs and then effectively segment and target those customers to deliver the right offer at the right time through the right channel . It does not stop after one transaction, however. Organizations need to maximize customer lifetime value through up-sell and cross-sell activities, engaging them across multiple touchpoints throughout their lifecycle. Some of these interaction opportunities come when a customer has a question about the product or service they are using. Empowering these customer service representatives with the knowledge, driven by analytics and bolstered by the information captured throughout the conversation, can determine the correct strategy whether a sales opportunity exists or not. With this in mind, and leveraging the power of social media and real-time recommendations, organizations need to harness the power of the customer’s voice to increase customer loyalty and retention, proactively preventing churn as well as turning satisfied customers into advocates.
• #11: The situation we now find ourselves in, the era of the empowered customer, brings challenges as well as opportunities for organizations to optimize the customer experience… A major challenge surrounds the increasing complexity that accompanies today’s buying experience. Formerly, a customer would purchase a product, use it, and then if needed, reach out to customer service. Now, the buying process has become significantly more complicated, driven by the customer’s ability to research extensively before purchasing. What separates an average company from one that can differentiate from their competition, is the ability to ensure that they are present in all channels with meaningful messages during this time of research. But even more important, is the ability to determine when that customer is actually ready to make a purchase decision. With business analytics, organizations can understand and anticipate customer behaviors and needs and then effectively segment and target those customers to deliver the right offer at the right time through the right channel . It does not stop after one transaction, however. Organizations need to maximize customer lifetime value through up-sell and cross-sell activities, engaging them across multiple touchpoints throughout their lifecycle. Some of these interaction opportunities come when a customer has a question about the product or service they are using. Empowering these customer service representatives with the knowledge, driven by analytics and bolstered by the information captured throughout the conversation, can determine the correct strategy whether a sales opportunity exists or not. With this in mind, and leveraging the power of social media and real-time recommendations, organizations need to harness the power of the customer’s voice to increase customer loyalty and retention, proactively preventing churn as well as turning satisfied customers into advocates.
• #12: As we look at ourselves, we have a balancing act that we must deal with. The fundamental question that all organizations must answer is how do you meet the customer’s needs while meeting profitability metrics? Talking Points: When we talk about Operations, we are talking about the internal workings of a corporation. It includes all the people, assets, and processes to ensure that a product or service is delivered to a customer. Operations can include everything from manufacturing processes in Automotive, to Claims Management in Insurance, to the online checkout process in Retail. While a company’s operations may vary from one industry to the next, there are 4 main levers that affect Operations. These levers are Cost, Speed, Flexibility, and Quality and most times some of these levers tend to counteract each other or move in opposite directions. For example, one would love to have the highest quality product in the marketplace, but usually the higher the quality, the higher the cost, which a company may not be amiable to such a tradeoff. Note that 48% of product companies see that improving quality is a key challenge for them. There is always an internal struggle to balance these levers to ensure that your product or service has the lowest cost that it can, that it can be brought to market quickly, that your operations are flexible enough to modify the product/service, and that the quality is as high as possible. In order to be smarter, this balance must be optimized in real-time and in order to optimize these levers you have to leverage all of the information available to you, so the decision-makers can ensure that your company is meeting the needs of the customers’ ever changing expectations, needs, and wants. Operational excellence means that each product or service throughout each stage of this value cycle not only increases its value, but increases it in an optimal way for the organization. The business processes and interaction points are flexible enough to take into account the unique influences of customer behavior. Operations must be flexible enough to ensure that your employees and processes are efficient enough to be modified in real-time to maximize not only output, but also profit. Going back to our automotive supply chain example, at the end of the day, organizations are all businesses and automotive companies have spent billions of dollars to improve their supply chain to maximize their profit. Organizations must ensure that they can achieve the greatest ROI possible on the people, processes, and capital. IBM IOD 2012 11/22/12 Drury Design Dynamics
• #13: And then when you take it one level farther, to the individual level…what are operations professionals dealing with on a daily basis? IBM IOD 2012 11/22/12 Drury Design Dynamics
• #14: We’ve talked about the balance of operations and at a high-level, what problems organizations are facing. Now let’s go one step further. As we continue to Know Yourself, lets discuss some specific problems that certain organizations face, some maybe similar to your problems. IBM IOD 2012 11/22/12 Drury Design Dynamics
• #15: Now it’s important to delve a little deeper into IBM’s operational capabilities. IBM operations solutions help organizations plan for operational success, manage day-to-day operations, and maximize operational performance. When we say plan, we mean just that – being able to plan your for your assets, people, and products as time changes, no matter if it is Headquarters or the retail location. When we say manage, we mean being able to gain insight into an organizations’ processes and being able to make decisions and modify processes to meet the ever changing demands of the customer while reducing as much waste as possible. And when we say maximize, we mean being able to keep your infrastructure and equipment running, so you don’t have unplanned downtime or excessive downtime for maintenance. Also, we understand the importance of allocating expenses appropriately – so have the capability to help our clients ensure the assets they have purchased are running as efficiently as possible.
• #16: Plan Allocate future expenditures in most efficient manner Ensure the right quantity of the right product is available at the right time and location Manage Enhance existing operational processes Improve employee productivity and effectiveness Maximize Extend longevity of infrastructure and equipment Improve asset and employee performance IBM has a suite of predictive operational analytics solutions across various industries to ensure benefits are attained quickly. Predictive operational analytics allows organizations to Plan for Operational Success, Manage Day-to-Day Operations, and Maximize Operational Performance. Some solutions are listed on this wheel from assortment planning and demand forecasting to debt management and claims processing to Predictive Maintenance and Program Evaluation. There’s a more comprehensive list, as well, and even then IBM IOD 2012 11/22/12 Drury Design Dynamics
• #17: Steve Mills 09/15/10 100915 MILLS WebSphere eCommerce Forum Toronto.ppt Advanced spatial analytics will deliver near real-time information to assist DC Water in predicting potential problems and occurrences based on location, time, weather and historical events. Business need: Facing an aging infrastructure and numerous customer complaints, the District of Columbia Water and Sewer Authority (DC Water) needed to improve asset reliability and lifespan, and streamline its business processes. Solution: DC Water worked with IBM, IBM Premier Business Partner ESRI, joint IBM and DC Water Business Partner tieBridge, and others to modernize infrastructure management and gain greater visibility into critical operations. Benefits: 36 percent reduction in customer calls through increased preventive maintenance and implementation of automated meter readings; Increased percentage of emergency investigations dispatched within 10 minutes from 49 percent to 93 percen; Ability to generate reports for regulatory compliance and management review in seconds versus days; Significant reduction in asset downtime Smart Water: Improving water quality and service Instrumented: Asset and maintenance data, including fire hydrant status captured from handheld devices, is collected and analyzed via a single platform and mapped with ESRI’s GIS softwarel Interconnected: Status of the city’s hydrants can be viewed by firefighters via Google Earth as they are rushing to the scene and spatial data is shared transparently. Intelligent: Real-time, map-based information and geo-analytics will help DC Water predict infrastructure problems based on location, time, weather and historical maintenance data. What makes it Smarter: Advanced spatial analytics will deliver near real-time information to assist DC Water in predicting potential problems and occurrences based on location, time, weather and historical events. According to George S. Hawkins, General Manager of the District of Columbia Water and Sewer Authority (DC Water), aging water and sewer infrastructure is a problem that plagues many of the older cities across the country and, the District of Columbia is no exception. The median age of the 1,300 miles of pipe in the DC Water distribution system is 76 years old and much of the 1,800 miles that make up the sewer collection system was installed in the mid-1800s and early 1900s. “I find it truly amazing that we still have infrastructure providing service to our customers that predates the Civil War,” says Hawkins. “My preference is to modernize the system and provide a higher level of service to the customers we serve.” DC Water provides clean drinking water services and wastewater collection and treatment to 600,000 customers in the District and wastewater services to 1.6 million customers in nearby Fairfax and Loudon counties in Virginia and Prince George’s and Montgomery counties in Maryland. The organization estimated that it would take billions of dollars and well over a century to replace its aging infrastructure. “What’s more, manual, disconnected business processes made strategic decisions on where to invest our limited capital dollars more difficult,” says Hawkins. According to Mujib U. Lodhi, Chief Information Officer of DC Water, the organization bridged the gap between technical and operational resources using information technology (IT) as the change agent. “The partnership developed between IT, operations and our business partners became the principal driver in advancing many smart initiatives that helped advance DC Water as a premier service provider and as a SMART utility in the nation’s capital,” says Lodhi. “At DC Water, we use an end-to-end process in technology solutions where IT and operations work hand-in-hand to understand and develop the business requirements before an IT solution is proposed. In my experience, the business process owners typically have a conceptual idea of what is needed when it comes to IT solutions. At DC Water, scarce funds are not committed to conceptual ideas without first developing clearly defined business requirements. Once the requirements are defined, DC Water reaches out to the executive team to serve as the steering committee for the entire project life cycle with clearly defined tasks and project milestones, including process owners composed of both IT and operations personnel. As a change agent, IT introduced the project life cycle discipline at DC Water and nurtured the partnership concept needed to transform a conceptual idea into a business process solution.” Modernizing an aging infrastructure Through a strategic maintenance and asset management program and transition to automated meter readings, DC Water is modernizing management of its massive water and sewer infrastructure—which includes hundreds of thousands of assets such as water distribution pipes, valves, public fire hydrants, collection pipes, manholes and water meters. IBM, IBM Premier Business Partner ESRI, and joint IBM and DC Water Business Partner tieBridge worked with DC Water to help staff gain greater visibility into its assets and streamline business processes across the organization. Using IBM® Maximo® Asset Management in combination with ESRI GIS software, DC Water staff can view the location and condition of each asset on a detailed map and can quickly access asset history, total asset cost, number of problems in specific areas, and even water quality issues by type and area. This is vital in enabling staff to identify patterns and make informed decisions regarding which infrastructure assets to repair, which to replace and when. With the implementation of IBM Maximo Spatial Asset Management, the integration between Maximo and ESRI software—using ESRI’s REST (Representational State Transfer) application programming interface—will provide an increasingly seamless integration of spatial and asset management data. “IBM Maximo Asset Management helps us to make intelligent decisions so we can extend the useful life of critical infrastructure components while planning the capital improvements necessary for reliable infrastructure,” says Charles W. Kiely, Assistant General Manager, Consumer Services, DC Water. When water and sewer customers call the agency regarding service issues—a water main break, a leak, a billing question or a water quality complaint—customer service staff in the agency’s new consolidated Command Center captures the information in IBM Maximo Asset Management software and automatically initiates a work order. Work orders that once took days to process can now be approved and crews dispatched in minutes. The system captures useful data such as the time to complete repairs compared with the expected problem resolution time. DC Water supervisors can then identify jobs in which durations exceed acceptable parameters and research what caused the anomaly. Process improvements are then implemented to alleviate reoccurrences. Planning preventive job plans help agency staff extend the lifespan of critical assets and manage compliance requirements, such as confirming that water samples and equipment tests are conducted at the appropriate intervals as required by the U.S. Environmental Protection Agency. “Using IBM Software, we’re able to deploy our crews faster, which is a key driver of customer satisfaction,” says Kiely. “For day-to-day maintenance, IBM Software helps us to coordinate and plan our crew assignments weeks in advance so we can work much more efficiently.” Advanced water management When DC Water implemented its asset and maintenance management program, the goal wasn’t to simply automate existing processes. It was to better serve the community through improved business processes. Take, for example, the agency’s new hydrant inspection program. Previously firefighters had to fill out paper forms when inspecting the district’s 9,000 fire hydrants and then mail the information to DC Water headquarters, which would assign work orders as needed. The process was time consuming and error prone. Information was often incomplete, making it difficult to reliably provide hydrant status information to the Fire Department, the public and DC Water field crews. Now with IBM Maximo Asset Management, ESRI ArcGIS and a third-party mobile application, inspections are performed using a smart handheld device. When an individual holding this device is within 10 feet of a hydrant, the application automatically identifies the hydrant and its location and the system prompts the inspector for the required information. Photos of the hydrant can be captured for inclusion in the inspection report using the handheld. If a problem is noted, the system automatically generates a work order. In addition, the status and water flow capacity of each hydrant is mapped and can be viewed by the Fire Department via Google Earth so when firefighters are rushing to the scene, in most cases they know in advance the level of water flow to expect out of the hydrants in the vicinity. “Our work with IBM has allowed our assets to communicate with us—and we’re doing more than just listening, we’re taking action,” says Lodhi. Realizing a significant return on its investment How much impact has this new approach had on operational efficiency? A great deal, according to Kiely. Among the many statistics compiled: Customer call volume has decreased by 36 percent through increased preventive maintenance, improved scheduling and the agency’s new automated meter reading (AMI) infrastructure. Meter reading costs that averaged US$3 per reading in 2000 are now measured in cents. “It is incredible when we step back and realize that DC Water has collected almost 400 million meter readings since implementing AMI,” adds Kiely. DC Water’s credit and collection performance improved dramatically as 90-day receivables declined from $26 million in 2003 to $5 million in 2009. Emergency investigations dispatched in under 10 minutes increased from 49 percent in 2006 to 93 percent in 2009. “Our first responders are at the site of any emergency within 45 minutes, although frequently our response is much faster,” says Kiely. “As part of DC Water construction permitting process automation with new business processes, the percentage of application reviews completed within goal has increased from 63 percent to 90 percent,” adds Lodhi. Kiely continues, “Our customer service goal is in keeping with the ‘one and done’ concept, meaning that we try to do everything needed the first time, every time and IBM Maximo helps us manage this process. This results in very few return visits.” The recent integration of ESRI ArcGIS with IBM Maximo allows DC Water to deploy its crews more effectively, which translated into hard operational savings. Using ESRI ArcGIS and IBM Maximo software, DC Water can strategically assign its crews to a small geographical area to perform both corrective and preventive maintenance work, with the goal being to capture every asset touch in IBM Maximo. By capturing data and information on every asset, DC Water can reduce the costs of its preventative maintenance programs while extending the useful life of this critical infrastructure. According to Lodhi, while the organization has realized tremendous results so far, what comes next will be even more impressive. DC Water is working with IBM Global Business Services and the IBM T.J. Watson Research Lab to integrate advanced analytics with IBM Maximo Asset Management software and ESRI ArcGIS. The availability of real-time, map-based information and geo-analytics—developed based on hundreds of algorithms and delivered using IBM Cognos® 8 Business Intelligence, IBM WebSphere® ILOG® and IBM SPSS software—will help DC Water engineers predict potential problems and occurrences based on location, time, weather and historical maintenance-related events. What’s more, the agency will be able to more intelligently dispatch crews so that as maintenance personnel are sent to a site they can address all work requirements in the vicinity—both corrective and preventive. This is expected to further reduce the time to correct problems while decreasing mileage on its trucks by at least 20 percent. The agency also plans to use analytics to understand service demand—such as which areas of the city use water the most and how usage changes each season—and potentially create a new rate model. “Predictive analytics will bring our operating costs down even further, reducing the cost per work order of service,” says Lodhi. “DC Water is well beyond the phase of automation and now very much focused on predictive analytics and ‘making our assets intelligent’. It is all about data insights as part of the ‘out data management strategy’, which sits on three pillars, I call the three A’s—Acquire, Analyze and Act. This will help us gain not only operational efficiencies but also investment efficiencies, which in the long term offer a much bigger payoff.” The District of Columbia Water and Sewer Authority (DC Water) provides water, sewer, and wastewater treatment services to nearly 600,000 residents, 1.6 million annual visitors, and 700,000 workers in the District of Columbia and parts of Virginia and Maryland. Business need: For several years, senior managers at DC Water have found it difficult to balance the need to update its infrastructure with its funding limitations. Solution: DC Water began working with IBM Global Services to create a system that would enable the organization to manage its infrastructure proactively rather than reactively. IBM Business Analytics was integrated with existing data sources that included IBM Maximo, a supervisory control and data acquisition tool, an interactive voice recognition system, GIS systems, and an advanced meter reading application. Benefits: By using IBM Business Analytics as the core of the ADAM system, DC Water was able to improve decision making by employees, reduce labor costs, and recapture lost revenue. THE BOTTOM LINE Nucleus Research examined DC Water’s adoption of IBM Business Analytics and its integration with various data sources. Nucleus analysts found that the deployment enabled employees to utilize more information when making decisions, resulting in lower contract labor costs, the recapture of lost revenues, and reduced call center costs. ROI: 629% Payback: 2 months Average annual benefit: $6,559,000 THE COMPANY The District of Columbia Water and Sewer Authority (DC Water) provides water, sewer, and wastewater treatment services to nearly 600,000 residents, 1.6 million annual visitors, and 700,000 workers in the District of Columbia and parts of Virginia and Maryland. THE CHALLENGE For several years, senior managers at DC Water have found it difficult to balance the need to update its infrastructure with its funding limitations. In assessing its situation, the organization saw opportunities and challenges that included: Assets. The organization’s infrastructure, including assets such as pipes, hydrants, valves, and manhole covers, was aging. The average asset was 76 years old and some assets were 150 years old. Capital requirements. Management knew that maintaining high levels of service would eventually require replacing much of its infrastructure at the cost of billions of dollars. However, DC Water’s only funding source was rate increases, which require a lengthy regulatory process. Operations. Management knew that if it could find ways to extend the life of the existing assets and better use its labor force, it could use the resulting cost savings to pay for its eventual investments in infrastructure replacement. THE STRATEGY In order to better utilize its workforce and extend the life of its existing assets, senior management decided to change many of the practices that impact asset maintenance and service delivery, including: Data access. Senior management wanted its managers and field-service workers to have better access to information about customers, water sources, water uses, and every asset within the infrastructure, including pipes, manhole covers, storm drains, outfall pipes, and storage facilities. Data analysis. The organization wanted an application that could combine the information from DC Water’s multiple data sources in order to assist people in decisions such as repair crew assignments and identifying when best to perform preventative maintenance on individual assets. Decision making. Senior management wanted its supervisors and workers to begin making decisions focused on preventative asset management, so that the organization could spend less time and money repairing broken assets, which is far more expensive. In mid-2008, three employees from DC Water began working with consultants from IBM Global Services to create a system that would enable the organization to manage its infrastructure proactively rather than reactively. In order to complete this project, the organization: Integrated assets. IBM Business Analytics was integrated with existing data sources that included IBM Maximo, a supervisory control and data acquisition tool, an interactive voice recognition system, GIS systems, and an advanced meter reading application. Configured the solution. Once fully integrated with the data sources, the analytics application was configured to perform predictive analyses on each component in DC Water’s infrastructure, identify the assets most in need of preventative maintenance, and create work orders accordingly. Changed decision making. Once trained on the individual applications, employees were taught how to use the queries and reporting capabilities to make decisions focused on preserving assets and improving productivity. DC Water’s asset management system was operational in 2005 and used by over 300 people on a daily basis, including managers and dispatchers who deploy 400 field-service employees. KEY BENEFIT AREAS By using IBM Business Analytics, Nucleus Research calculated that DC Water was able to improve decision making by employees, reduce labor costs, and recapture lost revenue. Specific benefits of the deployment include: Reduced labor costs. As a result of the deployment, dispatchers and managers are able to use geographic information and asset-related data to make more selective and cost-effective decisions about work assignments and truck rolls. By improving the utilization of its field-service employees, DC Water became less reliant on contract workers and reduced the annual cost of these workers by $1.8 million. Avoided call center costs. Despite growth in the levels of commercial and residential activity which increase water usage and stress on existing infrastructure, preventative maintenance and better incident management have reduced call volumes, enabling DC Water to avoid adding five customer service representatives. Reduced fuel costs. By reducing the annual number of truck rolls completed, DC Water’s gasoline costs were reduced by 20 percent. Recaptured revenues. The deployment has resulted in the recapture of $3.8 million in revenues. Revenue loss from defective meters was reduced because the advanced metering infrastructure is integrated with IBM Business Analytics, enabling more timely identification and replacement of defective meters that reduce billings. Revenue was also recaptured because DC Water can now identify and bill locations where there is unmetered water usage.
• #18: Steve Mills 09/15/10 100915 MILLS WebSphere eCommerce Forum Toronto.ppt Advanced spatial analytics will deliver near real-time information to assist DC Water in predicting potential problems and occurrences based on location, time, weather and historical events. Business need: Facing an aging infrastructure and numerous customer complaints, the District of Columbia Water and Sewer Authority (DC Water) needed to improve asset reliability and lifespan, and streamline its business processes. Solution: DC Water worked with IBM, IBM Premier Business Partner ESRI, joint IBM and DC Water Business Partner tieBridge, and others to modernize infrastructure management and gain greater visibility into critical operations. Benefits: 36 percent reduction in customer calls through increased preventive maintenance and implementation of automated meter readings; Increased percentage of emergency investigations dispatched within 10 minutes from 49 percent to 93 percen; Ability to generate reports for regulatory compliance and management review in seconds versus days; Significant reduction in asset downtime Smart Water: Improving water quality and service Instrumented: Asset and maintenance data, including fire hydrant status captured from handheld devices, is collected and analyzed via a single platform and mapped with ESRI’s GIS softwarel Interconnected: Status of the city’s hydrants can be viewed by firefighters via Google Earth as they are rushing to the scene and spatial data is shared transparently. Intelligent: Real-time, map-based information and geo-analytics will help DC Water predict infrastructure problems based on location, time, weather and historical maintenance data. What makes it Smarter: Advanced spatial analytics will deliver near real-time information to assist DC Water in predicting potential problems and occurrences based on location, time, weather and historical events. According to George S. Hawkins, General Manager of the District of Columbia Water and Sewer Authority (DC Water), aging water and sewer infrastructure is a problem that plagues many of the older cities across the country and, the District of Columbia is no exception. The median age of the 1,300 miles of pipe in the DC Water distribution system is 76 years old and much of the 1,800 miles that make up the sewer collection system was installed in the mid-1800s and early 1900s. “I find it truly amazing that we still have infrastructure providing service to our customers that predates the Civil War,” says Hawkins. “My preference is to modernize the system and provide a higher level of service to the customers we serve.” DC Water provides clean drinking water services and wastewater collection and treatment to 600,000 customers in the District and wastewater services to 1.6 million customers in nearby Fairfax and Loudon counties in Virginia and Prince George’s and Montgomery counties in Maryland. The organization estimated that it would take billions of dollars and well over a century to replace its aging infrastructure. “What’s more, manual, disconnected business processes made strategic decisions on where to invest our limited capital dollars more difficult,” says Hawkins. According to Mujib U. Lodhi, Chief Information Officer of DC Water, the organization bridged the gap between technical and operational resources using information technology (IT) as the change agent. “The partnership developed between IT, operations and our business partners became the principal driver in advancing many smart initiatives that helped advance DC Water as a premier service provider and as a SMART utility in the nation’s capital,” says Lodhi. “At DC Water, we use an end-to-end process in technology solutions where IT and operations work hand-in-hand to understand and develop the business requirements before an IT solution is proposed. In my experience, the business process owners typically have a conceptual idea of what is needed when it comes to IT solutions. At DC Water, scarce funds are not committed to conceptual ideas without first developing clearly defined business requirements. Once the requirements are defined, DC Water reaches out to the executive team to serve as the steering committee for the entire project life cycle with clearly defined tasks and project milestones, including process owners composed of both IT and operations personnel. As a change agent, IT introduced the project life cycle discipline at DC Water and nurtured the partnership concept needed to transform a conceptual idea into a business process solution.” Modernizing an aging infrastructure Through a strategic maintenance and asset management program and transition to automated meter readings, DC Water is modernizing management of its massive water and sewer infrastructure—which includes hundreds of thousands of assets such as water distribution pipes, valves, public fire hydrants, collection pipes, manholes and water meters. IBM, IBM Premier Business Partner ESRI, and joint IBM and DC Water Business Partner tieBridge worked with DC Water to help staff gain greater visibility into its assets and streamline business processes across the organization. Using IBM® Maximo® Asset Management in combination with ESRI GIS software, DC Water staff can view the location and condition of each asset on a detailed map and can quickly access asset history, total asset cost, number of problems in specific areas, and even water quality issues by type and area. This is vital in enabling staff to identify patterns and make informed decisions regarding which infrastructure assets to repair, which to replace and when. With the implementation of IBM Maximo Spatial Asset Management, the integration between Maximo and ESRI software—using ESRI’s REST (Representational State Transfer) application programming interface—will provide an increasingly seamless integration of spatial and asset management data. “IBM Maximo Asset Management helps us to make intelligent decisions so we can extend the useful life of critical infrastructure components while planning the capital improvements necessary for reliable infrastructure,” says Charles W. Kiely, Assistant General Manager, Consumer Services, DC Water. When water and sewer customers call the agency regarding service issues—a water main break, a leak, a billing question or a water quality complaint—customer service staff in the agency’s new consolidated Command Center captures the information in IBM Maximo Asset Management software and automatically initiates a work order. Work orders that once took days to process can now be approved and crews dispatched in minutes. The system captures useful data such as the time to complete repairs compared with the expected problem resolution time. DC Water supervisors can then identify jobs in which durations exceed acceptable parameters and research what caused the anomaly. Process improvements are then implemented to alleviate reoccurrences. Planning preventive job plans help agency staff extend the lifespan of critical assets and manage compliance requirements, such as confirming that water samples and equipment tests are conducted at the appropriate intervals as required by the U.S. Environmental Protection Agency. “Using IBM Software, we’re able to deploy our crews faster, which is a key driver of customer satisfaction,” says Kiely. “For day-to-day maintenance, IBM Software helps us to coordinate and plan our crew assignments weeks in advance so we can work much more efficiently.” Advanced water management When DC Water implemented its asset and maintenance management program, the goal wasn’t to simply automate existing processes. It was to better serve the community through improved business processes. Take, for example, the agency’s new hydrant inspection program. Previously firefighters had to fill out paper forms when inspecting the district’s 9,000 fire hydrants and then mail the information to DC Water headquarters, which would assign work orders as needed. The process was time consuming and error prone. Information was often incomplete, making it difficult to reliably provide hydrant status information to the Fire Department, the public and DC Water field crews. Now with IBM Maximo Asset Management, ESRI ArcGIS and a third-party mobile application, inspections are performed using a smart handheld device. When an individual holding this device is within 10 feet of a hydrant, the application automatically identifies the hydrant and its location and the system prompts the inspector for the required information. Photos of the hydrant can be captured for inclusion in the inspection report using the handheld. If a problem is noted, the system automatically generates a work order. In addition, the status and water flow capacity of each hydrant is mapped and can be viewed by the Fire Department via Google Earth so when firefighters are rushing to the scene, in most cases they know in advance the level of water flow to expect out of the hydrants in the vicinity. “Our work with IBM has allowed our assets to communicate with us—and we’re doing more than just listening, we’re taking action,” says Lodhi. Realizing a significant return on its investment How much impact has this new approach had on operational efficiency? A great deal, according to Kiely. Among the many statistics compiled: Customer call volume has decreased by 36 percent through increased preventive maintenance, improved scheduling and the agency’s new automated meter reading (AMI) infrastructure. Meter reading costs that averaged US$3 per reading in 2000 are now measured in cents. “It is incredible when we step back and realize that DC Water has collected almost 400 million meter readings since implementing AMI,” adds Kiely. DC Water’s credit and collection performance improved dramatically as 90-day receivables declined from $26 million in 2003 to $5 million in 2009. Emergency investigations dispatched in under 10 minutes increased from 49 percent in 2006 to 93 percent in 2009. “Our first responders are at the site of any emergency within 45 minutes, although frequently our response is much faster,” says Kiely. “As part of DC Water construction permitting process automation with new business processes, the percentage of application reviews completed within goal has increased from 63 percent to 90 percent,” adds Lodhi. Kiely continues, “Our customer service goal is in keeping with the ‘one and done’ concept, meaning that we try to do everything needed the first time, every time and IBM Maximo helps us manage this process. This results in very few return visits.” The recent integration of ESRI ArcGIS with IBM Maximo allows DC Water to deploy its crews more effectively, which translated into hard operational savings. Using ESRI ArcGIS and IBM Maximo software, DC Water can strategically assign its crews to a small geographical area to perform both corrective and preventive maintenance work, with the goal being to capture every asset touch in IBM Maximo. By capturing data and information on every asset, DC Water can reduce the costs of its preventative maintenance programs while extending the useful life of this critical infrastructure. According to Lodhi, while the organization has realized tremendous results so far, what comes next will be even more impressive. DC Water is working with IBM Global Business Services and the IBM T.J. Watson Research Lab to integrate advanced analytics with IBM Maximo Asset Management software and ESRI ArcGIS. The availability of real-time, map-based information and geo-analytics—developed based on hundreds of algorithms and delivered using IBM Cognos® 8 Business Intelligence, IBM WebSphere® ILOG® and IBM SPSS software—will help DC Water engineers predict potential problems and occurrences based on location, time, weather and historical maintenance-related events. What’s more, the agency will be able to more intelligently dispatch crews so that as maintenance personnel are sent to a site they can address all work requirements in the vicinity—both corrective and preventive. This is expected to further reduce the time to correct problems while decreasing mileage on its trucks by at least 20 percent. The agency also plans to use analytics to understand service demand—such as which areas of the city use water the most and how usage changes each season—and potentially create a new rate model. “Predictive analytics will bring our operating costs down even further, reducing the cost per work order of service,” says Lodhi. “DC Water is well beyond the phase of automation and now very much focused on predictive analytics and ‘making our assets intelligent’. It is all about data insights as part of the ‘out data management strategy’, which sits on three pillars, I call the three A’s—Acquire, Analyze and Act. This will help us gain not only operational efficiencies but also investment efficiencies, which in the long term offer a much bigger payoff.” The District of Columbia Water and Sewer Authority (DC Water) provides water, sewer, and wastewater treatment services to nearly 600,000 residents, 1.6 million annual visitors, and 700,000 workers in the District of Columbia and parts of Virginia and Maryland. Business need: For several years, senior managers at DC Water have found it difficult to balance the need to update its infrastructure with its funding limitations. Solution: DC Water began working with IBM Global Services to create a system that would enable the organization to manage its infrastructure proactively rather than reactively. IBM Business Analytics was integrated with existing data sources that included IBM Maximo, a supervisory control and data acquisition tool, an interactive voice recognition system, GIS systems, and an advanced meter reading application. Benefits: By using IBM Business Analytics as the core of the ADAM system, DC Water was able to improve decision making by employees, reduce labor costs, and recapture lost revenue. THE BOTTOM LINE Nucleus Research examined DC Water’s adoption of IBM Business Analytics and its integration with various data sources. Nucleus analysts found that the deployment enabled employees to utilize more information when making decisions, resulting in lower contract labor costs, the recapture of lost revenues, and reduced call center costs. ROI: 629% Payback: 2 months Average annual benefit: $6,559,000 THE COMPANY The District of Columbia Water and Sewer Authority (DC Water) provides water, sewer, and wastewater treatment services to nearly 600,000 residents, 1.6 million annual visitors, and 700,000 workers in the District of Columbia and parts of Virginia and Maryland. THE CHALLENGE For several years, senior managers at DC Water have found it difficult to balance the need to update its infrastructure with its funding limitations. In assessing its situation, the organization saw opportunities and challenges that included: Assets. The organization’s infrastructure, including assets such as pipes, hydrants, valves, and manhole covers, was aging. The average asset was 76 years old and some assets were 150 years old. Capital requirements. Management knew that maintaining high levels of service would eventually require replacing much of its infrastructure at the cost of billions of dollars. However, DC Water’s only funding source was rate increases, which require a lengthy regulatory process. Operations. Management knew that if it could find ways to extend the life of the existing assets and better use its labor force, it could use the resulting cost savings to pay for its eventual investments in infrastructure replacement. THE STRATEGY In order to better utilize its workforce and extend the life of its existing assets, senior management decided to change many of the practices that impact asset maintenance and service delivery, including: Data access. Senior management wanted its managers and field-service workers to have better access to information about customers, water sources, water uses, and every asset within the infrastructure, including pipes, manhole covers, storm drains, outfall pipes, and storage facilities. Data analysis. The organization wanted an application that could combine the information from DC Water’s multiple data sources in order to assist people in decisions such as repair crew assignments and identifying when best to perform preventative maintenance on individual assets. Decision making. Senior management wanted its supervisors and workers to begin making decisions focused on preventative asset management, so that the organization could spend less time and money repairing broken assets, which is far more expensive. In mid-2008, three employees from DC Water began working with consultants from IBM Global Services to create a system that would enable the organization to manage its infrastructure proactively rather than reactively. In order to complete this project, the organization: Integrated assets. IBM Business Analytics was integrated with existing data sources that included IBM Maximo, a supervisory control and data acquisition tool, an interactive voice recognition system, GIS systems, and an advanced meter reading application. Configured the solution. Once fully integrated with the data sources, the analytics application was configured to perform predictive analyses on each component in DC Water’s infrastructure, identify the assets most in need of preventative maintenance, and create work orders accordingly. Changed decision making. Once trained on the individual applications, employees were taught how to use the queries and reporting capabilities to make decisions focused on preserving assets and improving productivity. DC Water’s asset management system was operational in 2005 and used by over 300 people on a daily basis, including managers and dispatchers who deploy 400 field-service employees. KEY BENEFIT AREAS By using IBM Business Analytics, Nucleus Research calculated that DC Water was able to improve decision making by employees, reduce labor costs, and recapture lost revenue. Specific benefits of the deployment include: Reduced labor costs. As a result of the deployment, dispatchers and managers are able to use geographic information and asset-related data to make more selective and cost-effective decisions about work assignments and truck rolls. By improving the utilization of its field-service employees, DC Water became less reliant on contract workers and reduced the annual cost of these workers by $1.8 million. Avoided call center costs. Despite growth in the levels of commercial and residential activity which increase water usage and stress on existing infrastructure, preventative maintenance and better incident management have reduced call volumes, enabling DC Water to avoid adding five customer service representatives. Reduced fuel costs. By reducing the annual number of truck rolls completed, DC Water’s gasoline costs were reduced by 20 percent. Recaptured revenues. The deployment has resulted in the recapture of $3.8 million in revenues. Revenue loss from defective meters was reduced because the advanced metering infrastructure is integrated with IBM Business Analytics, enabling more timely identification and replacement of defective meters that reduce billings. Revenue was also recaptured because DC Water can now identify and bill locations where there is unmetered water usage.
• #19: Steve Mills 09/15/10 100915 MILLS WebSphere eCommerce Forum Toronto.ppt An example of a company that utilized predictive analytics for inventory management is Brammer Group. Brammer is Europe’s leading distributor of technical components, supplying thousands of customers across some of the biggest industries in Europe, such as automotive, pharmaceuticals, chemicals, food and drink, utilities and aerospace with the millions of technical parts and associated services required for the maintenance, repair and overhaul (MRO) of production line equipment. The company employs over 2,000 people in more than 300 locations, across 16 countries. Single source supply, exceptional customer service Brammer’s size and reach means it is able to offer its customers a single source supply of the world’s leading industrial brands, as well as competitive pricing through its considerable buying power. The company is also known for its excellent levels of product availability, having built one of the most extensive inventory holdings in Europe. Brammer invests a considerable amount of capital in its inventory and realized that identifying and predicting sales patterns could result in up-front cost-savings through more intelligent inventory control. For customers experiencing business-critical breakdowns, Brammer’s emergency replacement service is committed to dispatching essential parts within hours of a customer’s request - 24 hours a day, 7 days a week, 365 days a year. It is essential for Brammer to know in advance which items customers are most likely to need so that they are always in stock. Brammer looks for ways to continually improve the service it provides to customers and identified that being able to more accurately predict customers’ needs for slow moving products would enable them to supply such products with the same speed and convenience as the more regularly ordered stocks. Thriving in a challenging business environment With the global downturn creating a challenging business environment, Brammer identified the need to take proactive steps to limit the effects of an inevitable downturn in sales. The company knew that greater insight into its data could reveal how to improve the management of its inventory, with the objective of increasing inventory turnover (a key metric in this industry: the number of times the inventory was sold) and providing added value for customers by accurately predicting their inventory requirements so that a greater range of products would be available for immediate dispatch. Predictive analytics brings insight for smarter business decisions Brammer turned to IBM to implement predictive analytics technology to reveal patterns and trends in organizational data and obtain crucial insight into how to manage stock levels more efficiently. The company selected IBM SPSS Modeler data mining workbench to implement a best-practice demand forecasting and stock planning system based on predictive analytics. Brammer is now able to create profiles of the MRO inventory that customers require, based on the history of previous and current usage. This information is used to predict future requirements and determine the inventory Brammer needs to hold on a regular basis to meet customer demand. The new system revealed where Brammer could cut back on surplus stock and contributed to a 22 percent reduction in inventory levels, resulting in considerable cost savings. “IBM predictive analytics technology has helped us dramatically streamline our inventory by creating stock profiles based on customers’ buying patterns. This enables us to forecast more efficiently what we need in stock, and in what quantity, contributing to a £31.1 million inventory reduction,” said Yongli Ge, Senior Logistics Analyst at Brammer. Business Benefits • IBM predictive analytics helped Brammer to manage its inventory more efficiently, significantly reducing the need to carry surplus stock, resulting in a total inventory reduction of £31.1 million in one year • Inventory turnover improved from 3.2 times at the end of 2008, to 3.7 times at the end of the first half of 2009 • Greater understanding of patterns and trends in customer purchasing data helps Brammer forecast marginal stock products more accurately and improve customer satisfaction by making a wider product range available for immediate dispatch • Detailed insight into inventory requirements has helped Brammer develop closer relationships with strategic suppliers, leading to further cost benefits Instrumented IBM predictive analytics enables Brammer to uncover patterns in its data, helping it anticipate and stock those items that are most likely to be required. Interconnected Anticipating stock requirements in greater detail has helped the company better meet customers’ needs. Intelligent Brammer can now supply to customers infrequently ordered products as fast as regularly ordered stocks. Streamlined inventory, increased customer satisfaction Brammer’s streamlined inventory has contributed to the company’s strong performance, with inventory turnover improving from 3.2 times at the end of 2008, to 3.7 times at the end of the first half of 2009. Brammer’s annual customer satisfaction survey showed that despite reducing stock levels by almost a quarter, customer satisfaction increased. Brammer received high scores for performance and customer focus. The survey also revealed that there has been significant improvement in customer perception of Brammer’s stocked range and availability. Understanding stock requirements in more detail has also helped Brammer develop closer relationships with strategic suppliers and increased the concentration of spend with those suppliers, leading to further cost benefits and greater supplier marketing support. Using predictive analytics to anticipate demand, improve data management IBM predictive analytics enables the company to identify and stock those items that are most likely to be required by analyzing historical customer data from the previous five years at an item, branch, country and European level, as well as analyzing price, service and distribution data. Brammer’s use of predictive analytics is part of a wider initiative to improve the management of data across all territories. For example, different countries use different names for the same product which can make company-wide analysis challenging. To overcome this, Brammer has implemented a project called Master Data Management powered by IBM software to standardize data across the different countries, providing an accurate view of how inventory is performing at a European level. “We are confident that inventory returns and customer satisfaction can continue to increase as more of our inventory is managed on a pan-European basis,” concluded Ge. IBM products and services that were used in this case study. Software: SPSS Modeler
• #20: Steve Mills 09/15/10 100915 MILLS WebSphere eCommerce Forum Toronto.ppt With 431 employees, Laboratorios Indas is the largest manufacturer of sanitary and hygiene products in Spain. Headquartered in Madrid, the company distributes its products through both retail channels (pharmacies, hypermarkets, supermarkets etc) and hospitals throughout the country. Some of Indas’ most important retail clients are pharmacies; the company currently has approximately 65 sales representatives who visit some 14,000 pharmacies at least once a year to promote its products. Business need: Laboratorios Indas was looking to launch a targeted marketing campaign which would maximise sales in the pharmaceutical channel. Indas needed a solution which would enable it to extract information from its data warehouse system directly and in real time, and exploit this information for statistical analysis. Solution: Laboratorios Indas decided to implement IBM SPSS Modeler which allows the Data Mining and Market Research team to extract both external and internal marketing data from the company’s data warehouse in real time and unite and exploit the sets of data simultaneously. The market research team used IBM SPSS Modeler, a leading data mining solution, to create predictive targets for the existing Spanish pharmaceutical world. Benefits: Improves the average number of sales per loyal pharmacy by 37 percent. Allows Laboratorios Indas sales representatives to focus on the pharmacies which offer the most potential in terms of sales. Enables sales representatives to promote products tailored to the clientele of each pharmacy. Reduced the administrative workload of Laboratorios Indas sales representatives. With 431 employees, Laboratorios Indas is the largest manufacturer of sanitary and hygiene products in Spain. Headquartered in Madrid, the company distributes its products through both retail channels (pharmacies, hypermarkets, supermarkets etc) and hospitals throughout the country. Some of Indas’ most important retail clients are pharmacies; the company currently has approximately 65 sales representatives who visit some 14,000 pharmacies at least once a year to promote its products. Targeted marketing Laboratorios Indas was looking to launch a targeted marketing campaign which would maximise sales to clients and non-clients in the pharmaceutical sector. In order to do this, the company first needed to register the quantity and type of products purchased during the visits of Indas sales representatives to the pharmacies in their region. It could then establish which types of pharmacies should be targeted to a greater or lesser degree, thus enabling the company to improve the cost-effectiveness of each sales visit. The company’s previous method of collating data from pharmacy sales visits had been a tedious process. “In the past, sales information would have to be gathered using client surveys and questionnaires, the results of which would then be entered into Excel spreadsheets,” said Roberto García, Data Mining and Marketing Research Manager, Laboratorios Indas. “We felt that the quality of this data was sometimes questionable due to the high margin for human error in its processing. In addition, it was difficult to present the data to our sales teams in a user-friendly way.” Another challenge faced by the company was to convince its sales teams to be more forthcoming with their clients’ information. Roberto García explains, “We needed the input of our sales representatives who are the only ones with the proximity to clients and prospective clients; however, it was a significant cultural change to ask them to share their knowledge.” The Indas sales teams needed to be persuaded that the provision of their clients’ data would create better targeting models which would ultimately enable their sales efforts to be focused more profitably. “It was essential that the solution we chose should deliver on this promise,” said Roberto García. Finding a solution To perform the statistical analysis and present the data effectively Laboratorios Indas decided to implement IBM SPSS Modeler. “ We chose IBM SPSS over other vendors’ solutions because it is a better-known and more specialised tool, which is ideally suited to our requirements,” said Roberto García. “We required a solution which would give us the ability to work with the extremely high volumes of data that are uploaded daily into our data warehouse.” After each sales visit to a pharmacy , sales representatives now upload required information onto their PDAs, such as the quantity and type of products sold to the pharmacy. This data is then transferred to the company’s data warehouse. In addition to this internal data, Laboratorios Indas’ Market Research team collates external data, for example information regarding the population size, socio-economic level and number of pharmacies in the geographical regions in which the sales representatives are operating. The advanced analytical tools provided by IBM SPSS enable the creation of sophisticated statistical models that use both the internal sales data and the external geographical data to provide insight into the likely demand patterns for pharmacies in different locations. “ IBM SPSS Modeler has enabled the simultaneous statistical treatment and modelisation of both our internal and external data,” says Roberto García. “In every data mining project, the first phase is to collect and create susceptible variables. IBM SPSS is particularly useful to us because it shows us the significance of every variable selected inside the model and indicates if one variable or another improves the model’s result. As a result, we’ve succeeded in creating highly sophisticated models which unite and exploit both sets of data to identify groups of pharmacies depending on their potential market by product type. Real commercial benefits It took only four months after the implementation of IBM SPSS Modeler for the use of predictive models to start yielding commercial benefits for Indas in the pharmaceutical channel. “ After just four months we could already see that the average number of sales per loyal pharmacy had improved. By the close of year 2009 we calculated a 37 percent average growth in sales per pharmacy compared with the year before,” said Roberto García. “Predictive models have enabled us to identify the best pharmacies for our products and target them more systematically with visits, emails and mailings. As a result, the loyalty of these clients has been greatly strengthened while our competitors’ best clients have also been encouraged to purchase from us instead.” Predictive models have given Laboratorios Indas a greater understanding of pharmacies’ socio-demographic characteristics. “We’re now better able to categorise clients and target particular markets with particular products,” said Roberto García. “For example, we have been able to analyse which pharmacies are located closest to families with young children, and tailor our sales campaigns for this type of establishment accordingly to focus on children-oriented products.” The use of IBM SPSS Modeler has enhanced Laboratorios Indas’ market research processes right through from the collection of the data to its analysis. Roberto García comments, “Our lives as analysts have been made a lot easier as we now have much more confidence in the quality of the data. The use of IBM SPSS Modeler has also satisfied our sales representatives’ needs. Not only are they selling more products per visit, but their administrative workload has been greatly reduced by the new system.” In the past, a sales representative’s record of his visit to a pharmacy would take five minutes to compile; now the process takes about 25 seconds as the representatives can simply tap sales figures into their PDAS. The success of IBM SPSS Modeler in creating predictive targets for pharmacies has led the Data Mining and Market Research team at Laboratorios Indas to begin the process of expanding the solution’s use to distribution chain clients and non-clients (hypermarkets and supermarkets). “ IBM SPSS has revolutionised our market research process. By enabling us to understand our clients and non-clients, it has given us a real edge over our competitors,” concludes Roberto García.
• #21: Steve Mills 09/15/10 100915 MILLS WebSphere eCommerce Forum Toronto.ppt Rudolf Ölz Meisterbäcker GmbH has been tickling Austria’s tastebuds since 1938, when the family-owned company first began its successful pastries business. Today, Ölz is the market leader and the most popular pastries brand in Austria. The company has stores and warehouses in Austria, Germany, and Switzerland, and in 2010, its 850 employees helped to generate total sales of €183 million. Business need: Flexible analysis of an employee survey to gain insights about employees’ needs. Solution: Thanks to IBM® SPSS®, Rudolf Ölz Meisterbäcker GmbH is able to filter its employee surveys by specified variables, create histograms and frequency tables, and perform statistical analyses. Benefits: IBM SPSS provides definitive, quantified information about areas such as employees’ needs and the general work climate. This information provides business managers with a sound basis for decision-making to optimise business processes, improve collaboration and support the development of the company. Rudolf Ölz Meisterbäcker GmbH has been tickling Austria’s tastebuds since 1938, when the family-owned company first began its successful pastries business. Today, Ölz is the market leader and the most popular pastries brand in Austria: brand awareness is at about 98 percent, based on aided recall studies. Eight out of ten Austrian consumers buy Ölz products, more than two thirds regularly and often. The product portfolio comprises more than 100 different products, including specialties like Topfen-Plunder, punch stollen and Bio-Keimkraft toast, a delicious organic sliced bread made from sprouted seeds. The company has stores and warehouses in Austria, Germany, and Switzerland, and in 2010, its 850 employees helped to generate total sales of €183 million. Cultivating organisational culture To support the continuous growth of the Ölz brand, a coherent organisational culture is crucial. The company emphasises openness and respectful collaboration: its guiding principle is that only with satisfied employees can Ölz continue to hold its excellent position in the market and grow further. A major concern of the company’s management team is to understand the needs and attitudes of the employees in all parts of the company. Prof. Dr. Kurt Zischg, Director of Finance, Informatics and Human Resources at Rudolf Ölz Meisterbäcker GmbH points out: “The focus of our company leadership philosophy is on maintaining a sound corporate climate and fruitful cooperation at all levels of the business. After all, our employees are our most important resource. And esteem guarantees good employee relationships.” Employees’ views in focus In mid-2010, the senior management team decided to conduct a comprehensive employee survey in all departments of the company. The priority was to obtain hard data regarding the work climate, the mood within the company, and employees’ needs. The results would then be used to support decision-making, plan new measures, modify business processes and reconsider communication channels. The need for an intelligent solution To conduct a survey of more than 800 employees and analyse the results, Bäckerei Ölz needed a statistics solution that could deliver well-founded insights without too much effort. During his former job as professor at a university of applied sciences, Kurt Zischg had already gained some experience with IBM SPSS software, which made it an easy decision to use IBM SPSS for the employee survey as well. He comments: “I got to know IBM SPSS as a first-class statistics solution that provides versatile analysis functionality and is easy to use. These were exactly our requirements.” Successful knowledge transfer To help to plan the employee survey and the statistical analysis of the results in detail, and also to get to know the features of the statistics software, Bäckerei Ölz invited an IBM SPSS consulting team to conduct a workshop at the beginning of 2010. Working with the consultants, the project team around Kurt Zischg created the plan and concept for the employee survey and the results analysis. The result of the workshop was an extensive questionnaire with 49 detailed questions. “ The questionnaire contained questions about all areas that are important for successful collaboration, such as: employees’ own work environment, their relationships with colleagues, the corporate climate, professional development and acknowledgement, ideas for improvement, and personal employee data,” explains Zischg. Registering results manually Because not all employees at Bäckerei Ölz have their own PC, the questionnaire was distributed and filled in by hand in paper form in mid 2010. All divisions of the company were asked to participate: sales and distribution, logistics, production, purchasing, finance, IT and stores. The detailed questions were measured on an ordinal scale: employees could tick values between 1 (applies completely) and 6 (does not apply at all). Subsequently the questionnaires were collected and manually registered within IBM SPSS, where they can be analysed. IBM SPSS Statistics Base is used the main analytical solution, and IBM SPSS Custom Tables makes it easy to present the results in a clear tabular format. Diagrams at a click The first stage of the analysis was to examine the validity and plausibility of the results: Are there any answers that cannot be correct? Did employees leave gaps when they filled in the forms? Kurt Zischg was able to get an initial overview of the results within a few minutes. “ When I need a distribution graph for frequencies or mean values, I only need to click on a certain variable and then the software generates a corresponding histogram. For such tasks, IBM SPSS offers a user-friendliness that I have never experienced in any other statistics solution.” The integrated IBM SPSS Custom Tables solution pays dividends for easy analysis. With a few clicks, Zischg can create user-friendly tables that provide an overview of the statistical analysis. How many percent of the employees are satisfied with the working hours arrangement; how many percent see a need for improvement at cross-department communication; is there a gender-related tendency or a problem in a specific department? All these questions can now be answered instantly, displayed clearly, and compiled into a report. As Kurt Zischg states: “I can drag individual variables quite easily into one column or row and immediately get the table I need. The same level of comfort applies for report generation in Microsoft Office formats – it actually only takes one mouse click to output a report.” Deep knowledge without diversions Other functions of the IBM SPSS software offer well-founded and detailed insights into the employee attitudes. For example, Kurt Zischg can use hypothesis tests to calculate probabilities in real-time and render them in graphs immediately. In this way, the solution provides extensive functions not only for descriptive, but also for inferential statistics. Rapid access and analysis of the records facilitates the evaluation of the survey results and provides insights easily, without delays or diversions. “ Thanks to IBM SPSS, we achieved our central goals for the employee survey: we sharpened our awareness of employee interests not only within the senior management team, but also among all the employees themselves. Furthermore, IBM SPSS gives us the basis we needed for decision-making, which helps us rethink our business processes and if necessary align them more closely with the needs of the employees. Finally, we now possess the information necessary to review measures that we implemented in the past.” Looking to the future with SPSS The insights that the company is gaining from the SPSS solution have led to a number of actions that the management team has taken to react to the needs of the employees. Key examples include: the introduction of more flexible working hours; changes to the rules governing stand-ins; and changes to cross-departmental communication procedures. The company wants to extend its use of IBM SPSS statistical analysis, and also expand into the area of data mining in future. Kurt Zischg concludes: “IBM SPSS completely has convinced us that it is the right solution for our needs, and will continue to support us in our efforts to increase growth while supporting a productive corporate climate and effective business processes.”
• #22: Today’s complex value chains require visibility into information that is integrated into a common view. E ffective Value Chain Visibility requires: - That the end-to-end supply chain information is synchronized in an integrated, or common view. - Demand, supply and logistical events that are aggregated or consolidated from multi-tier suppliers through multi-tiered distribution to final customer - Collaboration among supply chain partners that is web-based. Information is shared – each supply chain partner views their secured view of the same page. - Decision feedback loops from the collaboration As a result, organizations can develop agile supply chains that respond quickly to shocks or shifts in supply, production, demand and logistics. An integrated approach to Value chain visibility paired with use of near real-time monitoring of data feeds and advanced analytics not only helps optimize performance, but creates an environment of game changing competitive agility. An example is a large beverage manufacturer that is rolling out highly instrumented beverage mixing and dispensing machines that monitor machine health in real time and every night phone home with consumption, component performance, and ingredient levels from RFID enabled ingredient cartridges. Advanced analytics are then used to mine the machine health data to flag potential problems, as well as forecast demand and launch optimized replenishment to the machine location to insure beverage availability and freshness, while hiding the complexity of this game changing device from the outlet operator.
• #23: Predictive analytics can help reduce costs by using data to your advantage..   We pull into data from multiple different sources, that can be internal transactional info, external third party data that is relevant e.g. benchmarking data, weather reports, etc - whatever is relevant. It could also include your companies’ experience and domain expertise. The data can be in the usual structured format or unstructured/text format.   We are able to create models that determine and score the most appropriate action, i.e. which products are likely to be stocked out. To this we add business rules and domain expertise which we add to the scoring to ensure that facts are taken into consideration. We can feedback that information into our KPI´s and dashboard but also most importantly we act on that data. In operations it´s our ability to be able to manage it and decide what the best course of action is just as important as the ability to react. This is all about being able to balance customer demand and inventory supply. Predictive analytics is based on the data, both structured or unstructured. So what you can predict is really limitless…if you have the information, the software is likely to find a pattern.   IBM IOD 2012 11/22/12 Drury Design Dynamics
• #24: The use of predictive models to predict the number of asset failures provides a very accurate estimation of warranty costs by region, operating condition, etc.
• #25: Anomaly detection can identify small problems (that often go undetected) before they become bigger problems. For example, production line issues affecting quality can be very difficult to detect. Anomaly detection can find the problem early on and with automated root-cause analysis (using decision lists/trees) the problem can be addressed VERY early in the process before the it escalates into a much more costly problem.
• #26: Predictive models also give great insight into what combination of conditions lead to increased failures. Root cause analysis is fully automated with techniques such as decision lists and decision tree.
• #27: While Weibull can be very insightful into determining the failure modes, the use of predictive models is far more powerful. Predictive models leverage all available data including sensor logs (condition monitoring data), and unstructured data such as inspection and maintenance logs. These models can determine the reliability (or unreliability) of any equipment asset under any set of operating conditions.
• #29: Predictive analytics can help reduce costs by using data to your advantage..   We pull into data from multiple different sources, that can be internal transactional info, external third party data that is relevant e.g. benchmarking data, weather reports, etc - whatever is relevant. It could also include your companies’ experience and domain expertise. The data can be in the usual structured format or unstructured/text format.   We are able to create models that determine and score the most appropriate action, i.e. which products are likely to be stocked out. To this we add business rules and domain expertise which we add to the scoring to ensure that facts are taken into consideration. We can feedback that information into our KPI´s and dashboard but also most importantly we act on that data. In operations it´s our ability to be able to manage it and decide what the best course of action is just as important as the ability to react. This is all about being able to balance customer demand and inventory supply. Predictive analytics is based on the data, both structured or unstructured. So what you can predict is really limitless…if you have the information, the software is likely to find a pattern.   IBM IOD 2012 11/22/12 Drury Design Dynamics
• #30: IBM SPSS Predictive Analytics solutions can be applied at every stage of your Operations Strategy, as you build and stabilize your core operations to growing it and then ensuring that you leverage it as a competitive advantage. As we stated before, as Tom Davenport, an expert in the field of analytics and author of “Competing on Analytics” states, “At a time when companies in many industries offer similar products and use comparable technology, high-performance business processes are among the last remaining points of differentiation.” And in order to have high-performance business processes, you have to have Operational Excellence. IBM IOD 2012 11/22/12 Drury Design Dynamics
• #31: As we deal the visibility it´s also the ability to deal with what the analytics can provide across the board, how we can start in one area and progressively improave our approach and ability to be proactive.. We need visibility and control SPSS Solutions for threat and risk control are designed to meet you where you are – and provide value in two ways. For many, providing insight for decision makers is the top priority and advanced analytics clears the picture of what is happening and why. For others, moving beyond insight to actually identifying the next best action in a mission critical process is the key to breaking away. We can help you craft a roadmap that adds value where and how you need it.   Foundational is more governance based policy where activity and items are being measured and monitored but more for regulatory reasons Competitive.. These is where we are still analyzing data but more so we can refine policy going forward e.g. where are probably using some dashboard capabilities and statistics to measure Differentiating these organizations are looking at data from many different sources and determining area of where threat and risk might come from.. Data is a key component to the strategy they are looking at eliminating breaches as efficiently and quickly as possible At breakaway these are organizations who are taking the next level and taking insight and analytics and determine the next best action based on the what has happened and what is most likely to happen at the moment of impact. Wherever you are today, analytics is an important aspect to this journey.. CONSIDER where you are today as part of your threat and risk strategy.. foundational or Breakaway?  
• #32: While everything we discussed today may sound great, you are probably asking, what now? How do I get started. Here are some aspects/steps that you should be looking into to ensure that you are using your operations as a competitive advantage. First you must ensure that you have a strategy in place regarding your operations/threats and analytics that is aligned to a business objective. Then you must collect information and augment it with what you have. Then analyze the information and make predictions. Once that is completed, you must be able to share those insights into your organization. Afterwards, you want to ensure that that entire process is automated and optimized within your organization, so the analytics and insights do not just rest on a singular desktop. And finally, once that is completed, you will want to ensure that you have visibility on an ongoing basis, so it is not just a “one and done” initiative. Leveraging our Services group will help you as needed and leveraging additional hardware will improve the performance and response times of your analytics. As you leave today think about this roadmap and how you would get started.
• #33: So what makes Analytic-driven organizations different? What is comes down to is their ability to leverage All Information -social media, chats, emails, documents, data warehouses, transactions, sensors, video, location etc…. All People -all departments, experts and non-experts, executives and employees All Perspectives -Past (Historical, aggregated), Present (Real-Time), Future (Predictive) All Decisions -Major and minor, strategic and tactical, routine and exceptions, manual and automated and all processes And to do all that where it matters most – precisely at the point of impact - to drive better outcomes for their organization.