Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications
- 1. 78i am scip Special Edition Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications by Paul Santilli & Stephanie Paulutt BACKGROUND It is a fact that is readily agreed upon throughout the business community that technological advances over the past 15 years have significantly changed the way organizations operate. The most obvious advance surrounds the meteoric rise of the Internet and the never-ending generation of applications developed to support the billions of users and their information requirements. Similarly, Social Media (SoMe) had jumped on the internet backbone and now has proliferated into a dynamic communications phenomenon that is unprecedented in history. Facebook has 1.5 Billion subscribers, Twitter has 500 million registrations, LinkedIn has 450 million users, Instagram has 400 Million active participants - and they all are growing in size, capability, and global presence. Additionally, we are on the cusp of an explosive tidal wave of data surrounding the Internet of Things (IoT). IoT is all about connecting vast numbers of “smart” machines and autonomous devices across multiple platforms and applications in order to gather information about the performance and usage of products and services. Industry analysts are predicting 50 billion connected devices by the year 2020, all transmitting mountains of information every second of the day. This new information landscape presents enormous challenges for the Competitive Intelligence (CI) professional – the scalability and analytical processing capability of all of this data is simply overwhelming to historical CI methodology and modeling behaviors used in the past. One of the key ways to prepare an organization for
- 2. 79i am scip Special Edition this onslaught of information is not by simply directing more people towards the problem, but by looking at the requirements from a holistic perspective; mainly understanding the value of tools and related processes that can be utilized within an organization to gain better insights into data analytics. A key area to explore is the use of Knowledge Management Systems (KMS) designed for CI practitioners. Well defined, these tools can be extremely effective in helping organizations efficiently manage this data tidal wave in a quick and seamless manner to arrive at better actionable insights for quick organizational decision- making for both strategic and tactical use. What is a Knowledge Management System and why does your organization need it? A KMS system is a tool that collects and analyzes information from a vast quantity of resources to provide comprehensive intelligence on a real-time basis. Some critical elements are: • A platform used for creating, sharing and organizing information and knowledge. • Used as a central repository (similar to a data library) based on harvesting relevant data with real-time monitoring of web sources. • Integrates different types of data sources and formats • Data is indexed and clustered to be searchable based on user requirements. • Proposes features and functionalities to analyze the content, such as customized dashboards and related user interfaces. • Supports the generation of deliverables for sharing across the organization. KMS systems centralize data that is otherwise often present in separate data silos, making analysis and sharing difficult. It helps to exploit the full potential of the knowledge present in an organization by making the data available at a central location. This makes it much easier to locate and extract relevant content for the user. Additionally, info can be collected and extracted real-time, without delays in compilation which leads to shorter development of actionable insights (Time to Insights (TTI)). But how do you define such a KMS and what do you need to consider? There is a five-step approach for designing and implementing a system for CI: • Start with a needs analysis to gather the requirements. • Establish a process including the description of responsibilities and the implementation plan. • Define Key Performance Indicators (KPIs) and the expected added value. • Determine the Implementation and application aspects toward CI needs. • Establish a Value proposition and requirements fulfillment assessment and Review. NEEDS ANALYSIS To determine the right context for a knowledge management system you need to understand the market dynamics and competitive positioning of your business. In fact, this understanding and common awareness represent the basis for everything that follows. Being a critical element, this should receive appropriate levels of time and attention. Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications <<
- 3. 80i am scip Special Edition The key question is clear: what is it that the CI practitioner needs to collect in order to make better decisions for your organization? Too many times, CI practitioners gather substantial amounts of information for the sake of “data gathering” without understanding how and why this data is relevant to their objective. Understanding the context of the data collection requirements and how it is relevant to the objective of the CI practitioner is an obvious but often overlooked first step in a needs analysis. All stakeholders should be considered in the needs analysis and have the chance to express their information needs, key topics, desired output, etc. in order to best characterize objectives to drive tool requirements. (One technique that can be utilized is for stakeholders to recommend the preparation of a catalogue of “open” questions allowing everyone to describe the “ideal” tool by prioritizing their wishes.) If the objective of the tool is to be used by different divisions within an organization, it is important to detect potential synergies and common needs at this stage. For example, a list of use cases can help in illustrating that the colleague in the office next door is looking exactly for the same data as you. Example of four divisions in an organization who might have use cases in common: PROCESS Once the needs have been defined, the practical part begins with the description of the process covering the main responsibilities as well as the implementation plan. It is crucial to define precise roles and responsibilities and make everyone commit to them. Ideally, all stakeholders from decision-maker to the future KMS end user should be represented here. An additional key requirement is to ensure key solution enablers are involved in the process definition, as well as technical experts when it comes to content integration and IT requirements. Early involvement by all key members at this stage is critical, and allows for sufficient planning and alignment of requirements to business objectives; this includes developing realistic deadlines that also allow certain flexibility with regards to time and resource planning. When it comes to the implementation plan, the following main steps and milestones are required: • Preparation of the official requirements catalogue identified during the need analysis and summarizing the use case and reason of setting up a KMS. • Defining clear Key Performance Indicators and evaluation criteria to assess the added value of the KMS. • Obtaining a precise understanding of knowledge management systems available on the market and make a preselection based on an RFI (request for information). This should include defining a proof of concept to test one or two tools against a set of established criteria. • Whereas analysts will assess the workflow and functionalities of the tool, the CI practitioner should think about positioning the KMS internally for effective development of actionable insights, and how to promote it within the organization as a cross- functional strategic tool. Use Case/ Topic Marketing Corporate Strategy R&D Business Development I want to detect new trends at an early stage to assess their potential. X X Which new technologies should my company focus on? X X X How can I optimize my analysis on customer satisfaction and my customers’ (new) needs? X X X I want to combine external & internal data to get the full picture. X X X X >> Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications
- 4. 81i am scip Special Edition • During the KMS evaluation cycle, the IT department should be involved to define the effective implementation plan to deploy the system. The latter actually requires a good understanding of the organizational structure, culture and again the market dynamics the organization is surrounded by. KEY PERFORMANCE INDICATORS (KPI) Just like other projects, the performance and success of a KMS implementation is measured via KPIs. At the same time, their definition is more challenging in this context as classic indicators based on financial figures only cannot be applied 1:1 here. It is important to understand that KPIs associated with a knowledge management tool are rather qualitative, and mid-term / long-term oriented. One major indicator refers to an increase in efficiency regarding the whole process starting with the collection of data and ending with the actionable insights generation and sharing. This mainly includes the reduction of time spent on each step to have more time left for analysis and interpretation. The centralization of data is key in this context and the latter should be available for everyone at any time. Another indicator implies the relative ease at being able to switch from a reactive approach to a proactive one, directing the information collection towards the anticipation of changes and disruptions. In other words, the status of “being informed” which implies a look back on published data shall change to a predictive detection mode focusing on weak signals and change indicators. Besides, it is crucial to enrich the analysis and deliverables regarding the depth and variety of data. Thus, analysis and recommendations become more comprehensive and ideally reflect a look beyond the near-term tactical actions of the company to one that is more strategic in nature. Another KPI refers to encouraging a change in company culture towards a natural sharing of data and knowledge. Data silos should be reduced to a minimum and be replaced by a policy of data centralization and transparency. KMS systems help facilitate this information sharing by proposing different system functionalities that are easy to use not only for CI practitioners, but can also be effective tools for other organizations (Sales, R&D, etc.) Lastly, it is important to define realistic deadlines for the KPI achievement. Companies tend to underestimate the cultural change they go through by implementing and using a KMS on a continuous basis. Although it is necessary to have so-called “Quick Wins“ to justify the investment, the real advantage is the long- term knowledge enrichment and continuous strategic investment that these tools can support. All in all, these qualitative indicators create an advance in knowledge gathering and thus a competitive advantage which will lead better analytics and hopefully, a better business proposition. IMPLEMENTATION After testing and optimizing the tool for CI and relevant KPI requirements, the implementation should be focused on these 3 areas: • Immediate departmental applications and business requirements – determining the ability for the tool to extract relevant content, in the right format, and in a real-time progressive output to meet departmental requirements and achieve short-term objectives in data compilation and analytics. One of the key areas to consider is not only the volume of data sources, but the ability to manage the data sources to include key areas that are vital to your CI analytics objectives – those sources that are rich in content and truly critical to getting the best information as possible. Sometimes these sources are readily available, but sometimes there are sources that require memberships and login credentials – having a tool that can navigate around feed limitations and allow for credentials and related access implications is a major advantage over traditional secondary research methodologies. • Development of actionable insights from tool output generation – data generation is important, but the ability to develop actions from this data is what is key. The tool must be able to segment this information in order to visually identify key areas that allow the CI practitioner to easily interpret and readily develop action plans for strategic and tactical application. Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications <<
- 5. 82i am scip Special Edition • Leveraging of tool functionality throughout similar organizations within the parent company – this is an area that helps with Return on Investment (ROI) and can leverage not only the learnings from your organization, but to enrich the data collection and analytics to include peripheral requirements from potentially related businesses within your organization. VALUE PROPOSITION AND ASSESSMENT REVIEW Of course, as with any major system or tool implementation, there needs to be measurements in place to determine effectiveness and whether the tool has met overall expectations and deliverables, as outlined in the KPIs mentioned earlier. Every organization will have different specifics on how well the tool satisfied their needs, but there are some foundational elements that are applicable to most environments: • Not just a large volume of data processing, but the right data processed at the right time - secondary research analytics is readily available and easy to use, but KMS systems should bring a new dimension to filtering information so that it is most useful and most recent for up-to-date decision making on real- time market and competitive activities. The whole purpose of the tool is to equip the CI practitioner with better information to react quickly to market dynamics! • Generation of actionable insights – this is another key requirement; the information needs to not only be significantly more valuable than traditional secondary research sources, but also needs to be segmented in a way that allows the CI practitioner to easily navigate through the data and realize tangible insights. This should allow for quick interpretation and easy generation of recommendations and suggestions for strategic and tactical direction planning. • Support and enhancements moving forward – not all implementations are finite. There will probably be additional requirements, changing business conditions, and new learnings that will require modifications to the KMS model. The ability for the tool to allow for changes and the flexibility of the development / ability to incorporate modifications without major system upheavals are two other key determinants for CI practitioners to consider. Complex business market disruptions and changes in market dynamics will lead to exponential increases in data generation, and will put a great deal of stress on Competitive Intelligence models. Practitioners will need to be pragmatic in their data compilation and efficient in their analytics to stay ahead of the competition. Knowledge Management Tools are an effective means to managing data work streams and provide a vast array of valuable outputs and deliverables that will lead to actionable insights for effective utilization in organizational strategic planning. ABOUT THE AUTHORS: PaulSantillileadstheBusinessIntelligence and Customer Insights organization for Hewlett Packard Enterprise’s (HPE) WW OEM Business, and has been with HPE for 20 years. He is responsible for Business and Competitive Intelligence Modeling and Customer Insights analytics, where he is the Chairman of HPE OEM Executive Customer Advisory Boards worldwide. Paul also is on the Strategic Competitive Intelligence for Professionals (SCIP) Board of Directors and has presented worldwide on various topics related to CI in both keynote and workshop forums. Paul has a Bachelor’s degree in Engineering from the University of Michigan, and a Master’s degree in Engineering and Business from Stanford University. Stephanie Paulutt Stephanie brings 10 years of experience in Market and Competitive Intelligence with roles as a Web Intelligence Analyst, Project Manager, and Sales Manager for leading informationandintelligencesoftwarecompaniesinFrance and Germany. This year Bertin IT brought Stephanie on board as Sales Director for its Digital Intelligence Solution, AMI Software. Stephanie is responsible for business development in the DACH region (Germany, Austria, and Switzerland) where she supports her customers in the introduction and implementation of the AMI platform as well as associated processes and workflows. Stephanie holds workshops and delivers presentations on CI tool implementation at a variety of conferences and as a guest lecturer at the University of St. Gallen in Switzerland. >> Needs Assessment and Implementation Requirements of a Knowledge Management System for Competitive Intelligence Applications