How to Create a Data Driven Contract Management Process

Editor's Notes

• #2: Jason open
• #3: Introduction Jason to intro team Journey of CLM at HPE (3 step chevron) Where we started What we changed (from last presentation) What we have coming Soft segue: data is the only way to get where we’re going…. Background for the session: Defining Your Drivers (Data is more than one thing) Quantitative: Why this is such a challenge for so many Qualitative: How to avoid the pitfalls of opinion Qualitative story We had a shift to high value deals a year ago (recap). (Molly to tell us what to include from Jack) Focus on shifting work to appropriate location Agility center or onshore (Jack Lee’s data) Design, measurement and outcomes.  What does the process looks like to support the shift. (Process map??) Quantitative Formation of user group from diverse practice areas. Outputs from the group. (Lauryn to sanitize to Apttus generic; not HPE specific) Utility gaps identified. (Dan Duryea can provide) Shift to Azure version Expected benefits and how we will implement. Bifurcated Qualitative and Quantitative path Sources for each (User Community and Raw Data). Suggestions on how to identify these to the audience Qualitative and quantitative continuous improvement Best practices on how to tactically support this “One Thing”…if you only remember one thing from this session, it should be X
• #4: Jason
• #5: Molly and Michael Soft segue: the only way to get where we’re going is through Data….
• #6: Molly
• #7: Molly Response target < 36 hours, actual <20 hours, total turnaround time reduced by 10% during FY16
• #8: Molly and Michael
• #9: Michael
• #10: Michael Link to issues we addressed: (1) too much time on small deals, and (2) issues with CLM for public sector contracts Discrete, good bad, yes no. Failed or not. Great for check sheets. Continuous, measured on a scale, can be broken down into pieces (project, tasks, etc..). I’m not going to give a lecture on the types of data. What is important is that use our data to uncover key symptoms. Our initial data analysis often encourages people to jump to a solution. This is a distraction. Initially we have just a symptom. For example we had a call center representative that was responsible for 95% of all keyboard shipments in Brazil. The immediate reaction as to confront her. I stopped all action and continued through the process to root cause after reviewing all of our suspect issues. We discovered that IT had to pick a code for outbound shipments and randomly selected her employee code for all web orders. Let the SMEs come up with their list of suspects that will be compared to process analysis and drilled into for root cause.
• #11: Michael Now that we have talked about both data and process lets take a look at how we combine the
• #12: Michael One example of reducing waste and improving efficiency is a project to help us manage government contracts. Anyone who deals with government contracts knows a deal worth a $1B is actually worth $0 until you get a “Task Order” So how does a system handle the management of the valuation of government contracts? How do you make sure you don’t miss out on approved funding if you don’t know the residual value of a contract? By performing process and data analysis we identified 5 root causes driving 17 problems. If we had just solved symptoms we would have chassed 17 individual problems and created 17 solutions. Instead we found 8 processes that need clarify and simplification and launched 1 modification to our CLM tool Apttus. When we were done we had made four key improvements:
• #13: Jason and Lauryn: With over 3 million data points available in Apttus, not to mention the other solutions in place that support the end to end contract management process, it can be difficult to separate the actionable data from the noise. It’s very important to validate that your data capture strategy correctly identifies a data point as quantitative, qualitative, or something else entirely. Quantitative data is a challenge for many due to the lack of consistent data to measure. A certain amount of inference is often needed to get started. If you are in a position where you don’t have normalized data, what assumptions can you truly make to allow for a “go forward” strategy to quantitative measurements? Be prepared for the uninformed pushback, i.e. “We used to do it faster when we didn’t have a system”. Qualitative data is naturally subjective, but the validity of the subjectivity must stand up to scrutiny. It is acceptable to ask for user opinion and apply a scale, but be prepared for outliers. Example: in a recent project, survey participants were asked to rate 10 topics on a scale of 1 to 5. When the results were provided, answers ranged from 0 to 2.5 to one person who wrote 4 1/5. Apply a scale and use it to help eliminate errors in responses that heavily represent bias. Bias is the “court of public opinion” and can kill a data driven contract process. Bias is very difficult to eradicate once it is introduced to a data strategy, so take great care to avoid it. For example, evaluate what subjective qualitative measurements are most at risk for bias and discuss as a team. Either the scale or the interpretation of this data can be adjusted to avoid bias.
• #14: Jason and Lauryn
• #15: Lauryn with inputs/color commentary from all
• #16: Lauryn
• #17: Lauryn
• #18: Lauryn
• #21: Jason In our 10+ years of experience delivering contract management solutions to the world’s mid-sized organizations and the who’s who of the Global 1000, we’ve developed the five stages of contract management maturity. As customers move up the maturity model, return on investment increases. The stages are: Accessibility and Compliance. This is achieved with all contracts in a single global repository. Typically our customers begin with this step so they can search for and organize contracts, comply with global rules, and get confidence and excitement for further steps. Almost all of our customers do this. Analysis for Action. The next step is to put reporting and workflows in place. About ¾ of Apttus customers are doing this. The repository enables alerts for individual contracts and reports on sets of contracts, covering any aspect of the contract: key dates for renewals, cycle times, behavior of individual users, clause-level reporting, trends and much more. We also have workflows that route the information and actions correctly, and based on dynamic conditions. Control of Language. The third step in maturity, often implemented along with the second step, is automation of contract authoring. Self-service wizards can be set up to allow users to generate their own accurate contracts without creating any risk. And authoring and negotiation tools, built in Microsoft Word, let attorneys and legal ops professionals work with total access to approved language and full visibility to every change and every version. This saves time and improve negotiating outcomes. About ½ of companies have made it here—though even those companies that haven’t are happy with the value they are getting from the lower steps on this pyramid. Perfect Execution. In Stage 4, you turn the contract into instructions for the rest of the business with Obligation Management technology. What this does is take all the contracts terms and sends them to the right people for action. This includes options and conditional “triggered” events. In other words, your contracts go work for you automatically: It’s as if each contract is a piece of software that kicks off as soon as the contract is complete. This is true 21st-century business process, creating real leading-edge efficiency and risk reduction. About a third of Apttus customers have started down this path. Full Automation. Want to run a true digital business? That means all your systems are running together, in concert with each other. Apttus offers Contract Management on a common platform with Quote-to-Cash and Supplier Relationship Management applications, and we have experience connecting to CRM systems like Salesforce and Microsoft Dynamics, and have integrated our software to every major ERP including Oracle and SAP hundreds of times. Most Apttus customers have integrated Apttus Contract Management to at least one system, however this is the top of the pyramid because total end-to-end automation is the end-state vision. Companies with this vision are going to lead their industries because they will be simply more efficient, more responsive to customers, able to operate at lower cost, and less exposed to foreseeable risks. The contract is at the center of this transformation vision. Increasing ROI. As you add more capabilities and more process, you will capture ever more value from your contracts. Even the first step on its own offers positive ROI—moving up from there just increases your ROI further. And you can get even more value from every stage of contract maturity with artificial intelligence. Max Value with AI: Apttus deploys artificial intelligence across our customer journey. We offer conversational interfaces for users to request contracts, find contracts, approve contracts and more using text, chat, and apps—AI provides the logic to provide the correct response to your needs. We also offer Apttus Intelligent Import™, which scans and understands third-party and legacy contracts so you can understand every detail about even those contracts you don’t create in Apttus. This capability works for a single contract or for 1000s of legacy agreements. And we offer predictive contracting to help authoring and negotiation: Recommending the right language to reduce risk or speed up cycle times.