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Smart Process Design: Continuous Improvement to Leverage the Right Technology - Corporate Legal Operations Consortium - CLOC

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Corporate Legal Operations Institute, May 2017
A technology-first approach can distract us from asking the right questions and solving the right problems. We must start with processes. By designing smart processes, we can increase the efficiency and quality of legal service delivery, generate actionable data, and pave the way for future continuous improvement. We will:
• Introduce smart processes for gathering data and improving efficiency, quality, and substantive outcomes;
• Use maps as knowledge production and management tools that can also be used for communication and training; and
• Discuss how cross-functional alignment and communication between the legal ops team, in-house counsel, and the other departments of the business can be furthered with this approach.

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Smart Process Design: Continuous Improvement to Leverage the Right Technology - Corporate Legal Operations Consortium - CLOC

  1. 1. Jose Torres Fellow, Legal Design Lab Center on the Legal Profession Stanford Law School Twitter: @1jftorres Smart Process Design: Continuous Improvement to Leverage the Right Technology Daniel W. Linna Jr. Director of LegalRnD - The Center for Legal Services Innovation Professor of Law in Residence Michigan State University College of Law Twitter: @DanLinna
  2. 2. Challenges
  3. 3. “ ◉How might we leverage technology without being distracted by technology “solutions” searching for problems?
  4. 4. “ ◉How might we leverage legal operations to improve substantive legal work and outcomes?
  5. 5. “ ◉How might we deliver greater value to the business across the whole value stream, from beginning to end?
  6. 6. How might we integrate efforts for maximum leverage? Tech
  7. 7. “ ◉Is technology the answer?
  8. 8. Technology First is a Problem “The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” – Bill Gates Source: Lean Ohio, Innovate Before you Automate, http://lean.ohio.gov/Portals/0/docs/info/LeanOhio_Innovate_Before_You_Automate_july2015.pdf
  9. 9. “ ◉If tech is not the answer, then what?
  10. 10. Smart Process Design
  11. 11. LeanData KM Technology Integrate 4 Areas
  12. 12. Lean Thinking
  13. 13. Lean Thinking
  14. 14. Applying Lean to Knowledge Work Can generate significant benefits, including: ◉ Lower costs ◉ Faster response time ◉ Higher quality and creativity ◉ Better outcomes ◉ Reduced drudgery and frustration ◉ Greater job satisfaction
  15. 15. Defining Lean ◉ Lean is getting the most value for the customer using the least amount of resources with the shortest overall lead time. ◉ The customer defines value.
  16. 16. Applying Lean Thinking – Step 1 Identify customers and specify value: ◉ End customer; ◉ Every person or activity in a value stream.
  17. 17. Applying Lean Thinking – Step 2 Identify and map the value stream: ◉ What are activities and steps in the process? ◉ What is the sequence and dependencies? ◉ How does information flow? ◉ What is the lead time?
  18. 18. The Purpose of Mapping ◉ Compare planned to actual ◉ Establish baseline metrics ◉ Identify opportunities to eliminate - Waste - Unevenness - Overburden - Complexity
  19. 19. M&A Example
  20. 20. Contact Law Firm M&A PROCESS MAP OVERVIEW Scope Services Document Engagement Create Case Team Formation Deal Management Draft Contract Negotiate Contract Close Deal Due Diligence
  21. 21. Early Due Diligence Assessment Due Diligence Request List Client Specific Queries Perform Due Diligence Send Clarifying Requests Zoom In - Due Diligence Process Finish Due Diligence Draft the Report Use Info for Negotiation
  22. 22. Waste (Muda) ◉ Defective Production ◉ Overproduction ◉ Waiting ◉ Non-used Employee Talent Wikipedia, the Free Encyclopedia, Muda, at http://en.wikipedia.org/wiki/Muda_(Japanese_term) ◉ Transportation ◉ Inventory ◉ Motion ◉ Excessive (Over) Processing
  23. 23. Sources of Waste in Contracts ◉ Reviewing, preparing, or concluding contracts; ◉ Obtaining contract approval; ◉ Tracking due dates for contract deliverables; ◉ Bottlenecks due to insufficient personnel and resources.
  24. 24. PDSA – Scientific Approach to Process Improvement ◉ Plan ◉ Do ◉ Study ◉ Act Source: The W. Edward Deming Institute, https://deming.org/management-system/pdsacycle
  25. 25. Embedding Data into the Map
  26. 26. Data Analysis Process Get Data Explore Data Model Data Visualize Results Use Results Use Results in Business Business Application
  27. 27. Gathering and Embedding Data Example: Due Diligence
  28. 28. Why Due Diligence Data in M&A? ◉ Confirm strategy and transaction fit ◉ Verify operations and assets ◉ Predict and limit inherent acquisition risks ◉ Determine business plan feasibility
  29. 29. “ ◉ Capture Data at Every Step of the Process
  30. 30. Collecting Structured Data ◉ Checklist ◉ Template ◉ Final Product
  31. 31. Early Due Diligence Assessment Due Diligence Request List Client Specific Queries Perform Due Diligence Draft Report Capturing Due Diligence Data
  32. 32. ABA’s Due Diligence Checklists
  33. 33. Liabilities Dashboard Environment Employment. IP Litigation
  34. 34. Compliance IP Employment Litigation Environment Deal4 Aggregated DD Data Deal3 Deal2 Deal1
  35. 35. Use Aggregated Data to Negotiate better deals Improve contract drafting Improve compliance Manage outside counsel better 1 2 3 4 5 Price transactions better
  36. 36. Gathering and Embedding Data Example: Contract Performance
  37. 37. Draft Contract Review with Client Negotiate Contract Review with Client Finalize Contract Contract Negotiation Process
  38. 38. Acquisition Terms Background/Details Comments/Notes Structure of Acquisition - Asset - Stock - Merger Escrow/Holdback - None - Escrow - Holdback Reps & Warranties USE DD DATA ABA Drafting Guides
  39. 39. 0 1 2 3 4 5 0 1 2 3 4 5 0 2 4 6
  40. 40. Compliance IP Employment Litigation Environment Deal4 Aggregated R&W Contract Data Deal3 Deal2 Deal1
  41. 41. Feed Contract Lifecycle with End-to-End Data Improve Contracting Process Understand Contract Structure Negotiate Perform Gather Performance Data Gather Litigation Data
  42. 42. Comparing effort vs. value IACCM Top Terms 2013/2014
  43. 43. Use Aggregated Contract Data To Better communication with business units Negotiate better deals Improve contract drafting Train attorneys 1 2 3 4 5 Improve external business relationships
  44. 44. Continuous Improvement Issues (disputes, friction) Contract Performance Contract Drafting Negotiation DD Process
  45. 45. Smart Maps = Knowledge Management
  46. 46. Smart Process Map as KM Tool Preparation for Acquisition Acquisition Task Checklist Initial Deal Scoping Discussion Deal Management Discussion Outline Deal Issues Negotiating Tool Deal Issues Drafting Guide Early Due Diligence Assessment Deal Kickoff Meeting Checklist Roles and Responsibilities Chart Task Status Report Post-Matter Assessment
  47. 47. Capture Data at Every Step
  48. 48. Identify Complexity of Work Standard Standard Bespoke Systematized Bespoke Packaged Commodity Standard Standard Bespoke Bespoke
  49. 49. Map + Data Captures Knowledge ◉ Codify repeatable parts of the process; ◉ Framework for continuing study of tacit work.
  50. 50. Choosing the Right Tech
  51. 51. Right Technology for each Step of the Process ◉ Expert systems ◉ Contract review and due diligence tools ◉ Excel + database for templates and checklists ◉ Pave the way for AI
  52. 52. Early Due Diligence Assessment Due Diligence Request List Client Specific Queries Perform Due Diligence Draft Report Leveraging Tech – Due Diligence Example Process Tech Expert System Excel + Database Doc Assembly Contract Review Tools Expert System
  53. 53. Leveraging Structured Data from Smart Maps SQL Expert System AI Data Excel
  54. 54. UX Software to Prototype Smart Maps
  55. 55. LeanData KM Technology Smart Process Design
  56. 56. Questions? You can find us at ◉ jftorres@stanford.edu ◉ Twitter: @1jftorres ◉ linnadan@law.msu.edu ◉ Twitter: @DanLinna Thank you!

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