Monitoring Competitive Dynamics to Anticipate Industry Change
1. Competitive Intelligence Monitoring Competitive Dynamics to Anticipate Industry Change Arik R. Johnson LifeScience Alley Founder & Managing Director Twin Cities, Minnesota Aurora WDC Friday 19 September 2008
2. Emergence of the Intelligence Community & Think Tank Model for TASKING > SENSING > INTERPRETATION
8. Competitors, Customers & Technologies Are Complex Interdependencies CI is about “Seeing Clearly” through Market Illusions
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11. Traditional CI Follows a Disciplined Process for Information Collection and Analysis Deliver, Inform & Recommend Planning & Direction Secondary Research Analysis & Production Primary Research Tactical Users & Strategic Decision Makers Needs The Traditional CI Cycle
14. Impacts on Planning & Execution Your Company’s Plans and Execution Vision and Grand Strategy Strategic Plans Market Success Operational Projects and Programs Tactical Execution Other (More-or-Less) “Uncontrollables” Competitors’ Plans and Actions New Forms of Competition X Y Z P Q R A B C Indirect Competitors Direct Competitors Government and Regulatory The Economy Technology Market Trends Industry Rationalization Other Unknowns
15. CI is a Critical Element in Strategy COMMERCIAL MARKET STRUCTURE & RESOURCES Strategic Position Strategic Position Competitive Position Market Attractiveness Scope & Context Strategic Issues Insight Stakeholder Score Card Financial Position Growth Economic Profitability Critical Success Factors & Key Performance Indicators Performance Monitoring & Incentive Compensation Organizational Design Projects & Resources CAPITAL MARKET MANAGED PERFORMANCE Chosen Strategy Scenarios & Options Creativity Strategy Execution Strategy Formulation
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22. Source Extraction & Pattern Recognition Aggregate content, tag & categorize Hypertext links to similar content Personalization from forms/questionnaires geodemographic profiling Searching for information E-mailing information to relevant recipients Reformatting for multi- channel delivery, e.g. PDF to XML Answering customer inquiries via a help desk Manual Processes Process Automation Aggregation Automatic Categorization Hyperlinking Profiling Personalization Collaboration Delivery Retrieval Routing Alerting Integration Through Understanding Information Theory and Bayesian Inference Notes News Feeds Email Internet Database Files Document Management XML Audio/ Media
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25. Analysis is Key The Difference Between Data and Intelligence “ The competitor would make a good acquisition candidate. Its lean & mean structure would fit well with our current operations.” Intelligence: The insight that will allow you to make an informed decision “ After gathering more operational information and running a side-by-side profit & loss analysis, it appears the competitor has become highly efficient. It exceeds industry standards and has become a best-in-class facility.” Analysis: Distilled information “ Based on the D&B and the salesperson’s report, it appears the competitor has lost business.” Information: A pooling of these bits of facts, observations and rumors 2001: “The D&B report told us that the competitors plant had 100 employees.” 2004: “One of our salespeople just passed by the competitor’s plant and spotted only 30 cars in the lot.” Data: Scattered bits and pieces of facts, observations and rumors
29. Level of CI Involvement in M&A Stage ID Evaluate Due Consum- Criteria Targets Analyze Diligence Recommend Negotiation mation Integration Level of CI Involvement High Low Intelligence Research Business Units Finance Technical Assessment Legal Executives M&A Specialists Transition Team Logistics HR
40. The Duality Continuum of Reconnaissance includes Both Decisive & Incisive Sensing Incisive Scanning for Trends, there is no “Decision” to be made Framework for Interpretation Recognize “Pattern Vector” History Implications for the Reader Bottom-Up Exposition Driven by Trends Outcome is Often Observation Itself Emergent & Theoretical Decisive Frame of Reference is the Decision, Less Trend-Dependent Framework for Current Analysis Compares Options & Outcomes Recommendations and Trust Top-Down Imposition Driven by Issues Decision & Action vs. ‘Nariyuki’ Factual & Hypothetical
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49. “ Competing head-to-head can be cutthroat especially when markets are flat or growing slowly. Managers caught in this kind of competition almost universally say they dislike it and wish they could find a better alternative. They often know instinctively that innovation is the only way they can break free from the pack. But they simply don’t know where to begin. Admonitions to develop more creative strategies or to think outside of the box are rarely accompanied by practical advice.” Chan Kim and Renee Mauborgne
50. Most Attempts at Innovation Fail But by integrating three types of insights - customer needs, competitive patterns, and a company's own capabilities - and combining them with solid protocols, innovation becomes a routine competence and companies can double or triple their success rates. And the really big hits are often the products that innovate in not one but two or three or more "innovation spaces."
55. Customers “Hire” Products to Do “Jobs” for Them Concentrate Less on What Customers “Want” and More on What Customers “Need”
56. RPV Theory: Building Capabilities Processes Ways to Turn Resources into Products/Services Hiring/Training Product Dev. Manufacturing Budgeting Research Values Prioritization Criteria for Decision-Making Cost Structure Income Statement Customer Demand Opp. Size Ethics Resources Assets the Firm can Buy or Sell, Build or Destroy People Technology Products Equipment Cash/Brand/Distr.
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58. Disruptive Innovation Theory Sustaining Innovations Better Products Brought to Established Markets Low-End Disruptions Target Overshot Customers with a Lower Cost Business Model New-Market Disruption Compete Against Nonconsumption Difference Performance Measure Time Nonconsumers or Nonconsuming Contexts Performance
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60. Process of Predicting Industry Change Signals of Change Strategic Choices Influencing Success Likely Outcome of Competitive Battles
61. Different Missions, Different Approaches Specialist Slow Production, Less Output, More Analytical Agenda Driven by Contact Network Lots of Subject Matter Knowledge Seeks Explanation of the Subject Investigative Very Slow, Curious, Historical Little Output, Highly Analytical Questions Official Positions, Listens to Nonspokesmen Operates Outside Publisher Agenda Generalist In a Hurry, Lots of Output, Less Analytical Agenda Driven by the Publisher Little Knowledge of Subject Matter Seeks Volume of Public Interest
