Are You Able to Predict? Brian Stedman Product Specialist, ComSci

Transcription

1 Are You Able to Predict? Brian Stedman Product Specialist, ComSci

2 Agenda : Are You Able to Predict Introductions Descriptive and Predictive Analytics What Does "KPI" Mean as Predictive Measures in Place Guiding Principles to Follow Examples & Use Cases Final Questions 2

3 Rule of Thumb S M A R T 3 3

4 Without Interpretation, Data Is Just Numbers 4

5 Some Lessons are Self Taught 5

6 Some Lessons are Self Taught An organization s ability to learn, and translate that learning into action rapidly, is the ultimate competitive advantage. 6

7 Predictive Business Analytics Using Predictive Business Performance Metrics Will Increase Profitability 20% by 2017 Gartner 7

8 Predictive Business Analytics Using Predictive Business Performance Metrics Will Increase Profitability 20% by 2017 Gartner Increase profitability Alert best next action to take Using historical measures only, will not prevent an unforeseen event 8

9 The Business Intelligence Hierarchy Power of Information Raw Data Standard Reports Descriptive Modeling (with analytics) Ad hoc Reports & OLAP Predictive Modeling Optimization $ROI Two types of software are like a brain s two halves. Data Information Knowledge Intelligence Transactional systems (e.g., ERP) the reptilian brain stem (breathing, blinking, digesting) Predictive Business Analytics and Performance Management the cerebral cortex (thinking and decision making) 9 9

10 Predictive Business Analytics Predictive analytics can reduce costs produce actionable outlooks reporting improve business performance To prevail in challenging market conditions, businesses need predictive metrics. 10

11 Predictive Business Analytics Predictive analytics can reduce costs produce actionable outlooks reporting improve business performance To prevail in challenging market conditions, businesses need predictive metrics. 90% attained a positive ROI 66% say it provides very high or high business value. 11

12 A Working Definition 12

13 A Working Definition Predictive Analytics Business Analysis Driver-based Forecasting 13

14 It Is a Process a Methodology A process encompassing a range of techniques dealing with the collection, classification, analysis, and interpretation of data to gain insight, reveal patterns, anomalies, key variables, and relationships. 14

15 If You Could Improve One Aspect of Your Metrics Creation, What Would it Be? a. Use business performance metrics to improve quality decision-making b. Adopt broader set of metrics (i.e. non-financial, risk and control) c. Tighten alignment between corporate wide and operating unit metrics d. Have better tools to produce scorecards 15

16 How Predictive Business Analytics Works As the organization understands / becomes more confident in the insight of the cause and effect relationships. 16

17 Comparison to the Study of Weather Weather Data collection sensors for temperature, humidity, wind speed. Current conditions summary reporting. Future prediction capability weather models with partial differential equations. 17

18 Further Illustration Weather Data collection sensors for temperature, humidity, wind speed. Current conditions summary reporting. Future prediction capability weather models with partial differential equations. Business Data collection sensors on sales, orders production, pipeline, economic conditions. Current conditions business reports. Future prediction capability models with partial differential equations advanced analytics. 18

19 Continuous Framework Design, Measure, Report Process Design Model Development Data Capture Report Results Guiding Principles Analyze/Monitor/Manage 19

20 Model Development: Performance Drivers & Risk Measures 20 External / Economic Governance and Control Interest Rates Commodity Prices Competition Business Strategies Business Model Efficiency Growth / Retention Market Share Customer Penetration Mix/Substitution Price Activity Intensity Channel Utilization Service Level Quality Productivity Rates Capacity Utilization Spending Initiatives Capital Investment Authorities Roles and Responsibilities External Factors Identify potential causal drivers Statistically test historical relationships Identify vital few with strong correlation Develop and test predictive model Internal Factors Define levels of performance Identify key drivers of cost Identify links to revenue model Identify risk factors and mitigations Identify links to KPI indicators Scenarios Determine What-if scenarios Monitor early warnings and trigger points

21 Change - Management sets the Tone Why didn t we anticipate that in the budget? Who screwed up? 21

22 Change - Management Sets the Tone Why didn t we anticipate that in the budget? Who screwed up? Okay, clearly things have changed 1. What are the major drivers of the change? 2. What are the implications for our business going forward? 3. What actions should we be taking as a result? 22

23 KEY PERFORMANCE INDICATORS How companies translate providing greater visibility and insight from accurate, reliable, and relevant information 23 23

24 Selecting KPIs Align Key Performance / Risk Indicators with strategic objectives Select the critical few Seek a balance between lead and lag indicators 24 24

25 DASHBOARDS VERY IMPORTANT Focus on important KPIs and measures Real time and predictive business analytical insights Highly visual impact and intuitive Provides insight into external factors and environment Use with observation, experience and intuition 25 25

26 Selecting KPIs Outcome (Lag) Measures Driver (Lead) Measures Purpose" Focus on the performance results at the end of a time period or activity" Measure intermediate processes and activities" Examples" year-results " utilization baseline " cycle time " Hours spent with customers" # of mortgage applications" Strengths" Usually objective and easily measured" More predictive in nature allows organizations to adjust behaviors for performance" Issues" Outcome measures reflect success of past, not current activates and decision" Based on hypotheses of strategic cause and effect " Sometimes difficult to collect supporting data" 26 26

27 Testing the Driver Relationships Gut Feel drivers are a good start but are often not reliably correlated with results Results should be tested against multiple variables using statistical analysis Back-Testing Measure and adjust on an ongoing basis; look for new drivers 27 27

28 IT Strategy Map Sustained IT Value IT Value perspective Manage IT unit cost Optimize IT portfolio Manage IT spend Enable BU value-add Competency Credibility Control Contribution User perspective Be cost competitive Serve us reliably Do things right Partner with Me Operational perspective Manage service quality Achieve scale economies Improve internal processes Standardize platforms and architecture Deliver on time Support end users Improve business productivity Manage risk and security Define enabling solutions Discover emerging technologies 28 28

29 Application Rationalization Holistic Applications Portfolio views to optimize performance and costs Drill-down capability to individual application descriptives and key metrics Application SLA and Cost Details Application Description and Overview System Generated Cost Optimization Recommendations 29 29

30 Scorecard Example Trends and forecasts Narrative discussions and business analysis Analysis of results Identification of business risk Discuss key decisions, feedback and forecasted actions Hot topics / key issues Ref # IP2.1 IP2.2 Asset Development Cycle Time Reported Results by KPI and performance measure Actual, Plan, and Variance to Plan for current period, YTD, etc. Strategic Objective: Develop Asset Value MTD YTD Act Plan Var to PL Act Plan Var % KPI: Asset Development Cycle Time POC to Launch (Avg. # of Days) % % # of amendments issued per protocol % % POC acceptance to Phase III Start (Avg # of wks) % % KPI: Launch Uptake # of Days from 1st Launch to Last Launch % % % of Asset Value achieved in 1st 3 years 25% 40% 63% 25% 40% 63% Rate of Revenue growth in 1st 3 years % % 30 30

31 Guiding Principles Demonstrate a strong cause-and-effect relationship Contain a balanced set of financial and non-financial, internal and external measures/ drivers Be relevant, reliable and timely for decision makers (i.e. fit for purpose ) 31

32 Guiding Principles Ensure data integrity Be accessible and well organized Integrate into the management process Drive behaviors and results 32 -

33 Leaving One Last Thought to Ponder S M A R T 33 33

34 Leaving One Last Thought to Ponder Simple Measurable Achievable Results Oriented Timely 34 34

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38 Enterprise Work Management Run smoothly. Change quickly. Achieve more. 38