Lancet Data Sciences and Bluestem Brands

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1 Lancet Data Sciences and Bluestem Brands Man vs. Analytics Neil Gunn Bluestem Brands Inc. BI Manager Jason Todd Lancet Data Sciences Practice Leader & AE

can be tricky to understand Via http://en.

2 The Challenging Part of Analytics It can feel like team members are speaking a language that can be tricky to understand Via via mathsyear7.wikispaces.com

3 Agenda Consumable Analytics About Bluestem About Lancet A business centric approach Define Organize Match Maintain Matchmaking Advance analytical capabilities Future

the Year 2013 (#34)-Fastest growing private companies in the Twin

4 Lancet Data Sciences BI is in our DNA Became a MSTR partner in 1997 Multiple Practices Managed Services 2013 MSTR Solutions Provider of the Year 2013 (#34)-Fastest growing private companies in the Twin Cities 2013 Inc list of the fastest-growing private companies in America

5 Lancet Data Sciences Bluestem Brands Headquartered in suburban Minneapolis Parent company to three fast-growing, dynamic, multichannel retail brands. We provide a unique mix of retail and payment options for a diverse range of customers with a wide range of financial needs. Three campuses and more than 1000 employees

MicroStrategy Implemented in April 2012 100 Users less than a month after install Utilized visual insight to gain momentum

6 Lancet Data Sciences Bluestem and Lancet The Journey In 2010, Bluestem and Lancet collaborated on a BI Roadmap to transform our BI environment After implementation of a new Enterprise Data Warehouse, MicroStrategy was the final piece in the puzzle MicroStrategy Implemented in April Users less than a month after install Utilized visual insight to gain momentum Platform developed and administered by Lancet Today there are now 300 users of MicroStrategy in several different departments across Bluestem

Consumable Analytics: A business focused style A business centric language Tunnel Vision A Data Science Approach Define: Use case(s) & storyline(s) Organize:

7 Consumable Analytics: A business focused style A business centric language Tunnel Vision A Data Science Approach Define: Use case(s) & storyline(s) Organize: Business questions into desired flows Match: Business questions & Analytic methods Not just pushing buttons and configuring technical BI options Maintain: The approach

8 Define: Use case(s) & storyline(s) Consumable Analytics: Solving business problems Putting analytics in a business focused language that engages users Type Question Examples Historic Predictive Relation Grouping Classify What has happened? What will happen if these trends continue? Are these entities associated? How should I assemble these items? What s the chance of this outcome? Sum, Avg, Rank, Min, Max, Counts Linear & Exponential Regression, Time Series Affinity Clustering Decision Tree, Logistic Regression

9 Define: Use case(s) & storyline(s) Lancet Data Sciences From Whiteboard to Dashboard! What is the purpose of this dashboard? What questions am I trying to answer? What actions will be taken from this dashboard? How do I navigate here? Who is the audience?

10 Define: Use case(s) & storyline(s) Lancet Data Sciences From Whiteboard to Dashboard: Prototyping Lancet Mock-up Dashboard

11 Define: Use case(s) & storyline(s) Lancet Data Sciences From Whiteboard to Dashboard: The Final Product Confidential for live presentation only Final Dashboard Presentation

12 Competitive Advantage Organize: Business questions into desired flows Consumable Analytics: Most have seen Optimization Predictive Modeling Forecasting/extrapolation Statistical analysis Business Intelligence What s the best that can happen? What will happen next? What if these trends continue? Why is this happening? Alerts Query/drill down Ad hoc reports Standard reports What actions are needed? Where exactly is the problem? How many, how often, where? What happened? Sophistication of Intelligence Competing on Analytics: The New Science of Winning, by Thomas H. Davenport and Jeanne G. Harris (Harvard Business School Press, March 2007).

Organize: Business questions into desired flows Consumable Analytics: Organizing business questions What are my current sales? Historic Questions Year to Date? Quarter to Date? Month To Date? Today?

13 Organize: Business questions into desired flows Consumable Analytics: Organizing business questions What are my current sales? Historic Questions Year to Date? Quarter to Date? Month To Date? Today? Predictive Questions Forecast this month? Forecast this quarter? Forecast this year? Solution with match the desired information flow Builds an information app vs unsynchronized dashboard Reduces dashboard build time Engages the user community

14 Match: Business questions & Analytic methods Consumable Analytics: Matching Which stores have a similar product sales pattern? What is my sales forecast? What are my cross-sell recommendations? What s my optimal investment choice? What is my average defect rate every 10 days by location? How do I rank against my peer in the last 30 days? Analysis/Method Logistic Regression Time Series Association Decision Tree Clustering Rank Moving Average Regression (Linear & Exp.) Algorithm K-means

Condition Transformations Properties Use Metrics Anywhere Dashboards Consolidations

15 Match: Business questions & Analytic methods Consumable Lancet Data Analytics: Sciences Create Personalized Expressions Expressions (rich features) Formula Level Condition Transformations Properties Use Metrics Anywhere Dashboards Consolidations Filters Subtotals Prompts Custom Groups Deployable to Web Mobile Office Common Metric Definitions!

Match: Business questions & Analytic methods Lancet Consumable Data Sciences Analytics: Association Use Case What are my cross-sell recommendations?

16 Match: Business questions & Analytic methods Lancet Consumable Data Sciences Analytics: Association Use Case What are my cross-sell recommendations? Analysis/Method Association What products do customers commonly buy together? Important Considerations! What is the time horizon? Are there any exclusions? What is the dimensionality? In a single shopping visit or over customer lifetime?

17 Match: Business questions & Analytic methods Lancet Consumable Data Sciences Analytics: Association Use Case Lancet Mock-up Dashboard

Lots of fish in the sea for matchmaking Can

parameters Lots of opportunity to utilize.

& Operators Date & Time Financial Internal &

OLAP & Rank Sum Count Average First Min Max

Current Date Current Time Hour Minute Month

Duration Apply Simple Apply Agg Banding Case

Is not null Null Null to zero Zero to null

18 Match: Business questions & Analytic methods Consumable Analytics: Comprehensive Library Lots of fish in the sea for matchmaking Can help to improve performance Dynamic parameters Lots of opportunity to utilize. Basic Comp. & Operators Date & Time Financial Internal & String Logical & Zero Math & Stat. OLAP & Rank Sum Count Average First Min Max Last > < = Like Between + - () Add Days Current Date Current Time Hour Minute Month Quarter Year IRR NPV PV PMT Rate FV MIRR Duration Apply Simple Apply Agg Banding Case Coalesce Concat Position Trim And If Not Or Is not null Null Null to zero Zero to null Int Round Slope Power Tan AvgDev Forecast Growth Intercept Mov. Avg Mov. Count Run.Avg Run. Max Run. Min Ntile Rank Percentile

Match: Business questions & Analytic methods Consumable Analytics: Solid data mining foundation Parameterized models Accepted algorithms View model details Lots of opportunity to utilize.

19 Match: Business questions & Analytic methods Consumable Analytics: Solid data mining foundation Parameterized models Accepted algorithms View model details Lots of opportunity to utilize. Analysis Details Uses Linear Regression Ordinary Least Squares Forecasting Exponential Regression Ordinary Least Squares Forecasting Time Series Exponential Smoothing Forecasting Logistic Regression Iteratively Re-weighted Least Squares Predicts Categories Decision Tree CART algorithm Predicts Categories Clustering K-means algorithm Grouping Association Rules Apriori algorithm Affinity

20 Match: Business questions & Analytic methods Consumable Analytics: A business centric approach Pass-thru functions PMML R Plug-In GEO API s Lots of opportunity to utilize.

21 Match: Business questions & Analytic methods Lancet Consumable Data Sciences Analytics: Integrating Tools Limited to 4GB currently 64 bit will be coming!

22 Match: Business questions & Analytic methods Lancet Data Sciences Consumable Analytics: Building Models Analytical Lifecycle Create Dataset Build Deploy Maintain Analyze options Analyze variables Validate Model Calibrate Model Presentation Review as-needed It can be an iterative process Baseline knowledge of data mining algorithms Metadata is critical for success Many visualization options to display the output

Maintain: The approach Consumable Analytics: Analytical lifecycle A Lasting Relationship Building is only the 1 st step Monitor & Maintain is sometimes forgotten Schedule frequent

23 Maintain: The approach Consumable Analytics: Analytical lifecycle A Lasting Relationship Building is only the 1 st step Monitor & Maintain is sometimes forgotten Schedule frequent business reviews On predictive metrics, review your accuracy Adjust model parameters as needed to fit the situation in the field Analytical Lifecycle Monitor & Maintain Build Deploy

What are my most run reports? Which reports or cubes run the longest?

24 Maintain: The approach Lancet Data Sciences Consumable Analytics: Monitor & Maintain Enterprise Manager has a wealth of data waiting to be explored! What are my most run reports? Which reports or cubes run the longest? Are users experiencing errors? Who are your power users? Should I look into my cube strategy? Am I meeting my SLA s?

Maintain: The approach Lancet Data Sciences Consumable Analytics: A business centric approach Language: Chat Session gone awry A business centric language A Data Science Approach Define:

25 Maintain: The approach Lancet Data Sciences Consumable Analytics: A business centric approach Language: Chat Session gone awry A business centric language A Data Science Approach Define: Use case(s) & storyline(s) Organize: Business questions into desired flows Match: Business questions & Analytic methods Via Maintain: The approach

26 Maintain: The approach Lancet Data Sciences Consumable Analytics: Future Stats & Entertainment? A new kind of capital Data Quality Security, Risk, & Compliance Localization Cross Sell Logistics

Add Sophisticated Analytics to Your Repertoire with Data Mining, Advanced Analytics and R

Add Sophisticated Analytics to Your Repertoire with Data Mining, Advanced Analytics and R Why Advanced Analytics Companies that inject big data and analytics into their operations show productivity rates