Historical perspective. When can analytics enhance value of information?
Using analytics to utilize information.
Using analytics to extract information.
Collaborative filtering, Netflix challenge
Using analytics to collect information.
Information / Analytic services start up when a new sector of economic activity begins to take-off Information / Analytic Service Starting Points 2000 1990 1980 1970 1960 1950 1940 1930 1920 1900 IMS Health Brand Pharmaceutical market begins to take off R.L. Polk meets with Alfred Sloan to discuss information needs in growing auto market Polk Auto Registry Database A.C. Nielsen Network TV advertising opens up Early Mover position in an emerging market is critical Getty Images Digital Photography takes over Navteq GPS becomes commercially usable Stock market crash of 1907 Moody’s aQuantive Internet advertising begins to grow Morningstar Take-off in individual mutual fund investing Fair-Isaac Consumer credit goes mass market
We consider situations where information is already available
From ERP or other business process automation tools
Some enterprise generated view of the future
May be combined with purchased data from information services
Most examples now are within an enterprise or an enterprise driven value net
We focus on the case where analytics are applied to the information with the goal of optimizing the use of resources
Supply Chain Collaboration: IBM Buy Analysis Tool ( i BAT) Improve Inventory Cost in IBM's Extended Supply Chain Business Problem Solution Business Value
A significant percentage of IBM’s hardware sales in high-velocity servers are sold through major channel partners such as Arrow, Ingram, and Tech Data.
Lack of alignment between procurement, manufacturing, and channel sales resulted in significant price protection and sales incentive costs for IBM and high inventory-related costs for our channel partners
Web-based collaboration platform for IBM’s channel replenishment planning that c ombines innovative forecasting and inventory analytics with up-to-date visibility of channel sales and inventory data
Optimized buy recommendations for channel partners based on statistical forecasting techniques and risk-optimized inventory replenishment models
Proactive r eview system that initiates demand shaping based on supply and demand imbalances
Standard SOA-based solution design which can easily be adapted to specific ERP environments
Cornerstone of IBM Server Group’s Business Partner Transformation Initiative
Fully deployed with IBM’s largest channel partners across the United States, Canada and Europe
Solution enables business partners to carry 15-25% less inventory without negatively impacting their delivery performance
Lower channel inventory resulted in lower price protection expenses for IBM, improved cash flow, and higher operating margins
Available to Sell (ATS) Find saleable product recommendations to consume excess inventory Business Problem Solution Business Value
With shrinking product lifecycles, component supply overages can quickly lead to obsolescence requiring costly inventory writeoffs. One way to avoid this costs is to find products to build and sell that would consume the excess supply.
In a complex product environment such as IBM Servers, product build-out typically requires additional procurement of non-excess parts to “square” with the excess supplies. With part commonality across many possible product configurations, this leads to an enormous number of potential build-out strategies to choose from. Additional factors such as part substitution, re-work costs, and marketing constraints make this a difficult optimization problem.
ATS Engine uses IBM’s Watson Implosion Technology to find optimal sales recommendation portfolio given: excess part supplies, bill of material, procurement and value-add costs, product demand upper bounds, and product pricing.
Pegging module assigns excess consumption additional costs to each product in the sales recommendation allowing users to pick which build-outs to execute and promote in market.
What-if capability enables users to cost a targeted build-out plan, supporting end-of-life processes.
ATS Engine and Process fully deployed in IBM’s Systems Technology Group since 2002.
Solution drove build-outs and sales recommendations which consumed $200 million worth of excess inventory in 2002.
Ongoing usage of the tool keeps excess supply from becoming obsolete.
System is integrated with IBM’s Central Planning Engine with Web-based, on-demand availability within IBM STG.
Application Areas in Workforce Management Many opportunities to improve workforce management through utilization of information JAN APR JUL DEC DEMAND FORECASTING CAPACITY PLANNING STRATEGIC PLANNING TRAINING AND LEARNING SKILL&ENGAGEMENT ANALYTICS MATCHING & SCHEDULING ? x Now Target
Workforce challenges - The DATA is distributed in many enterprise applications
There is no single “Enterprise Resource Planning” tool for labor management
Supply (given in terms of roles or skills)
Traditional HR systems contain information about the current job
Structured: Position code, salary, location, shift, etc
Unstructured: Education, IBM courses, dept history, awards
New Job Role/Skill Set with job taxonomy and skill list
Full Text Resumes
Demand (given in terms of engagements or contracts)
Past and Current Contracts (and history of deal closure)
New opportunities: Sales Opportunity Database
Bill of resources = set of skills required to deliver an engagement
But billing database includes detail (by individual) on employees participation in engagements
And additional sources include contractor/engagement data
Business Consulting Examples Can range from one month, one skill set….. … .to more than 10 months, 16K hours, and wide range of job roles/skill sets Weekly variations appear to be driven by calendar effects, vacation schedules, and resource availability Supply Chain-PLM Engagements
Service offerings/opportunities are typically specified in terms of revenue and solution
Using statistical analysis and clustering, develop template staffing structure for offerings, which can be used to translate offering revenue forecasts and opportunity revenue into staffing resource requirements
Semi-automated and parameterized process for generating staffing templates and supporting software
Standardized project templates allow for planning of staffing decisions at earlier stages of the engagement process, more reliable forecasting of resource needs and better workforce planning
Enables partners/project managers to quickly develop staffing plans early in the opportunity cycle
Predictive accuracy of 70-80% at engagement level and 90-95% at aggregate level for major job roles
Deployed by GBS in the Demand Capture Tool 2.1 released in December 2006
ABC Client Name Plan Names No Linked to other projects? 4700000 Estimated Revenue 12/31/2004 End Date 1/2/2004 Start Date Package Configuration and Implementation Project Type SAP.SCM Modules SAP ISV Supply Chain Management Service Industrial Sector
Risk Based Capacity Planning Allows development of capacity plans according to business strategy. The best solution will be based on a combination of expected revenues/costs/profits, allowed risk tolerances with respect to revenue loss, and other business concerns, such as market-share and growth TECHNOLOGY ADOPTION PRODUCT SERVICES, US, 3Q05 Revenue at Risk ($M) Revenue curve Labor Cost curve Gross Profit curve 251 266 292 346 247 Capacity
Workforce Does Not Happen Overnight The use of analytics and optimization in workforce management applications requires significant maturity levels in terms of data, process and business understanding Automation Job taxonomies “ How to describe skills and activities” View of supply “ Infrastructure and process to capture available resources” Bills of materials “ Templates to describe projects/tasks to be performed” View of demand “ Infrastructure, process and analytics to forecast demand” Analytics & Optimization Nothing
Carbon as a New Variable in Supply Chain Decisions
Typical supply chain optimization only considers the direct monetary costs
Inventory and supply policies can be significantly different with the inclusion of broader environmental costs, and constraints
A good model can quantify both the cost and the carbon impact of various supply chain policies.
A comprehensive model can identify areas where carbon and cost reduction can be achieved simultaneously (e.g. minimization of wastage, rework etc)
Transportation Options Inventory Policy Options Quality CO 2 Cost Service Supply Chain Trade-offs Design Options Energy Options Packaging Options Process Options Component Options
Any Supply Chain Carbon View must be Multi-Dimensional Shrinkage ($, CO 2 cost) Breakage ($, CO 2 cost) Real Estate ($ cost) Handling ($, CO 2 cost) Transportation ($, CO 2 cost) Utilities ($, CO 2 cost) Manufacturing ($, CO 2 cost) Component Supply ($, CO 2 cost) Packaging Options Transportation Options Energy Options Inventory Policy Options Process Options Supply Options ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦
Correct for missing duplicates based on the estimated rating marginal of the users
Estimate the Scalar to rescale from marginal to total
4 Poisson regression models: 1, 2, 3 and 4 quarter ahead prediction of the number of ratings for all movies
Correct for decreasing user base by creating lagged datasets with removed users after deadline
Key point: Understanding the data domain and how the sampling was done was critical factor in accuracy of prediction
ASCOT ( A utomated S earch for C ollaboration O pportunities by T ext-mining)
We currently build OnTARGET models to predict purchase probability for existing IBM clients as well as “Whitespace” -- e.g. will they purchase an IBM Rational software product?
These models use historical IBM transactional data joined with D&B data
What if we added indexed content crawled from each company’s website?
We apply Active Feature Acquisition to minimize number of web sites we need to crawl
We find interesting terms on a company website that increases likelihood of a Rational SW purchase And the resulting model is more accurate than our existing OnTARGET model … Improvement due to web content Percent of Websites Processed Accuracy (AUC) Active Feature Acquisition Random Acquisition With Web Content Existing OnTARGET model (Without Web Content) 0 5 10 15 20 25
BANTER ( B log A nalysis of N etwork T opology and E volving R esponses) 77M Blogs Technology Blogs Enterprise Software Blogs
1. How do we identify the relevant sub-universe of blogs?
We submit set of relevant keywords to Technorati, include out-linked blogs, and then refine this sub-universe via active learning
2. How do we determine “authorities” in this sub-universe?
We use page-rank-like algorithms against cross-reference structure, combined with SNA concepts (e.g. Information Flow)
3. How do we detect emerging topics and themes in this sub-universe?
One approach is to predict link (cross-reference) formation using network evolution and content (keywords) at the nodes (blogs)
4. How do we detect sentiment associated with specific posts?
One approach is to learn a model using text features against labeled product ratings (1-5 stars) scraped from Amazon
OBJECTIVE: Apply machine-learning to extract business insight from technology-based blogs OpenID Buzz in January
Governments and large institutions are becoming less effective and efficient at providing affordable and reliable basic services (retirement benefits, health care, insurance, education) for individuals.
Individuals need to become increasingly self-sufficient in these regards
Individuals are turning to other individuals in a peer-to-peer fashion, to tap into the collective knowledge and financial pockets of communities (both virtual and physical).
In developing countries self-sufficiency may be only practical solution.
As peer-to-peer networks progress from serving ‘lighter’ (e.g., entertainment) needs to serving these long-term, basic needs, a more robust set of IT, communications and business services is required
manage new peer-to-peer applications
provide high-quality information and analytics services to individuals.
Peer-to-peer ‘services’ (e.g., social/micro lending, peer-to-peer insurance, homeschooling) are growing
There are risks and sources of uncertainty associated with peer-to-peer service: - Reliability and accuracy of web-based data - Fraud & Reputation (how do you know who you are really dealing with?) - Security of personal information - Reliability of web-based IT infrastructure
These risk factors are not new. However, the models required to adequately capture the characteristics of uncertainty in a peer-to-peer services environment may be different from traditional models used in more centralized business environments.
Additionally, the types of services that participants in the P2P environment require may also be different (e.g., more personalized uncertainty analytics services, mobile web).
Core technologies are available and gaining adopters (P2P, electronic health records, social networking sites, business integrity, business intelligence)
Will we see an emergence of companies whose business is to support P2P services networks?
Peer-to-Peer Insurance is preparing to launch a new type of insurance product, is based on pooling people together to insure each other at rates cheaper than they currently pay, without automatically losing the money they pay as premium. The Peer-to-Peer Insurance Project:
Peer-to-Peer Auto Insurance (safe drivers pooled together to insure each other)
Peer-to-Peer Home Insurance (categories of homeowners pooled together to insure each other)
Participants will not automatically, and permanently, lose all the money paid for coverage.
Incentive for safe driving (personal, and social good)
Credit score will not be used to set premium.
No age discrimination
No fine print. None of that sleek legal lingo buried in the middle of a thousand pages of policy.
What information is used to create pools? What information about pool is provided to participants? New methods for calculating risk may be required.
www.carbonfootprint.com calculates, compares to national average and proposes products to reduce or offset the footprint (like donating money for reforestation)
Enter information about your car make and model and miles you travel. Energy bills, flights you take, number of people in household, state of residence.
Can use for targeted marketing of alternative energy sources, hybrid cars, even travel packages.
Health and Fitness
www.revolutionhealth.com builds your profile, enables members to create webpages on topics interesting to them, supports blogs and communities, helps people find communities with similar health related interests.
Enter information such as age, interests, health history, fitness routine, etc.
Can use for health insurance marketing, drug marketing, weight loss programs, etc.