Case Studies
Over the course of the last few decades we have helped dozens of companies create data roadmap that convert data assets into innovative products @ scale. Below we offer a small snapshot of such cases.
Improving demand forecasting @ global food & beverage conglomerate.
PROBLEM:
Original forecasting solution in SAP was based on sales history (only) and average just above 60%
Can alternative data and machine learning improve forecast accuracy by 15% (leading to $50M+ in incremental sales)
SOLUTION:
Created data lake for Nielsen, POS, and weather data on Hadoop platform
Built a hierarchical machine learning model for demand
Designed report in PowerBI for ad hoc analysis by managers
OUTCOME:
Improve forecast across 3x3 product/market combination use cases by 20%
Created a roadmap for integration w/ SAP APO & TPM systems
Building a recommender system @ global steel producer.
PROBLEM:
Marketshare dropped during time of general industry growth, alerting customer to potential sales problem
Can recommender system help sales drive top-line growth by bringing the right product to the right customers?
SOLUTION:
Leveraged transaction data & customer demographics to create customer & product segments
Built recommendation engine to identify actionable insights for incremental sales in 10 weeks
OUTCOME:
~1000K tons of incremental product and $100M+ sales captured for the top 10% of customers
Salesforce trained to use PowerBI dashboard & recommender system integrated w/ CRM
Designing a platform & analytics center of excellence @ global entertainment & media conglomerate.
PROBLEM:
Develop a roadmap to build a platform and a center of excellence to transform into a customer-centric enterprise
Built an integrated ecosystem with enterprise data governance, model monitoring & development
SOLUTION:
Performed data management maturity assessment & remediation
Architected a data governance warehousing & governance framework w/ master data management system
Integrated w/ AWS systems for BI and dash boarding
Designed Data as a Managed Service platform
OUTCOME:
Improve service by providing personalization to users
Establish golden view of customer & increase CLTV
Creating a servitization platform @ global tire manufacturer.
PROBLEM:
The earthmover division was rapidly losing market share to competitors from China due to commoditization
Can a service offering be developed to enhance product for mining corps where tires make up to 10% of operating cost
SOLUTION:
Suggested recommendation engine to create value-added insights from existing data for 200+ mining clients worldwide
Performed exploratory data analysis to understand tire wear as a function of 500+ variables from dozen sources
Built predictive model for failure rates relative to operating parameters in R on Hadoop w/ 7% margin of error (2σ)
OUTCOME:
Created a service division and a new business model with $50M a year in incremental sales and 20% retention boost
Building an anomaly detection system @ large US utilities operator.
PROBLEM:
Vendors and contractors have defrauded the operators of millions through complex transactional schemes
Can a system be developed to proactively identify potentially fraudulent transactions?
SOLUTION:
Leveraged unsupervised learning clustering algorithms (isolation forest) to group “similar” sets of transactions
Developed an interactive Tableau dashboard for review of “flagged” cases & daily monitoring
OUTCOME:
Robust monitoring system that flags suspicious activity and enable proactive monitoring of vendors and contractors
Increasing sales @ global talent & media agency.
PROBLEM:
Can the firm drive growth for itself and increase value to clients by uncovering authentic brand/client relationships?
Will machine learning techniques applied to 3rd party social media data be used to equip agents with innovative insights?
SOLUTION:
Collected data from dozens of curated social media sources
Used machine learning to create affinity and influence scores and construct a knowledge graph b/w talent & brands
Created an interactive dashboard w/ talent-based and brand-based rankings, trained half a dozen agents
OUTCOME:
Increase value of sponsorships for brands by increasing market penetration & for talent via leverage in negotiations
“Stole” key A-list clients from competitors by running their names through graph and creating compelling brand offers
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