SERVICE
LINES /
PROJECTS
RETAIL
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above to review these service lines in more detail.
RETAIL / OTHER
SEGMENTATION
PRODUCT LINE REDESIGN
PREDICTIVE ANALYTICS
INNOVATION
VIDEO
CENTER
CONSULTING
PLATFORMS
SOFTWARE
SOLUTIONS BY INDUSTRY
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SERVICE LINE: SEGMENTATION
EXAMPLE CLIENT #1:
EXAMPLE CLIENT #2:
One of the top two U.S. beverage firms.
McDonald's
1993-Present
SUMMARY
OBJECTIVES
RESULTS
DSE TECHNOLOGIES USED
DIFFERENTIATION
On the heels of our segmentation success in the Financial Services industry* we brought the same technology of VALUE-BASED segmentation to the retail industry. For objectives, results, technologies and differentiation roll over the tabs above.
* = DSS partnered with Accenture in the National Retail Banking Buyer Value Study. The NRBBVS still the largest advanced segmentation study ever deployed in the banking industry.
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SERVICE LINE: PRODUCT REDESIGN
SERVICE LINE NAME:
EXAMPLE CLIENTS:
REBOOT: Retail Product Line Re-Design
1995-Present
One of the World's Largest Department Stores, Others
SUMMARY
OBJECTIVES
RESULTS
DSE TECHNOLOGIES USED
DIFFERENTIATION
REBOOT is based on a simple idea. If you build what consumers really want...they will come!
After performing more advanced, multi-business line buyer value-based research projects for top 20 U.S. banks than any other strategy firm worldwide, we adapted the tools and technologies from that business line into the retail vertical. Roll-over the tabs above to see what we found!
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SERVICE LINE: PREDICTIVE ANALYTICS
EXAMPLE PROJECT:
Ultra-High Performance Data Mining (UHP-DM)
1995-Present
CLIENTS:
Leading US Retail and Financial Service Firms
SUMMARY
OBJECTIVES
RESULTS
DSE TECHNOLOGIES USED
DIFFERENTIATION
The average data mining analyst builds about a dozen predictive models per week. What if data mining could be automated to produce millions of models per week? The UHP-DM framework is a fundamental rethinking of how to transform data mining from the ground up. UHP-DM sees data mining as a solution space of potential models with six primary dimensions: data transforms, model form, algorithms, sub-algorithms, iterations, and criteria. By building a data mining assembly line that penetrates this solution space, we can zero in on high performance volumes within the solution space. For the technologies that achieve this, see the DSE TECH section above.
UHP-DM is software development project fifteen years in the making. It has yielded two linked applications; VISTAR and BigDataSolve.
The Differentiation of our UHP-DM (Ultra-High Performance Data Mining) practice is industry-leading. In two simple ways. It is:
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SERVICE LINE: INNOVATION
SERVICE LINE:
EXAMPLE CLIENT:
Retail Product Innovation
1996-Present
One of the Two Largest Beverage Firms Worldwide, Others
SUMMARY
OBJECTIVES
RESULTS
DSE TECHNOLOGIES USED
DIFFERENTIATION
Innovation is all the rage. And for good reason. Only so much growth can come from M&A...and only so much margin can be obtained through better management practices. Fundamentally, business recognize that mature markets require active and continuous innovation to achieve sustained competitive advantage. But how does one come up with that elusive new category or that elusive new idea?
DSS's insight? Innovation is fundamentally defined as building new services in LATENT areas of demand. Said mathematically innovation discovers unmet volumes of demand in a multivariate need space. Our ideas in innovation were, well, so innovative that they earned us a main stage presentation at the prestigious annual ART (Advanced Research Techniques) forum. Click on the tabs above to learn how our Innovation Practice used our DSE platform InnovationSolve to enable one of the word's largest retail companies to find and fill undiscovered niches of demand.
In contrast to all other Innovation approaches, DSS's Innovation practice:
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