Partnership
Designed to meet your needs, DPG offers "Embedded Expert" consulting (lower cost, utilizing primarily partner staff) and "Full Execution" consulting (rapid value realization through end-to-end DPG staffing).
Operating Model
Designed for transparency and sustainability - the DPG operating model is a systematic approach to realizing value through data product implementation. If Embedded Expert consulting is chosen, training is layered in through each step - with DPG staff taking a Player-Coach role throughout execution. While engagements are often longer, partners retain the training capital and ability to repeat this operating model across a large array of opportunities.
From Roadmap to Realization
The path to data driven value is a journey. The Data Products Group partners with you based on your strategic objectives and immediate needs. Whether it is Expert Embedded Consulting or Full Execution - we will develop a custom adaption to the above operating model that meets your needs and timely objectives!
Discover Opportunities:
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Data Products Roadmap. A comprehensive solution to identify opportunities, assess feasibility & sustainability, and estimate potential revenue returns from data monetization efforts. Note - if Embedded Consulting is chosen, DPG will train your staff to execute Data Product Roadmaps on a repeatable basis.
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Partner to Identify Data Monetization Opportunities. Captured during the Data Products Roadmap, but if Full Execution is chosen, the DPG team will work with your leadership team to go through a systematic approach to identifying data science opportunities to minimize risk, enhance the customer experience, and maximize revenue.
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Partner to Maximize Known Potential Use Cases. Captured during the Data Products Roadmap, but if Full Execution is chosen, the DPG team will partner with your leadership team to translate existing high level opportunities to defined technical opportunities.
Value & Feasibility Assessment:
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Value. Analytically assess opportunities to estimate annualized financial returns (e.g. for a client retention model, the DPG team partners with your staff to define existing attrition levels, make estimates on what percent of those attrited customers can be retained, calculates customer life time value to back into a forecasted ROI for the data product opportunity.)
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Feasibility. Based on the availability of data and infrastructure needed to realize the each opportunity, the DPG team assigns feasibility scores to each opportunity (e.g. the client retention model receives high feasibility because 12 months of historic account behavior prior to an account closure is available and is in a database accessible for analytics purposes.)
Opportunity Prioritization:
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Value First. Partner with Executive Leadership to identify rank-ordered opportunities based on forecasted value and strategic imperatives
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Sustainability Minded. Support leadership in weighting use case forecasted revenue gains with respect to internal capabilities to maintain
Analytics & Change Management Execution:
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Formalize Team. Based on engagement model, DPG either works with executive management to select and formalize roles & responsibilities of internal staff with DPG Expert(s) - "Embedded Expert Engagement", or DPG staffs engagement internally - "Full Execution Engagement."
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Agile Training. All of DPG engagements are executed using the agile methodology. We've found the agile principles produce products that address business needs more closely than traditional waterfall techniques. At the start of all execution phases, a short course is held to solidify the agile principles that will be leveraged throughout the execution phase (e.g. sprint cadence, stand-up, backlog refinement, and sprint planning ceremony times / expectations).
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Executive Steering Committee. To maximize the design of the data product - key decisions need to be made throughout the entire development life-cycle, guidance from Senior Leadership is critical to steer the product in the direction that best suites the business needs. A formal steering committee is established that the working team presents to at the end of each sprint (2 week body of planned work) to provide updates, but also get strategic guidance and answers to key questions.
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Change Management Workstream. The Data Products Group believes in a user centered design approach to developing high quality products. Starting first with the current workflow of the users (customers) and designing a future state functionality integrated with data / AI with the users (customers) informing the design throughout the entire development lifecycle. This workstream not only informs best-in-class design, but also provides a mechanism for designing training / communication strategies to best adapt users to the new product.
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Analytics (Product) Workstream. The Data Products Group develops all products to realize sustainable business value. The core product workstream is managed in an iterative fashion - with reviews by end-users and strategic guidance from the Executive Steering Committee on an scheduled (agile) cadence. Leveraging the a variety of analytics techniques from machine learning, natural language processing, to regression - the DPG develops analytics that will not only deliver long-lasting business value, but a well documented and maintainable suite of analytical tools powering the data product.
Pilot Program:
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Design Pilot. Testing can occur in a small statistically representative group of customers (users) or occur in parallel to regular business as a simulated business process. For opportunities within Risk Management, simulations are often the preferred testing structure - especially in highly regulated industries (ex. new credit risk model); while, more business oriented opportunities (ex. customer retention, marketing, etc.) are better suited for small real-world tests. Based on the opportunity, DPG works with Executive Leadership to structure the pilot that best suites the businesses needs in a transparent and track-able manner.
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Execute Pilot. Implement pilot program tracking the pre-defined metrics for the set pilot time period. At the end of the pilot period, results are compiled for review by the Executive Steering Committee, it a go forward full-launch plan.
Launch Program:
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Execute Implementation Strategy. Roll-out program based on approved strategy with continual monitoring and value tracking.
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Update Steering Committee. Revise charter of steering committee to monitoring program health, decisioning new enhancements, and setting the direction of the next Data Product.