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Many organizations (both commercial and federal) see the potential in capitalizing on data to unlock operational efficiencies, to create new services and experiences, and to propel innovation. Unfortunately, too many business leaders invest in one-off technical solutions—with a big price tag and mixed results—instead of investing in a strategic data science capability.
A data science capability embeds and operationalizes data science across an enterprise such that it can deliver the next level of organizational performance and return on investment. A data science capability moves an organization beyond performing pockets of analytics to an enterprise approach that uses analytical insights as part of the normal course of business.
Building a data science capability in any organization isn’t easy—there’s a lot to learn, with roadblocks and pitfalls at every turn. But it can be done—and done right. Based on our pioneering work with Federal and commercial clients, and in building our own, 500+ data science team (one of the world’s largest), Booz Allen can help you understand what’s needed, how to get started, and how to mature your data science capability.
“Building a strategic #datascience capability: what’s needed, how to get started, & how to evolve it via @BoozDataScience”
Here are some of the most common questions we hear and how we can help.
Data science dominates the popular business press as a discipline that can deliver unprecedented outcomes. As a result, organizational leaders are clamoring to put their data to good use. However, it’s important to look before you leap. Booz Allen can help you define your analytics goals and map out a step-by-step plan to get there.
Our proprietary Data Science Value Realization (DScVR) framework evaluates an organization’s existing capacity for data science across 5 key dimensions (Data Attributes, Data Governance, Analytic Assets, Talent, and Culture). DScVR consists of a short diagnostic, a tailored deep dive assessment, and results in the identification of data science capability gaps and critical data science needs. Clients walk away with a 1-2 year capability building roadmap that will put them on a solid path to generating value from their data.
Explore the 5 typical profiles of organizations pursuing enterprise analytics and see where you might fit. Learn techniques to most effectively move forward.
With demand for data science talent far outpacing supply, Booz Allen created a first-of-its-kind Data Science Talent Management Model. Starting from scratch, we used the experience of our own 500+ data science team, our experience working with government clients spanning every federal market sector, and our experience supporting Fortune 500 commercial clients to describe the core elements of data science work activities. Then, we defined those characteristics that best represent successful execution of the work, and developed a Talent Management Model that will arm clients with the insights needed to best identify, attract, grow, and retain data science talent.
Complete with a data science competency framework, Booz Allen customizes this Talent Management Model to empower our clients to succeed during the current talent shortage and beyond. Learn more about our Data Science Management Talent Model and how to recruit, retain, and nurture the right talent for your team.
The heartbeat of any data science capability is knowledge and know-how. Booz Allen has a suite of offerings to enable clients to join the “data science club” and realize value from data.
From our proprietary online training course Explore Data Science, which introduces common data science theory and techniques, to our ground-breaking Field Guide to Data Science—which spells out what data science is and why it matters and provides field-tested approaches, personal tips and tricks, and real-life case studies—Booz Allen is committed to making sure that organizations have the knowledge needed to succeed.
Booz Allen’s approach also extends beyond analytic techniques. We apply the art of design-thinking, or human-centered design, to extract the most value from data. Learn how you could apply and benefit from design-thinking to to maximize value in your organization.
There are a variety of ways to align data science within an organizational enterprise - for example, a centralized model, a diffused model, or a deployed model – each with their own advantages and challenges. Booz Allen guides clients to select the right organizational alignment and designs organizational structures for data science teams to achieve analytic goals.
Learn more about how to select and implement the right organizational model for your needs and how to stand up a Chief Data Officer.
Building a data science capability is really about using analytics to generate insights that can be used by organizations to inform strategic decisions and propel the organization to the next level of performance. Booz Allen identified the foundational building blocks that are universal to delivering on the promise of analytics. We help our clients deliberately create the conditions for data science to flourish and then empower our client’s to own an organic transformation.
Has your data science investment delivered on its promise? Learn how your culture may be contributing and what you can do about it. Also, find out how effective change management can help you build buy-in and nurture adoption for your analytics practice.
Whether you’re an IT executive, skilled analytics practitioner, or data science novice, Tips for Building a Data Science Capability contains the insights you need.