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How To Create a Successful Data Strategy

By the MIT CISR Data Board

As large, established organizations transform to compete in the digital economy, they must rethink longstanding approaches to data. Inside the firm, digital business strategies require adjustments to data technology, processes, and mindsets. Outside the firm, changing regulations, evolving innovations, and shifting consumer perceptions and expectations make data “dos and don’ts” much less clear.

Amidst this change and uncertainty, at MIT CISR we believe organizations must establish a data strategy to clarify and communicate their desired next-gen data approaches. In Q1 2018, members of the MIT CISR Data Board—a research forum composed of data executives[1] and MIT CISR research scientists—discussed what exactly creating and implementing an effective data strategy involves. The following article defines data strategy, describes the MIT CISR Data Board and its recent data strategy collaboration, and shares four important principles that emerged from our Q1 board discussion.

Data Strategy

The MIT CISR Data Board defines a data strategy as a central, integrated concept that articulates how data will enable and inspire business strategy.[2] In general, a data strategy answers five questions:

  1. What is the organization’s vision for data? A data strategy lays out how data will enable specific business goals.
  2. How will the organization move forward on its data journey? A data strategy clarifies how the organization will execute desired data activities.
  3. How will the organization drive data adoption and use? A data strategy describes how the organization needs to change to maximize value from the desired data activities. It should include change management components (e.g., education, incentives, measurement, communication plans) that will inspire change at the individual, group, and organizational levels.
  4. When will the organization execute the proposed activities? A data strategy lists the sequence of steps that the organization will follow to move forward; it contains a roadmap with milestones and priorities.
  5. What is the organization’s economic logic? A data strategy explicitly describes how the company will monetize its data using some combination of improving, wrapping, and selling activities.[3]
The MIT CISR Data Board—and Members’ Data Strategies

The MIT CISR Data Board was established in 2015 to inform and influence data-specific research conducted at MIT CISR and in the broader academic community. In Q1 2018, the board included 89 data executives from 70 organizations around the world, representing 12 industries. At that time, the executives collaborated with MIT CISR researchers to produce a better understanding of contemporary challenges and opportunities associated with data strategy.

During Q1 2018, 52 of the organizations with participation on the board responded to a set of discussion questions on the maturity of their data strategies. The following breakdown describes data strategies in place at these organizations.

WHEN: Data strategies were new. On average, the existing iteration of an organization’s data strategy had been in place for 1.6 years.
WHERE: About half of the organizations’ data strategies were then owned either by IT (18%) or a formal data unit (34%). The remaining strategies fell under a diverse set of owners (see figure 1), such as an analytics group or digital team.
Figure 1: Data Strategy Owners
Data strategy owners in MIT CISR Data Board companies.
Source: MIT CISR Data Board responses to discussion questions on data strategy maturity in Q1 2018 Yammer forum conversations. Not all participants answered each question; N=50 responded to this question.
WHAT: For the most part, the organizations were creating data strategies that were much different from ones they had created in the past. Although about one-third of the organizations had possessed data strategies for years (with the existing iteration being evolutionary), two-thirds of the organizations possessed data strategies that were either dramatically refreshed or brand new (the organization had never had a data strategy before).
WHY: The organizations’ strategies were established to shift mindset, reengineer work practices, and advance architecture. As a result, the strategies proposed ways to attack hard problems such as breaking down data silos (e.g., to enable a 360-degree view of customers), defining the meaning of data as an asset, and prioritizing data investments (targeting needed improvements in data tech and data talent).
Data Maturity Matters

A host of data maturity models propose that organizations mature in data over time across a host of dimensions such as architecture, governance, funding, organizational impact, users, roles and skills, and applications. Therefore, most organizations become great at managing and using data after years of practice.

As organizations mature, their focus moves from establishing data foundations, to learning how to best extract insight from the foundations, to formulating from these insights meaningful and effective actions that create value in new and exciting ways. The data strategy, therefore, needs to evolve to reflect the organization’s current state of maturity.

In Q1 2018, fifteen CISR data board member organizations were just beginning their data journeys. These organizations were introducing data strategies focused on building an enterprise data vision, as well as investing in data foundations such as a central data lake and master data management. Thirty organizations had established data foundations previously—and were now developing strategies to exploit the foundations. These strategies proposed ways to extend data use—such as by talent development, self-service, and data services—and to change the nature of data use, such as by shifting from traditional business intelligence to analytics that enable improvements in customer experience. The seven most mature board organizations were developing data strategies to identify how data might enable new business models. These organizations were entering ecosystems, and driving revenue streams from information-based solutions.

Data Strategy Principles

As the board shared characteristics of participants’ data strategies, four important themes emerged. We believe the themes can serve as principles for other data leaders to consider as they move ahead with their own data strategies.

Principle #1: The journey is as important as the destination.

The act of crafting a data strategy is a chance to prompt data conversations, educate executives, and identify exciting new data-enabled opportunities for the organization. In fact, the process of creating a data strategy may generate political support, changes in mindset, and new business directions and priorities that are even more valuable than the data strategy artifact itself.

Principle #2: One size may not fit all.

Data leaders may need to adapt a data strategy for application across an organization that is large or decentralized. In big organizations, maturity can vary across business units; and in decentralized organizations, different business units may have distinct business needs. In these cases, data leaders may have to advance units at their needed pace via different methods.

Principle #3: Be prepared to change the tires while the car is moving.

A data strategy should actively help the organization use data activities to bring a business strategy to life. This is not easy, however, because an organization’s business strategy constantly changes. Organizations must proactively establish ways to maintain alignment of data and business strategies (see figure 2) to keep the data strategy relevant over time.

Figure 2: Ways to Maintain Alignment
How alignment has been achieved in MIT CISR Data Board companies.
Source: MIT CISR Data Board responses to discussion questions on data strategy maturity in Q1 2018 Yammer forum conversations. Not all participants answered each question; N=51 responded to this question.
Principle #4: Show me the money.

The most compelling data strategies articulate exactly how data will generate economic value—specifically and uniquely—for an organization. Thus, a data strategy should spell out the not just how data enables business strategy, but also how the enablement drives risks, costs, and benefits for the organization to result in net financial gain (or mission realization).

[1] The data executives on the MIT CISR Data Board are members of MIT CISR sponsor and patron organizations, which may nominate two representatives to participate on the board each year. Participants engage primarily via a forum on an enterprise social network—Yammer—responding to quarterly discussion prompts. After responses are analyzed, insights are presented to participants in webinar format and included in MIT CISR’s data research output.
[2] The MIT CISR Data Board formulated the data strategy definition and five questions based on Donald C. Hambrick and James W. Frederickson, “Are You Sure You Have a Strategy?” The Academy of Management Executive 19, no.4 (November 2001): 48–59.
[3] See Barbara H. Wixom and Jeanne W. Ross, “How to Monetize Your Data,” MIT Sloan Management Review, January 9, 2017,