From Data Laggard to Data Leader: Four Ways Chief Data Officers Can Transform an Organization

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By 2025 there will be a nearly unbridgeable divide between data laggards and data leaders. Data leaders will harness data as a powerful new asset to transform their organizations and separate themselves from the competition, while data laggards will find it harder to get market traction. Although executives are currently focused on digital transformation, chief data officers (CDOs) know that “digital” without “data” is senseless.

CDOs play a critical role in transforming their organizations, whether business executives recognize it or not. CDOs need to accelerate their organizations’ evolution through the stages of intelligence and develop world-class people, processes, programs, and platforms (P4) to deliver value (V) with data (D). But this is a tall order; it’s hard to know where to start. This article provides a simple framework to help CDOs identify their key points of leverage to help their organizations cross the data divide before it’s too late.

Mastering the Eras of Intelligence

Data leaders long ago mastered business intelligence—the delivery of integrated, governed data via reports and dashboards. More recently, they’ve navigated self-service intelligence, balancing empowerment with governance to deliver insights on demand throughout the organization. Today, data leaders are embracing artificial intelligence—the creation of analytic models that augment, automate, and optimize business processes. (See figure 1.)

Figure 1. Three Eras of Intelligence

As data leaders keep marching along the data continuum, building on past successes, data laggards struggle to get out of the starting gate. Many clients we work with still haven’t implemented a properly designed data warehouse, harmonized master data, or standardized key enterprise metrics. Business intelligence forms the foundation of self-service intelligence and artificial intelligence, so it pays to get it right because each step gets harder.

The Data Divide

As data leaders master the second and third eras of intelligence, the divide between data laggards and data leaders grows bigger. The divide will determine winners and losers in the marketplace during the next decade. Already, digital and data natives, such as Amazon and Google, have disrupted entire industries, collectively achieving trillions in market capitalization. Non-digital natives need to run fast to stay apace. (See figure 2.)

Figure 2. The Data Divide

Data Laggards. A data laggard is flush with spreadsheets and data silos. Users can’t find data or reports and don’t trust them when they do. Data fiefdoms abound and no one shares data. Analysts continually reinvent the wheel and spend more time fixing data than analyzing it. IT is a bottleneck for getting things done, and both IT and business react to events, spending most of their time putting out fires. Finally, not surprisingly, executives view data and analytics as a cost center or tactical endeavor.

Data Leaders. Data leaders are the complete opposite of data laggards. Their businesses run on insights and models, not spreadsheets and data silos. Data is integrated, governed, cataloged, curated, and shared. Data is easy to find, trustworthy, and standardized. Remarkably, business managers and users take an active role in governing the data, and data analysts and data scientists spend most of their time analyzing data and creating and refining models. Both IT and the business are agile, working proactively to identify opportunities and address problems. Here, IT facilitates self-service analytics and model-driven exploration, while executives view data as a key enabler of revenues and profits.

Community-Centric Framework for Success

Most CDOs have many areas of responsibility, so it’s hard to focus long enough to make progress in any one area. One way that CDOs might approach their work is not by task, but by community. A CDO is a leader who serves others. Having a clear understanding of those communities can help prioritize tasks and responsibilities.

Four Communities. CDOs serves four primary communities: executives, business unit heads, knowledge workers, and their own teams. Each community has trigger points, which when activated, can become agents of change that advance an organization’s data intelligence. A savvy CDO knows exactly where to apply pressure (and time) to effect the largest amount of change. (See figure 4).

Figure 4. CDO Communities - Agents of Change

Executives. How should CDOs manage business executives to help the organization cross the data divide? Here are three things CDOs can do:

1. CEO Fiat. By far and away, the most effective change agent is an enlightened CEO who issues a fiat that requires standardized metrics and harmonized data at the enterprise level. CDOs need to be “CEO whisperers” who help them recognize the importance of issuing such a game-changing fiat and what it entails.

2. Executive Dashboard. It’s one thing to say “We’re data-informed” or “We value data” and it’s another thing to do it. Executives need a standard dashboard and scorecard that they use at operational and strategy review meetings, respectively. This has a “trickle-down” effect that causes downstream managers to embrace data.

3. Analytical Recruits. CDOs need to help recruit analytically-minded executives. One data-driven executive can help spawn a program; multiple data-driven executives can change an organization.

Business Units. CDOs will probably spend a plurality of their time working with business unit heads to foster greater alignment and governance. Here are four key CDO initiatives:

1. Establish an Analytics Council. This cross-functional board of analytics directors serves as the data program’s board of directors, who review and approve the strategy, funding, and various initiatives.  

2. Center of Excellence (CoE). A CoE represents how the corporate data team interfaces with data and analytics resources in the business units. An Analytics Council is a key part of a federated center of excellence.

3. Data Governance. The CDO needs to spearhead and facilitate the process for defining, documenting, and maintaining data standards, policies, and procedures.

4. Report Governance. The CDO also needs to make sure that enterprise reports adhere to standard data definitions. Report governance is often a key initiative of an Analytics Council, along with project prioritization, and training.

Knowledge Workers. A CDO is ultimately responsible to the people who use data and analytics to run the company. A CDO needs to create:

1. Self-Service Platform. A CDO needs to provide the data and analytics platform that empowers business users, data analysts, and data scientists to do their jobs with minimal assistance from others and without creating data chaos.

2. Community of Practice. Power users (data analysts and data scientists) need ample amounts of peer-to-peer collaboration, both to exchange knowledge, tips, and tricks and reuse each other’s work to avoid reinventing the wheel.  

3. Data Literacy Program. Business users need to understand core statistical concepts and learn how to leverage data and analytics tools in the context of their business processes.

Data Team. A CDO may be in charge of many teams: data architecture, data engineering, business intelligence development, business analysts, data science, data analysts, data innovation, data monetization, and possibly data security. Here, a CDO should concentrate on three things:

1. Quick Wins. Nothing else matters if the business doesn’t trust the data team to deliver strategic solutions in a timely manner at an affordable price. The CDO needs to turn the data team into a strategic business partner by delivering quick wins that get attention.

2. DataOps. With proven successes, CDOs can then turn their attention inward to identify and eradicate bottlenecks and eliminate the source of data defects. The CDO needs to continually emphasize the mantra: “faster, better, cheaper.”

3. Data Architecture. Once CDOs establish a continuous improvement process (DataOps), they can focus on creating a modern, harmonized architecture that supports the three eras of intelligence.

To cross the data divide by 2025, CDOs need to accelerate their organizations’ evolution through the stages of intelligence and develop world-class people, processes, programs, and platforms that deliver value with data. The best place to start is to identify the critical success factors required to support four CDO constituencies: executives, business unit leads, knowledge workers, and the data team.

Wayne Eckerson

Wayne Eckerson is an internationally recognized thought leader in the business intelligence and analytics field. He is a sought-after consultant and noted speaker who thinks critically, writes clearly and presents...

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