“2017 underscored just how fundamental, and fundamentally difficult, the changes needed to manage data assets/become data-driven really are,” says Thomas C. Redman, president of Data Quality Solutions. The fact that only 3% of companies’ data meet basic quality standards makes it clear just how far we have to go, he says.
What continues to be a roadblock to businesses’ good intentions, and how might they make greater progress in solidifying an enterprise Data Strategy in the new year?
“We need more of everything – more provocateurs, more switched-on managers, more boards and senior leaders who see the opportunity, better tools, more case studies, and more data people to ‘get out there,” suggests Redman, who was one of the parties behind The Leader’s Data Manifesto that debuted at Enterprise Data World 2017 Conference. “It is going to take a lot of hard work over a long time.” Despite the hurdles, Redman says there was some headway made in 2017: “I’m more optimistic than ever,” he states.
Many other data experts see reason for optimism too – and, of course, challenges yet to be overcome. Here are some leaders’ perspectives on these points, as well as advice that may prove helpful to enterprise Data Strategy endeavors in the year ahead:
Donna Burbank, Managing Director, Global Data Strategy
“It’s not a coincidence that many of the companies who are leaders in the market also have a good handle on their data, and how to best leverage it as a strategic differentiator,” says Burbank. Among the numerous companies she sees that have a Data Strategy in place are smaller- and mid-sized organizations that are as savvy as bigger businesses when it comes to seeing the value in using data more strategically.
That includes players in realms beyond traditional sectors like finance, insurance, and government: “The relative gains for them in creating a Data Strategy can be even greater and have a more significant overall impact,” she says.
Regulatory pressures such as GDPR and BCBS 239 have done their part to increase Data Strategy awareness, but more and more companies realize that data can be a strategic business driver and that managing it effectively simply is good business.” New data capabilities “are allowing organizations to enter into new markets and adapt new business models. I expect that trend to continue in the coming years.”
For companies that want a piece of that action, it’s best to use a structured framework for building out a Data Strategy, she says. That should include key components like a top-down alignment with Business Strategy and bottom-up inventory and management of data sources – see the DATAVERSITY® article Data Management vs. Data Strategy: A Framework for Business Success for more details.
Those companies that have some sort of documented Business Strategy in place should look for ways that current and future data capabilities can support this strategy, including in the conversation people from all areas of the business. If a Business Strategy is not in place, “creating one should be the priority,” she says.
“This type of ‘green field’ opportunity can be a way for data capabilities to inform the Business Strategy. For example, could better Analytics provide insights into new markets? Is there data that can be monetized for third-party consumption? The list goes on.”
Next, put in place specific plans and metrics for achieving defined goals, lest your Data Strategy simply become a theoretical exercise. “A project plan should be created defining specific tasks to specific roles and departments. Each of these tasks should have accompanying metrics that are both business and technical metrics,” she advises.
Ramon Chen, Chief Product Officer, Reltio
Most companies understand that they have to start treating their data as an asset if they’re to compete with Amazon, complete digital transformation initiatives, better personalize customer experiences and comply with regulations like GDPR, Chen says.
That’s encouraging. However, “many have not been able to approach and further implement their Data Strategy in a holistic manner,” he adds. “Aligning a very large enterprise on a unified Data Strategy is a monumental undertaking,” and many large organizations wind up spending significant resources and time on bifurcated priorities, goals, and objectives.
Companies that are seeing success and making progress are those who have mapped out a Data Strategy and vision as a long-term focus and view.
“They understand that the right technology and platform is critical to solving data and, consequently, business problems today, but it must also be capable of continuously growing and bringing together more data sources across the enterprise,” he says.
A plan on paper outlining all this is a great start, but it’s the next step that makes the difference between failure and success: “Until it’s put into action through technologies that support modern data management, it won’t become a reality.”
Hiring Chief Data Officers (CDOs) and Data Scientists and creating Data Lakes also characterize companies that understand that “data is the new oil.” But, if that’s on the roadmap for your business in 2018, be smart about how you implement these positions and technologies. For instance, while it makes sense to hire a CDO to have a single point of ownership with a dedicated focus on Data Strategy, “the success of a CDO depends on where they live in the organization [and] how their role is clearly delineated juxtaposed with the CIO,” he says.
John Ladley, President, First San Francisco Partners
“A lot of companies have strategies now, or are actively trying to put one together,” says Ladley. What many of them cannot seem to do is “get traction and execute the strategy.” While companies driven by regulatory pressures or privacy concerns have been getting traction on the road to managed data, that’s less the case for those more invested in “doing cool things with data. [They] tend to do the one-off analytics vs. a cohesive Data Strategy.” Some clients have even hired CDOs without knowing what the role is supposed to do, or defining it for the rest of leadership.
To get a Data Strategy on the right track in 2018, an organization has to make it a priority to understand what Enterprise Information Management (EIM) is, and how much work the discipline of structuring, describing, and governing information assets can be, he says.
“They need to see if they are culturally positioned to tackle it. Too many execs are saying ‘we must be data-driven’ without the slightest clue what a drastic change they are presenting to their organizations,” Ladley says.
Once implemented, a Data Strategy also has to be measured and reviewed like any other business program, considering issues like its impact on important organization KPIs. “Is employee performance reviewed? Is the performance of an LOB reviewed? Data is no different,” he says.
Jaime Knowles, Product Manager, erwin
The good news is that most organizations have recognized the need for an enterprise Data Strategy. The less cheery news is that “many continue to experience analysis paralysis or are still in the ‘lip service’ stage,” Knowles believes.
To move from these stages into actual action in the coming year, it can be helpful to follow the examples of more successful organizations. In his experiences, those are the companies that “are taking an iterative approach, starting with an 80/20 proposition, looking for areas to excel and then repeat. Prioritization is the key.”
Other steps they should consider is hiring a CDO to lead an effective organization – that is, one that understands the need to underpin a Data Strategy with a solid Data Management foundation and framework. “Executive sponsorship, organizational support/awareness, dedicated team resources, methodology, measures” come after that. Stay on top of all efforts as you go along: “Measures, KPI and the ability to iterate and reuse is key,” he says.
Ken Kring, Principal, PGTIT
Large companies typically struggle with the fact that internally they act as multiple smaller companies cobbled together, which hurts attempts to have a holistic and integrated Data Strategy. “One large company may have an immense amount of data, but often the data is segregated into several smaller pools of data,” he says. “We need to do a better job of teaching people how all of the functional silos fit together,” showing the pattern of how the data aligns as business units, products and projects flow from potential to profitability.
He’s developed a framework you can view here that partially covers integrating data as part of business flow; organizations can populate it, then codify the process and continually communicate it moving forward. “In order to define and realize the utility of a real Data Strategy, it needs to be understood by the company as a whole,” he says.
Kring has seen incremental improvements in Data Strategies as companies realize the importance of understanding how marketing, finance, and operational data, for example, all flow together. They’re driven, he says, “primarily by the realization that it is going to be too expensive, if not impossible, to continue in the future, if you don’t know how things fit together.”
He urges the education community to become invested in the teaching of integrated thinking and the Data Strategies that can result from that, too: “We need to do a better job of teaching people how all of the functional silos fit together,” he says.
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