4 Essential Tips for Leading a Smart Data Strategy

The CIO has an incredible opportunity to take the lead on developing a data strategy that results in the best decisions for customers and the business. Workday CIO Diana McKenzie shares lessons learned about guiding a successful data strategy.

I’ve been thinking a lot about how the role of the CIO has changed, and how digital transformation has driven much of this change by making all kinds of information more readily available. Remember when getting answers to tough questions required big analytics projects that would take a year or more to complete? Now some of those same questions can be answered within hours, or even minutes.

CIOs have an incredible opportunity to take the lead on developing a data strategy that results in the best decisions for your customers and your business. This is truly exciting stuff, because how well a company leverages data to solve problems and find new opportunities will be what separates the most successful ones from the rest.

Here are some lessons I’ve learned about guiding a successful data strategy.

Establish Credibility

Good relationships with other leaders and a strong track record of delivering on commitments for internal business partners are critical. Without great credibility, it’ll be hard for CIOs and their teams to get the cooperation required to succeed when setting off on a major data or analytics initiative. And when you gain advocates, that creates momentum and enables your team to more easily work with other business partners throughout the organization to make the most of their data.

The power of data is unleashed when you can aggregate and analyze it across multiple functions within your organization.

Focus on Cross-Functional Questions

Whenever a leadership team meets, there are typically a set of strategy questions that repeatedly come up. CIOs have the opportunity to work with their business partners to pick one or two of those questions as a place to start and begin thinking about how to use data to answer them.

But where should you start? Focus on addressing questions that impact more than one business unit, and as a result, involve more than one data set. For example, “What is our profitability by product, geography, and customer?” The power of data is unleashed when you can aggregate and analyze it across multiple functions within your organization to better inform decisions. And thanks to the technology capabilities available today, organizations are better equipped to do this than ever before.

Consult to Avoid Data Sprawl

今天是相对容易的任何业务团队to use a platform-as-a-service or infrastructure-as-a-service model to spin up an environment where they can do their own data analysis, with little IT involvement required. Yet by doing so, that team could be taking valuable data and essentially putting it in a silo where it can’t be connected to other data sources, limiting the ability to gain richer and more meaningful insights for the business. If this were to continue to happen without engagement from IT and other business teams, the result is data sprawl. At that point it becomes very difficult to identify sweet spots within the company to bring data sources together to answer the most important questions.

Only when you can truly understand the question can you make a decision on the best technology approach.

Avoid the “Killer Technology” Pitfall

In recent years, some niche analytics tools have hit the market, drawing interest from both IT and business leaders. In some instances the reaction has been, “Wow, that’s a killer technology—we need to go figure out what problem we can solve with it.” However, taking this approach without giving careful thought to the desired business outcome can prove to be a waste of time and money.

Instead, work with your business partners to first understand the key questions related to important business challenges and opportunities, and then go about determining what’s required to answer them. For example, start first with a hypothesis and then determine what data sets are needed. Next, determine if different tools are needed to assemble the data for analysis, or if the data is already available and accessible (in that case you may just need to refine business processes to improve quality and reliability). At varying points throughout this often iterative process there will be opportunities to apply a variety tools, ranging from those that elucidate correlations in the data to further refine the hypothesis, to those that improve visualization or granular drill-down and exploration via dashboards and reporting. Only when you can truly understand the question—and how the answer will impact the business—can youmake a decision on the best technology approach.

IT can’t and shouldn’t do it all, and a successful data strategy requires active participation from the entire organization. Yet there’s no question that business partners will greatly benefit from your team’s expertise, leadership, and collaboration. When it’s a cross-functional team effort, the result will produce much better outcomes for all.

Watch Workday SVP Dan Beck’sinterview with CIO Diana McKenzie.

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