How To Successfully Align Data and Business Strategies

There’s been a great mental shift around data over the past few years. Most organizations have gone from viewing data as a defensive or reflective tool to realizing that it is the ingredient that will help them grow into a market leader.

That’s a big leap, and one that requires some expectation management. Yes, data can be a tremendous growth driver, but executives need to remember that, at its most basic level, data is raw material. It’s not something that should be used to do things to a business. Instead, it’s most useful as something that does things for a business. 

For example, data is a vital component of the technologies powering the future, including artificial intelligence (AI) and automation. Both reduce the burden of manual processes, allowing employees at all levels to focus on higher-value tasks. If organizations fail to keep up, they may go out of business. Data also empowers enterprises to answer their every question, including questions they didn’t know they had.

The best way to outpace competition is to be clear on the changes you want to make and the role of data in those changes. Approaching data this way can be an amazing asset to every organization. Ultimately, it’s really about ensuring your company’s data strategy and business strategy are aligned, and that you have the right mix of tools and culture to leverage data effectively at scale. 

Three pillars for a successful data strategy

Building a successful data strategy starts with thinking about use cases. Real-world use cases provide the framework that supports making the right investments. And by relating “the art of the possible” to real-world pain points, you more easily get internal teams excited about joining in a future informed by data.

Next, you’ll need to clearly map out the effort surrounding the changes you’ll implement. Data-driven growth is, in some ways, like a quest to get into shape. It’s possible, but to get to where you want to be, you’re going to want a clear plan. If the journey isn’t worth it for your people, you’ve picked the wrong use case.

For me, there are three core pillars that help create an environment for success when becoming more data-driven: 

Analytics – Data teams need to improve how they handle things like descriptive analytics and predictive analytics to determine how to deliver an impact at a specific point in time.  

Data governance – Be sure the data that is used can be trusted and is reliable. Is the business ready when it is time to use its analytics?

Technology – This isn’t the place to start, but you’ll likely need to deploy or enhance technical capabilities to ensure users have what they need to leverage data effectively. 

These three pillars provide the essential focus that generates buy-in, adoption and relevant impact to the business.

More data, more considerations

With the pillars established, you’re at the ‘end of the beginning’ on the road to data-fueled success. As your data’s value becomes more widely accepted internally, and you increasingly adopt things like AI-fueled analytics, many executives may come to believe it’s easy to predict an accurate outcome to any challenge. Unfortunately, it’s never that simple. Yes, it’s generally easy to create a model for any scenario, but do you have the right data (type and quality) and analysis chops across the business to leverage it effectively? That’s the trickiest part and where many analytics and AI efforts fall down. 

There are also ethical considerations to keep in mind. AI algorithms are only as good as the data they feed. It’s critical to impose human aspects on data once it’s gathered. If we don’t, we’ll have credit cards that discriminate on the basis of gender and unchecked bias in mortgage-approval algorithms. Even medical procedures could be delayed if algorithms are left to their own devices. 

Human intervention is a necessary failsafe to ensure the technology isn’t misused or causes unintended consequences. They have a real impact on real individuals, so people must be involved every step of the way. This reinforces the need for a data literate workforce; along with technology and process changes, make sure you’re baking in data skills training for all levels of the organization.

Your decisions should be as powerful as your data 

It's become crystal clear that data is essential to the future success of any business. Enterprises must pivot their focus from gathering data to defining how it can clearly impact their most crucial business challenges, and then execute a plan to infuse data into every process that matters. Analytics, data governance and technology are critical components to instilling any firm with the ability to become more data-driven.

While modernizing their approach to data, businesses must also remember to focus on data quality and data skills training. Whether using the information to make manual decisions or deploying an algorithm to handle the task automatically, no one — not even a machine — can be expected to make smart decisions with bad data. In order to become a data-driven enterprise, businesses need to ensure that both their data and their people are as powerful as the decisions they are about to make.