3 Steps Business Leaders Should Take to Build Data-Driven Organizations

It’s 2020, and “big data” is no longer a new buzzword. Business leaders in almost every industry talk about being data-driven and use phrases like “backed by data.” Although a survey by McKinsey suggests that most companies say advances in analytics are dramatically changing the modern business environment, not many companies are capitalizing on the data they collect and store.

For the firms that are capitalizing on the opportunities that data provides, the results have been transformative: According to that same McKinsey study, high-performing organizations — firms that are growing quickly in terms of revenue and earnings before interest and taxes — attribute at least 20% of that annual growth to advances in their data and analytics capabilities.

So what separates the leaders from the laggards? High-performing organizations make data and analytics a pillar of their long-term business strategies. If you want to join them, you’ll need to create an operational culture that’s genuinely anchored by data. Here are three ways to get started:

1. Get executives on board with analytics goals.
   Lasting organizational change must start at the top. Before demanding that employees adopt a data-driven mindset, you must ensure that your leadership team believes in the value of data. Show exactly where and how data and analytics fit into your core business strategy, and set clear expectations for the executives who will be driving the effort.In 2018, TD Bank Group division TD Wealth determined it was ready to harness the power of its data. The firm implemented the WealthACT program for executives to embrace AI, data, and related technologies. Today, about half of TD Wealth’s senior management team has graduated from the program, which involves immersive workshops and meetings with experts all over the world. Its leadership team now understands how data is changing wealth management and banking, and the company is prepared to lead that change.
2. Train all employees on data concepts.
   Most of your employees are probably unfamiliar with the techniques and technologies that turn data into actionable insight. That’s to be expected: Data analytics is a relatively new discipline that takes time to master. If you want to create a data-driven operational culture, however, you’ll need to make sure your employees understand the way your company uses data as well as why it’s so valuable.
   Once your leadership team has bought in, begin to implement training programs that educate employees at all levels. Regular workshops focused on improving data literacy and data storytelling — or analytics clubs led by internal experts — can be extremely valuable, especially early in your company’s transformation. Encouraging knowledge sharing and skill development will not only equip employees with the tools they need to work in a data-driven environment, but it will also boost employee engagement.
3. Get input from end users.
   AI is the technology that turns data into insight. According to a Harvard Business Review article, AI is most effective when cross-functional teams are part of the development process. When purchasing AI tools or developing proprietary algorithms in-house, be sure to consult the people who will be using the new technology. Getting input from team members who have a variety of backgrounds, skills, and perspectives will ensure the tools you build or acquire meet your needs and seamlessly fit into user workflows.
   According to research from ThroughPut Inc., an industrial operations AI company, using AI for data-driven operations can boost productivity by 30% and output by up to 200%. These results are only possible if end users are able to operate the tools you’re giving them.”.

High-performing organizations are already taking the above steps to harness the power of their data and widen the gap between themselves and competitors. If you’re not yet making the most of your data, it’s not too late to get started. Implement these measures and be patient as your organization gradually transforms — the results will be worth the wait.

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