A ‘Data-First’ Strategy Is Great – But Are Businesses Ready For It?

Enterprise Tech A ‘Data-First’ Strategy Is Great – But Are Businesses Ready For It? Joe McKendrick Contributor Opinions expressed by Forbes Contributors are their own. I track how technology innovations move markets and careers New! Follow this author to improve your content experience. Got it! Jul 27, 2022, 07:00am EDT | Share to Facebook Share to Twitter Share to Linkedin Data unlocks new insights.

getty “In God we trust, all others must bring data. ” How many times have you heard this quote, attributed to the late great scientific management guru W. Edwards Deming? He may have said it many decades ago, but the others are still not bringing in the data.

Plus, it’s not simply a matter of bringing in the data if the corporate culture isn’t ready to operate in a data-driven way. A recent survey finds 57% of financial firms still are not as far along as they would like to be when it comes to digital transformation, because they are not handling the data in the most judicious way. The survey, by Broadridge Financial Solutions , finds 94% have problems with their data, complicated by legacy or outdated technology stands out as the biggest hurdle that firms face (27%), followed by poor data quality (23%).

This is a challenge that surfaces in countless industry studies. The challenge goes well beyond data management — getting to a data-driven culture requires both executive and employee acceptance of data analytics. It shouldn’t be an issue getting colleagues to acknowledge that a data-first strategy and culture will deliver results, but it is.

Many of the 7,295 executives in a survey from across all industries cited data-driven insights as being essential for improving the customer experience (50%), locating data infrastructure (37%), developing new digital products (35%), and driving business growth (28%). Authors of the study , published by Digital Realty, advocate a “data-first strategy” for succeeding in the digital 2020s. This includes improving data infrastructure (72%), upskilling data capabilities (65%), and investing in artificial intelligence/machine learning technologies (59%).

Hiring more data scientists was also mentioned by about a third. At the same time, challenges cited include lack of sufficient investment in data systems/infrastructure (53%), lack of sufficient investment in relevant analytics tools (50%), and data privacy regulations (35%). MORE FOR YOU The 5 Biggest Technology Trends In 2022 ‘Enthusiastic Entrepreneurs’: Pre-IPO Statements On Profitability Prove To Be Larger Than Real Life The 7 Biggest Artificial Intelligence (AI) Trends In 2022 What does it take to build and sustain a data-first culture, so it isn’t just another flashy buzzphrase? We turn to Thomas Davenport , the most compelling voice in data analytics revolution, who explained the essence of a data-first culture in a Harvard Business Review webinar .

Davenport, an author affiliated with MIT and Babson College, describes seeing slow uptake of data-driven approaches in surveys he has conducted in recent years. “It’s been frustrating to me over the years that more chief financial officers have not adopted analytics to understand the drivers of their financial and operational performance,” he says. Once in place, though, a data-first approach can be like “having a heat-seeking missile approach to data analytics and AI,” he adds.

Here is Davenport’s word on what constitutes a well-functioning data-first culture: Understands the power of data and analytics, and how they can be effectively used in business. “We have lots and lots of evidence now that data and analytics decisions are on the whole better than decisions made by gut feel and intuition, less subject to bias,” Davenport explains, adding that “the bias in AI decisions is far more easier to address than the bias in humans. ” Closely monitors performance drivers with analytics.

A data-first culture emphasizes the need to “constantly find new ways to measure what’s happening in the organization,” he says. Knows and accepts the limits of data and analytics. “If you find company that is highly analytical, with the CEO is promoting it, they are comfortable with the idea that their organizations are very data oriented.

” But leading technology companies also understand there is a place for non-data-based decision-making, such as storytelling. “Some of the most important decisions may not involve data, so it’s important to know if you don’t have data, you still have to make a decision. ” At the same time, even the most data-driven enterprises can shift into reverse, depending on who is leading the effort.

“Gut-level decision making can creep very quickly back into the organization,” Davenport cautions. Continually educates executives and employees on the advantages of data-first strategies. “Mucking around with executive decision-making processes is not a terribly popular idea,” Davenport admits.

“Push too hard on the idea that you’re going to make our decisions on the basis of data, you will encounter resistance. Good leaders are those rely on data rather than just their own experience and intuition and encourages the rest of the organization as well. We don’t know how many are out there.

Leaders may be secretly worried about learning this stuff. You need to try to work on a day-to-day behaviors, you need to try to persuade executives within your organizations how this might work. ” Puts someone in charge, while making it everyone’s responsibility.

“More and more organizations have chief data officers — many are technological in scope, some initially were data security oriented,” Davenport observes. “You need a strong partner on the business side, preferably the CEO. Eventually, you’d like to have everybody involved in it, as a pervasive data culture.

” Exercises humility. “One of the great things about a data orientation is you can say ‘I really don’t know what the answer is until we see some data. ’” Davenport points out.

“Nobody has a golden gut, we have to rely on data. If you believe in data, then you also believe in circumstances where you were wrong, and executives need to able to admit when they were wrong, and to learn from it in a data-driven cultures. ” Follow me on Twitter .

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