Why Culture Is the Greatest Barrier to Data Success

To be successful with data and analytics, organizations must evolve and change the ways in which they structure current business processes.

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Building a Winning Data Strategy

Building a winning data strategy requires bold moves and new ideas. Creating a strong data foundation within the organization and putting a premium on nontechnical factors such as analytical agility and culture can help companies stay ahead. This MIT SMR Executive Guide, published as a series over three weeks, offers insights on how companies can move forward with data in an era of constant change.

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In order to compete in the new digital economy, businesses must become increasingly data-driven. Few executives would dispute this objective. Recent events, including the global outbreak of COVID-19, have underscored the critical importance of having reliable data to inform organizational decision-making. Yet companies continue to struggle to operate in a data-driven manner. Why?

Even though we are now decades into the age of competing with data, a 2020 NewVantage Partners survey of C-suite executives representing more than 70 Fortune 1000 companies found that only 37.8% of companies have created a data-driven organization. In the same survey, 45.1% of executives reported that they compete on data and analytics, but a majority — 54.9% — stated that they do not.

Meanwhile, investments in data are increasing, with 98.8% of organizations reporting that they are investing in data initiatives. Nearly a fifth of these companies — 18.3% — have invested more than $500 million. Changes are also happening when it comes to enterprisewide governance. Large corporations have increasingly embraced the newly established role of chief data officer (CDO). While only 12% of companies had appointed a CDO as of 2012, this percentage increased to a high of 67.9% by 2019 before falling back to 57.3% in 2020. Among major companies today, there is nearly universal acceptance that data-driven management is strongly preferable to the alternatives.

In spite of the growing consensus and investment levels, only half of organizations — exactly 50% — reported that they are managing data as a business asset. The advent of big-data solutions and a next generation of data management capabilities — Hadoop, data lakes, DataOps, and modern data architectures — have been helpful but have not assured successful business adoption or outcomes. Technology does not appear to be a barrier or the problem. Only 9.1% of executives pointed to technology as the principal challenge to becoming data-driven.

Albert Einstein is said to have remarked, “The world cannot be changed without changing our thinking.” What is clear is that the greatest barrier to data success today is business culture, not lagging technology. In fact, cultural factors — that is, people and process issues — were cited by 90% of executives as the principal obstacle that they face. It is not enough for companies to embrace modern data architectures, agile methodologies, and integrated business-data teams, or to establish centers of excellence to accelerate data initiatives, when only about 1 in 4 executives reported that their organization has successfully forged a data culture.

Forging a data culture is a relentless pursuit, and magic bullets and bromides do not deliver results.

Cultural change and business transformation must be adopted at all levels of an organization for data-driven management to be truly embraced. Having professionally engaged with scores of large organizations over the course of the past two decades, each at a varying stage of maturity, I have found that certain actions distinguish successful data-driven companies from those that continue to struggle.

1. Secure executive commitment, not just lip service. Executive commitment is essential to building a culture where data is central. Pay attention to what companies do, not what they say. Most pay lip service to the criticality of data in their annual reports and company mission statements, but far fewer companies embody it in their DNA or in their day-to-day business practices. Some companies, like Capital One and American Express, have a history of embedding data in all aspects of their business culture. For most legacy companies, however, building a data culture remains a challenge. Companies that have overcome it instantiate data processes throughout their supply chains, from data production to data consumption. I have met with organizations that have proclaimed their commitment to creating a culture where data is a priority without making the necessary investments and following through on their proclamations in order to drive real change and data-driven business outcomes. Don’t be one of them.

2. Expect to work hard, and forget about magic bullets. Companies that have succeeded in their data-driven efforts understand that forging a data culture is a relentless pursuit, and magic bullets and bromides do not deliver results. To borrow from Thomas Edison, becoming data-driven is 1% inspiration and 99% perspiration. I have seen too many companies undertake big-bang, overly ambitious initiatives that fail over time. Start simple. Focus on key business questions. Tie data investments to business outcomes. Realizing quick wins enables organizations to build credibility and establish sustainable momentum. Companies such as Cigna, Nuveen, and Citizens Bank are embarking on long-term efforts to define use cases with strong business sponsorship. Companies that accept that there is no easy path to success fare best over time.

3. Establish realistic expectations, not unattainable goals. Only 28% of companies reported that the CDO role has been successfully established within their organization. Why is this? One reason is that many organizations have struggled to establish realistic and achievable objectives for the CDO. Data is an asset that flows across an organization, and managing data is therefore complex. CDOs must establish achievable expectations to ensure success. I was once asked by a business line president for a plan to make his organization data-driven within 90 days. Until organizations develop attainable goals, it will be impossible to achieve successful data outcomes.

4. Make steady progress, and overcome false starts. For many organizations, impatience to see results in the short term often leads to false starts, whether it is the investment in and then abandonment of technology initiatives or the launch of and lack of follow-through in data programs across the organization. The CDO’s short tenure for many companies reflects both the nascence of the role and a lack of clear expectations. Some of the largest banks are on the fourth or fifth iteration of their CDO role within the past decade. For many organizations, the tenure of the CDO is averaging less than three years. Companies must reach a point of stability and consistency in leadership and approach to maximize the return on their data investments.

5. Learn from the experience of others. Organizing around data is a new principle for most companies, many of which have continued to evolve from a product-centric view to a customer-centric view in recent decades. Many organizations tell me that they have their data and cultural challenges all figured out, but in practice, those that think they have it all worked out rarely do. They would benefit from understanding what other companies have done so that they can avoid the same pitfalls and replicate formulas for success. I have seen organizations seesaw in hiring external CDOs as change agents and revert back to longtime company insiders who know the culture of the company. Staying the course is important. Keep an open mind, learn from the experiences of others — their failures and successes — and look beyond your four walls for inspiration and success models.

6. Maintain a long-term view, and expect a journey. It should be clear by now that achieving data success is a journey, not a sprint. Companies desire to accelerate their efforts to become data-driven, but consistency, patience, and steadfastness pay off in the long run. Companies that set a clear course, with reasonable expectations and phased results over a period of time, get to the destination faster. Develop a plan. Create a data strategy for your company if you do not already have one. If you do have a data strategy, make sure that it is updated annually to reflect changes in the business and the ongoing and rapid evolution of emerging data management capabilities. Define your future state, and build an execution road map that will take you from your current state to the target outcome. It is hard to reach any destination without a good road map. Companies need to maintain a long-term view and stick to it while making periodic adjustments. Patience, persistence, and commitment are the ingredients for ensuring a successful long-term outcome.

Change Means Finding New Ways of Doing Things

Organizations must evolve and change the ways in which they structure current business processes if they expect to become more data-driven. In short, companies must be prepared to think differently. In 1997, Apple launched its legendary “Think Different” advertising campaign, noting that it’s often “the misfits, the rebels, the troublemakers, the round pegs in the square holes” who “see things differently … change things … change the world.” Those companies that recognize that competing with data and analytics requires them to do business a little differently and embrace change will likely be well positioned to realize the benefits of a data-driven culture.

Topics

Building a Winning Data Strategy

Building a winning data strategy requires bold moves and new ideas. Creating a strong data foundation within the organization and putting a premium on nontechnical factors such as analytical agility and culture can help companies stay ahead. This MIT SMR Executive Guide, published as a series over three weeks, offers insights on how companies can move forward with data in an era of constant change.

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