Data-driven organizations: to be or to become, that is the question*
Bruna Ferreira, December 16, 2022
Did you know that data-driven organizations are 6 times more likely to keep their current customers, 23 times more likely to get new customers, and 19 times more likely to make a profit, reveals a McKinsey study? This is because when organizational processes are based on data and information analysis – from strategic planning to decision-making – the culture of “guessing” and intuition gives way to a data-driven culture based on facts and evidence that collects, measures, and cross-references data to generate a clear picture of the organization’s past, present, and future.
According to the Analytic Maturity Index used by the Cappra Institute for Data Science, organizations go through several stages of evolution concerning the use of data: data-negation, data-curious, data-try, data-safety, and finally, data-driven. Carl Anderson, Director of Data Science at Indigo and author of the book “Creating a Data-Driven Organization: Practical Advice from the Trenches”, believes that to reach this last level, organizations must guarantee three requirements: tools, skills, and culture.
There is an episode reported in the Harvard Business Review by Jeff Lawson, CEO of Twilio Inc., which recalls a mythical meeting at Amazon in which Jeff Bezos explained to his team that Amazon was not a retail company, it was a technology company: “Our business is not what’s in the brown boxes. It’s the software that sends the brown boxes on their way,” he said.
Today, 15 years after that sentence was uttered, it becomes even more apparent that whoever has the best software has the highest levels of capacity, agility, competitiveness, and innovation in the Digital Economy. It is through technology that today startups and centennial multinationals compete in the same ring, seeking a first place in the preference of their clients. How? Through an automated and coordinated workflow, a continuously organized knowledge repository, compliance with current legislation, and access to intelligent reports and dashboards whose indicators allow them to anticipate client needs and make faster, more assertive decisions with less risk and cost involved. Why? Namely because they are based on data whose predictive, descriptive, prescriptive, and diagnostic analysis contributes to the organizational strategy.
A data-driven organization can extract intelligent insights from data. Therefore, to move from data (representation of one or several quantitative or qualitative attributes) to information (data processed and explained for a purpose) requires professionals with specific competencies. These professionals have programming or cybersecurity and data analysis, measurement, and interpretation expertise. They may adopt a wide range of designations, such as Chief Data Officer, Intelligence Officer, or Data Scientist. Regardless of their job title, they are qualified to operate in business intelligence and analytics.
Business Intelligence refers to a set of techniques and solutions that define how the organization collects, measures, and analyzes data. It is a reactive area, producing easy-to-understand reports about the organization’s past and present (“What happened?”, “What’s happening?”), allowing to evaluate or extrapolate decisions made by management. These professionals deal daily with analytical processing, data monitoring, performance management, reporting, metrics, and KPIs.
Business Analytics, on the other hand, is dedicated to exploring, processing, and analyzing large amounts of accumulated data, to visualize trends and patterns, and forecast future scenarios (“What will happen?”, “What might happen in case of X or Y?”). These professionals often use data collection tools, quantitative and statistical analysis, predictive modeling, simulations, and optimizations to extract insights and support decision-making in the organization.
Data is deeply ingrained in an organization’s daily operations, mindset, and identity. And a data-driven culture empowers your employees with the know-how to know, tackle and even anticipate their most complex professional challenges. Along the way, these people become more creative and practical, applying and optimizing their time on strategically identified operations, knowledge creation… and innovation generation.
Also, in the book “Creating a Data-Driven Organization: Practical Advice from the Trenches,” Carl Anderson explains, “In a data-driven world, that means making sure that everyone understands the objective, the data collected, the metrics, and how the primary decision maker is interpreting the evidence. Give others a chance to put forward their interpretations and views if those differ, and get everyone on board, but also get inputs on other perspectives that the decision-maker may have missed. To help, remember this neat mnemonic, DECIDE: Define the problem. Establish the criteria. Consider all the alternatives. Identify the best alternative. Develop and implement a plan of action. Evaluate and monitor the solution and feedback when necessary. In other words, ensure stakeholders are on board with these steps.”
In short: we can gauge that technology, skills, and culture are three distinct but complementary foundations for an organization to become truly data-driven. Technology and skills leverage the first part of this process (creation, collection, and analysis). However, the culture determines the mindset and how the organization will leverage the findings. Will you trust them? How will you act on them? With what goals? What role do teams and individuals play in the process?
The International Data Corporation estimates that by 2025, the volume of data created will reach 180 zettabytes! In this context of increasing digitalization, organizations that are not yet data-driven will continue to move away from the ranks of organizations that triumph in Economy 4.0, losing themselves forever in the chaos described by author Geoffrey Moore in this sentence: “Without Data, you are blind and deaf and in the middle of a freeway”.
*This article was originally published in newDATAmagazine®.