How Can Managers Leverage Data for Decision Making?

We live in a world where it feels like we are drowning in structured, as well as unstructured data. Buzzwords, such as Artificial Intelligence, Big Data, Cloud Computing, the Internet of Things (IoT), and Blockchain may be thrown at us at every turn.?Sometimes, it may seem nearly impossible to keep up with the staggering amount of information available around us. Yet, when harnessed appropriately, data has the power to drive some of the most effective and accurate decisions in all areas of business.

Data-driven decision-making is about using facts, data, and metrics to make verified and informed strategic decisions that align with the goals, objectives, and priorities of the business. The question is, are we embracing the power of business intelligence to make decisions that can spur business growth and contribute to a healthy bottom line? Or, are we caught up in gut-based decisions because they happen to be romanticized by certain management gurus or corporate head honchos?

Data-Led Decisions Versus Intuitive Decisions: Is there a Happy Medium?

Intuition is a powerful tool and a necessary aspect of data-driven decision-making. Before the availability of such large and copious amounts of data and information at our fingertips, most leaders and managers relied on their gut. However, in today’s complex business landscape with ever-changing variables, decisions based entirely on instinct and detached from rigorous analysis would be an unreliable guide. At the same time, one needs to be careful about the “big data – no judgment” phenomenon. With the advanced, feature-rich tools and technology available today, we may have instant access to tons of data and analytics, along with the most impressive reports and presentations. But, if we become too fixated on the data, it is possible that we may fail to recognize the context of the business. In order to draw true and complete insights, we still need to combine the data with knowledge, experience, and domain/ business context. This will not only increase transparency and improve the accuracy of the interpretations, but it will also help us avoid blind spots (if any) and pursue opportunities in line with the business nuances.

Current Adoption of Data-driven Decision Making

In an S&P report that studied the Use of data, AI, and analytics in 370+ organizations across the globe, 26% of the executives said “nearly all” of their decisions are data-driven, while 44% said “most” decisions are data-driven. A PwC India report on Using Advanced Analytics to make Big Decisions concludes that 61% of executives believe their organizations make highly data-driven decisions. From IT, BFSI, and transportation, to manufacturing, healthcare, and retail (including e-commerce),?businesses across sectors have invested in technology that enables data-led decision-making. Whether it is through CRM data, financial flows, operational metrics, or employee performance data, there are numerous potential business intelligence opportunities in technology-supported organizations.?

Benefits of Data-Driven Decision Making

Tracking financial, sales, and marketing KPIs, analyzing the performance of your products and services, observing and analyzing customer behavior and usage habits, building dashboards to visualize data, and cross-referencing the data with various internal and external factors are all essential elements of making data-led decisions. However, the benefits of data-driven decision-making are immense. Here are just a few that I am listing

ü?Better resource utilization

ü?Improved Product/ Service and Pricing

ü?Happier Customers and Employees

ü?Improved Reach

ü?Better Organizational Problem Solving

ü?Minimized Bias in Decision Making

ü?Reduced Costs and Increased Profitability

Being a data-driven organization can undoubtedly contribute towards better decisions, reduced risks, and long-term business success. Look at some of the most inspiring examples of data-led decisions.

After Google created a People Analytics department (Project Oxygen), they could make better data-led decisions in all aspects of HR, including hiring, retention, diversity, and talent management. This team also culled out 8 distinct characteristics for managerial success, based on which Google revised their management training initiatives, as well as manager recognition programs.

Southwest Airlines studied the online behaviors and actions of customers to understand what new services would be most popular, yet profitable for the company. This data enabled the airline to provide different customer segments with the best rates for their needs, along with enhanced service experiences. Over the years, this has helped them build a significant customer base with strong brand loyalty.

Amazon’s data-driven decisions are also well-known in the industry. Using their customers’ past purchase data and pairing it with behavioral analytics techniques, Amazon was able to generate accurate product recommendations, which improved the customers’ shopping experience, and in turn, boosted sales and revenues.

Potential Pitfalls of Data-Based Decision-Making

Being overly reliant on data does have its pitfalls. More often than not the data can be stale and dated by the time you are making your decision. Another issue could be what data critiques typically call “Garbage in garbage out”. Essentially, the quality, accuracy, and consistency of the input data could be one of the biggest obstacles in generating meaningful analyses or interpretations. Other problems may include insufficient information for the past years, or an inability to measure certain intangible variables. Even if data is available in plenty, there is always the possibility that one function or department misuses it to make interpretations that benefit them and disadvantage others.?

No decision-making is fool-proof. This is why there is always the need to achieve a delicate balance between data on the one hand, and intuition, knowledge, and experience on the other. Investing in data mining tools and technology, adopting the language of business analytics, and cultivating an organizational culture of data-driven decision-making can help us stay ahead of the curve in the years to come.