The data revolution is in full swing, and organizations are starting to realize the power of their data. However, many are still stuck in their analytics phase. But what if we told you that companies don’t need analytics? What they do need is to learn decision intelligence, which is something that most companies lack.
In recent years, the practice of using analytics to make business decisions has become commonplace. However, there is a growing movement of thought that believes companies are overemphasizing the role of analytics and not giving enough attention to the role of human decision-making. This school of thought believes that what companies really need to focus on is not analytics but rather decision intelligence.
But what does that mean in practice? And how can companies use analytics to make better decisions? In this blog post, we’ll explore the concept of decision intelligence and show you how companies can use analytics to get smarter about their decisions.
What are data analytics, and why do they sometimes struggle to deliver value?
Data analytics is the process of examining data to draw conclusions from it. In business, the main goal of data analytics is to interpret trends and make predictions based on newly discovered patterns. Businesses use data analytics to guide their strategies and make better overall decisions. Or that’s what everyone claims at least.
Now that we have the definitions out of our way, let’s discuss why your business needs more than just data analytics. The answer lies in the limitations of a data-driven way of solving problems.
According to a recent survey by Abby McCain, 24% of companies use big data analytics. While 97.2% of companies say they’re investing in big data and AI projects, just 24% describe their organizations as data-driven.
In this instance, data-driven means that these companies use the data they collect and analyze to inform their decision-making. Therefore, about 75 percent of businesses don’t actually use their data for anything.
Companies make decisions about their customers, products, services, and pricing, but the data becomes a liability because it does not provide anecdotes about their decision-making. Decisions should come from personal interaction. In other words, companies need to incorporate decision intelligence into their data analytics process.
What is Decision Intelligence?
Decision intelligence is the ability to make decisions that are not only based on data, but also on an understanding of the complexities of the situation and the human factors involved. It is a process that takes into account both the analytical and the human elements of decision-making.
Those who advocate for decision intelligence believe that it is a more holistic and effective approach to making business decisions. They argue that the overemphasis on analytics has led to a situation where companies are missing out on important opportunities because they are not taking into account the human factor.
As we move forward, it will be interesting to see if more companies adopt a decision intelligence approach to business decision-making.
Why move from data analytics to decision intelligence?
As mentioned, in the world of business intelligence, we are always looking for patterns and correlations between variables. But what happens when we have too much data? How do we decide what variables to analyze? How do we know when we’ve found the right correlations? It’s a dilemma that plagues many organizations today: how do we decide which data thread to follow?
The answer is simple: we need to move beyond data analytics and into decision intelligence.
After all, with data analytics, you simply collect data and analyze it, right? But analytics is only half the picture when it comes to making decisions. Your data analytics magic is no longer enough. The magic is gone! Data analytics alone can only tell you when a problem does or doesn’t exist, or whether that problem is about to cost your company a lot of time and money.
Furthermore, the human mind often makes biased decisions based on emotions and prior experiences, not always with logical decision-making behaviors. To help reduce the number of biased decisions, companies can rely on decision Intelligence to make more deliberate, intentional, and strategic data-backed conclusions.
You may think that these personal prejudices aren’t that harmful to your business. After all, who knows the business better than your users, right? Well, that sort of thinking can quickly lead to major inaccuracies and lost revenue. So, when you actually think about it, do you really want to rely on your team looking for data to back up their decisions? Or do you want to introduce a data-first culture within your company that makes their decisions based on the data at hand?
The choice is yours, but we know what the top leading companies are choosing, and it doesn’t end with a biased decision-making process.
Conclusion
Understanding the relationships between data points, using data to identify and predict trends, and making decisions based on data-driven insights are all essential components of this new approach that will help you make better decisions and achieve your goals. Commit today and start seeing the benefits of going from data analytics to decision intelligence.
