Decision-making in business: Simple or Difficult?
The consequences of making a decision
Decision-making in companies sounds simple in theory, but difficult to do, in practice. Company CEOs and executives need to look at the information, contact the right people and make a decision – sounds easy enough, right? Sadly, that’s not always the case. When they make the right decision, executives, CEOs and employees will benefit. Stock prices go up, bonuses roll in, and no mass layoffs occur.
However, if the decision was wrong, it will have regressive effects on company earnings. When earnings go down, everyone from the CEO to the employees will feel the ramifications. Stock prices go down in reaction to lower earnings, employees are laid off in large scale to make up the difference. In some cases, the situation becomes so severe that even the CEO is fired.
Thus, CEOs and executives contend with high stakes when making a decision.
Why does decision making go wrong?
There are several reasons why decision-making can go wrong, like a lack of communication or poor processes. However, one reason is the external factors that affect a company’s fortunes. While companies acknowledge the influence of external factors on their chances, it is challenging to see its precise impact. In such cases, all executives and the CEO can do is follow their intuition when making a decision. The problem with that method is that so much is left to chance. There is no guarantee that the right decision was made, and in a company where millions of dollars and thousands of people are at stake, uncertainty in decision making is just unacceptable.
To reduce the likelihood of errors, company heads need an extra tool in their decision-making arsenal: Diagnostic analytics.
What is diagnostic analytics?
Diagnostic analytics is an advanced branch of data analytics built to answer one question: “Why did it happen?” by finding the correlation and causation between two key variables. Diagnostic analytics uses several advanced techniques to answer that question, including regression analysis, data mining, drill-down, data discovery and data mining. The branch of analytics builds on the information provided by descriptive analytics. Therefore, it’s safe to say that companies must be using planning and descriptive analytics to make full use of diagnostic analytics.
How does diagnostic analytics improve decision-making?
A complete picture for business leaders
With judicious use of diagnostic analytics, company heads can make decisions that lead to year-on-year growth, while cutting costs at the same time. Business leaders don’t have to deal with the uncertainty that usually comes with decision-making because they now have a detailed, comprehensive picture of the situation to make a well-informed decision. With diagnostic analytics, executives have iron-clad certainty that they are making the right decisions, or at least, the decisions with the most chances of success.
Integrates internal and external sources
Diagnostic analytics draws data from both internal and external sources to illustrate a series of connections and correlations between two variables, to find new and unexpected links. Furthermore, it’s possible to incorporate external information with internal data meaningfully. For example, a retail store can discover sales based on location, weather, traffic, parking and other variables. Something companies found challenging to accomplish without a data analytics tool.
Create a data-driven culture
It not only helps company heads make more accurate decisions but can even curate a more data-driven culture. A data-driven culture leads to a refinement of the collection, curation, analysis and diagnosis of data, which creates greater awareness of how the company operates. When there is greater awareness of how the company works, analysts can discover unique opportunities for growth that would have never been discoverable otherwise.
Diagnostic analytics’ ability to draw connections and causation between two variables makes it a valuable asset in decision-making. Analytics provides a comprehensive, detailed picture of a situation, which aids company leaders in making the right decisions. Furthermore, diagnostic analytics, allows CEOs to make more accurate decisions, which increases earnings and reduces the chances of large-scale layoffs. The analytics tool removes uncertainty from decision-making.
Want to learn about data analytics and its benefits in non-profit, aviation, marketing and more? Find everything you need, here at Selerity.