Faced with overwhelming amounts of data, organizations across the world are looking at leveraging data and analytics (D&A) to derive insights to increase revenue, reduce costs, and mitigate risks. McKinsey found that insight-driven companies report EBITDA (earnings before interest, taxes, depreciation, and amortization) increases of up to 25% [1]. According to belgium whatsapp number data Forrester, organizations that use data and insights for decision-making are almost three times more likely to achieve double-digit growth [2]. However, not many organizations are successful in transforming their data into insights despite being data-rich and having high D&A ambitions. In January of 2019, research advisory firm Gartner reported that 80% of D&A projects did not deliver business outcomes [3]. While there are many reasons for this poor success rate, one key factor is that many firms struggle to effectively consume the insights derived from D&A.
But what exactly is an insight? Insight is the unknown elements such as relationships, patterns, categorization, inferences, prediction, and so on, if known will influence decision-making. These insights are typically derived using a combination of descriptive analytics, predictive analytics, and prescriptive analytics techniques. Descriptive analytics – “what happened” – analyzes historical data to identify past or lagging patterns. Predictive analytics – “what will happen” – forecasts future trends and events from historical data. Finally, Prescriptive analytics – “what will make it happen” – recommends the best course of action by using the insights derived from predictive analytics.