How Data Analytics Can Help in Making Better Operational Decisions
In any business, it’s the role of an operations manager to make critical decisions that will cause ripples throughout the entire value chain. In the course of doing so, he asks himself certain questions. What kinds of raw materials will reduce total cost? How can we schedule and manage production so as to maximise throughput? And how can we schedule maintenance so as to cause the least amount of disruptions?
In the past, such crucial decisions were made, keeping these questions in mind, based on general rules of thumb or traditional business intelligence. Today’s managers and leaders, however, have the support of technology and advanced data analytics to make well-informed decisions that optimize value on all levels.
With that said, there is still a steep learning curve for many of these operations leaders in terms of understanding how they can best apply advanced analytics in their companies. Those who don’t necessarily have a background in analytics might find it challenging having to figure out the many difficult terms alone. Such lack of awareness or experience can make it difficult for managers to identify and employ the best techniques that will work to their advantage. In short, they might lose important business opportunities simply because they cannot properly comprehend and harness the power of analytics.
To better understand what advanced analytics is about, we suggest thinking about it in terms of three aspects: analysis, modelling, and optimization.
Analysis: Looking Back on the Past
Analysis is the most basic stage of advanced analytics. It entails looking back on the past—that is, gathering data about a company’s past performance and analysing said data. During the process, a selection of key performance indicators (KPIs) are gradually identified and summarised. This stage provides unique insight into the different factors that drive value as well as suggests solutions that can increase value.
Modelling: All About Simulations and Possibilities
While analysis looks back on past events, modelling is all about predicting the future—that is, simulations of the future. In this stage, a company can predict possible scenarios for their business with the help of a model. (“Model” in this instance refers to any abstract representation of a company or organisation.) With modelling, managers can experiment with different strategies and perceive the resulting outcomes free from any risk, in what is essentially a virtual reality.
Optimization: Maximising The Value of Your Decisions
After analysis and modelling comes the final stage: optimization. This is the phase when the rewards from applying analysis and using modelling finally reach fruition. Using data gleaned from the previous two stages, managers are now better equipped to make decisions for their businesses that will optimize value creation on every level. Every business faces complex problems in its day-to-day operations, and the bigger the company, the more complicated the issues. Simply put, optimization techniques help in identifying the best possible solution for these problems.
The Future of Advanced Analytics
It remains to be seen how far analytics can go in terms of technological development. But one thing’s obvious: with analytics, managers now have the power to transform their businesses and thus change the world.