Best is yet to come for analytics

Otso Massala

The exciting era of digitalization we are living in is showing a lot of progress in the advances of using analytics in the business applications to improve the lives of customers, employees and ourselves.

And the best might be yet to come.

Digitalization is creating large amounts of data, and analytics can be used to discover, interpret and communicate meaningful patterns in such data.

There are unprecedented amounts of data available. According to an IBM estimate, 90 percent of data currently stored has been created within the past two years. The fact that we interact largely over the internet — social media, VoIP, email, digital broadcasting, on-line shopping and securities trading — as well as control systems digitally — production control, traffic control and vehicle control — means there is enormous data collection that is constantly updated. This data contains patterns, some of which are fairly stable while some appear only during short instances. Analytics aims to discover those patterns and communicate them to decision makers so quality can be improved.

Recent development has been requiring a move from use of well-codified, internally generated numeric data to more rich, externally generated and less systematically codified data. A significant portion of data is qualitative — unstructured text, pictures and voice — and this makes it necessary develop advanced data mining techniques to treat it. In business contexts, analytics are typically combining the internal data sources with external ones.

One important advantage of analyzing large datasets is that it allows model-based testing of alternative business approaches. A predictive stochastic model might be used for almost any decision: pricing, timing, location, assortment, customer segmentation, supply sourcing etc.

The goal of using data analytics in business is to boost profitability, predictability, sustainability and social impact, among others. The following few examples might provide readers a starting point to learn more about analytics.

• Medical decision making uses large datasets about the circumstances of millions of patients and combines it with the results of particular treatment options, so that doctors can make better decisions.

• On sales and marketing applications, when the pricing decisions can be tested with models grounded in the reality of previous customer segmenting and pricing decisions, it is easier to set optimal prices. If the trend of user traffic on a company’s website is discovered by user analytics, it is easier to obtain high impact by online presence. Demand forecast models based on the internal and external data facilitate inventory level and assortment decisions.

It would be easy to continue the list, but I trust you have the idea and can realize some applications in your own circumstances.

When I communicate with various business participants in our area in my role at Shippensburg University’s John L. Grove College of Business, I get a very strong sense that professional opportunities is especially bright for people with analytics competencies.

Some organizations are in the process of building their analytics fundamentals. Other companies are well on their way to extend their advance-analytics models. In both occasions, one of the principal needs is to find experts. Computer-coding skills are in fashion, however the statistical language “R” has allowed streamlining of statistical searches. And user interface is getting more customer friendly with graphical illustration of analytics results.

And here’s something else: Analytics is connected to artificial intelligence, and that combination is creating an extremely rich field of opportunities for creating new businesses and improving the existing ones.

The current business landscape is dominated by companies heavily relying on business analytics, such as Amazon, Uber and Alpha

bet, and therefore it appears like a priority for other companies too to emphasize analytics.

Otso Massala is an associate professor and director of the Charles H. Diller Jr. Center for Entrepreneurial Leadership and Innovation in the John L. Grove College of Business at Shippensburg University in Shippensburg, Pa. Email him at