Can Complementary Investments Pay Off with Predictive Analytics?

Predictive Analytics Technology

By the year 2022, the predictive analytics technology industry is expected to be worth around more than 273 billion dollars. Though there has been quite a lot of optimism around big data and the predictive abilities of technologies, such as Machine Learning (ML) and statistical modelling and, not all organizations who invest in these technologies are able to reap their benefits. This has led to a lot of studies to understand why can’t some organizations really enjoy the luxuries of such technologies.

Where the Problem Begins

A well-educated staff, complementary and significant expenditures in IT resources, and high-efficiency manufacturing processes have been determined to be “essential” for reaping the benefits of predictive tools that help organizations to make their performance most efficient.

Organizations that used predictive analytics have increased sales by $500,000 to $1 million on an average amongst the 30,000 manufacturers who were assessed in a 2015 research. On the other hand, organizations that did not make even one of these mutually reinforcing investments, availed little to no return.

Kristina McElheran, an assistant at the University of Toronto Scarborough and the Rotman School of Management, states, “Such complements give the organizational infrastructure to collate, assess, and react to forecasts based on objective data.”

“Investments in data collation and computer equipment that can transfer, store, and analyze data, for example, are included in IT capital. Educated workers are recognized to be an essential component of that system. Because of the techniques utilized in specific production contexts, data is richer.”

Government mandates for collating safety and environmental data has also helped push some firms to adopt predictive analytics by mandating them to execute necessary infrastructure and train workers to use it. Organizations who have been h=nudged in this manner eventually displayed stronger performance, according to the researcher’s findings.

IT investments and Predictive Analytics

It is not a secret in the management world that IT investments attain better returns on being supported by educated workers and vice versa. What the research demonstrates is that some organizations have not yet established a connection in the context of predictive analytics, states Prof. McElheran. We definitely are puzzled,” states the professor. “More research is required to understand the market or organizational frictions that are a cause of this apparent misalignment, something that is a huge liability in the organizations that we have been observing.”

Prof. McElheran and her co-authors have work together with the United States Census Bureau to create a survey which was completed by a highly illustrative sample of U.S. manufacturing firms in the years 2010 and 2015. The poll questioned the requirement and use of predictive analytics by management practices, manufacturers, data availability and usage in decision-making, and the design of the manufacturing processes.

Conclusion

This is one of the first studies to have been conducted to assess the impact of predictive technologies on productivity in a large sample. The findings of the study have been cross-referenced with other data, such as corporate production inputs and outputs. Manufacturers were selected as they are known for being early adopters of new technology.