Mobile, web, smart devices, information systems, Internet of Things (IoT), apps – what do all these things have in common? They’re constantly generating data. Not just a few gigabytes mind you, but a scope of data on a gargantuan scale. It’s why businesses today are recognizing that to succeed in a data-driven economy, you need a strategy in place that not only sifts through the information, but turns this data into actionable insights. That recognition is translating to investment, according to a recent report by research firm MarketsandMarkets. The report forecasted the global prescriptive analytics market to reach $4.58 billion by 2021. This projected growth, up nearly 300 percent from $1.16 billion in 2016, reflects the desire for analytics solutions that can improve operating decisions (and ultimately the bottom line) in real-time. I’m proud to say that Profitect was recognized as a top provider of prescriptive analytics software by MarketsandMarkets in this report.
Interestingly, but not surprisingly, this growth runs in tandem with further investment in data-creating technologies such as IoT. Retailers have been on the forefront of IoT adoption and are seeing the value of prescriptive firsthand. During the National Retail Federation’s (NRF) Big Show this past January, I spoke alongside Seth Hughes of Walgreen’s and Andrea Weiss of The O Alliance Consulting to discuss the impact of IoT, machine learning, and artificial intelligence on big data investments. With each of these technologies, we came to the same conclusion: you are not maximizing the value of your data if you don’t have the right tools to make sense of it.
At Profitect we view the growth of prescriptive analytics as intrinsically linked to the democratization of data. As budgets for analytics investment rises, CIOs will look for solutions that emphasize ease of use and deployment. It is a much more difficult justification for the rest of the C-suite when you push for a technology that requires additional hires to effectively generate value. Delivering insights in simple language to the right person, rather than relying on data scientists for translation, will be a key factor in ensuring widespread adoption.
The ultimate goal of analytics is to make data work for you as efficiently as possible. What separates prescriptive is its ability to generate real-time value through immediate action, and ultimately this is what will continue to drive growth through 2021 and beyond.
For more information about prescriptive analytics, check out my full presentation from NRF 2017: NRF 2017 Prescriptive Analytics, Machine Learning & IoT.