Back in 2016, Gartner produced its first research note on prescriptive analytics technology, the Forecast Snapshot of Prescriptive Analytics. Once again, River Logic was noted as one of the few major players that hold around 85% of the market share in the prescriptive technology space. The prescriptive analytics software market is set to reach $1.57 billion by 2021, with a 21% CAGR from 2016.
I wanted to share some takeaways from the research note that strongly support the rapid progression and adoption of prescriptive analytics, driving home the point that 'now is the time for companies to act!'
Major Learnings from Gartner's Forecast Snapshot of Prescriptive Analytics
Adoption of prescriptive analytics is currently at around 10% adoption within mid-to-large-sized companies — and that number is set to grow to 36% by 2021. There are several factors making the adoption of prescriptive analytics more wide-spread across business units and among business leaders.
- Organizations are investing more in people skilled in data science and decision management.
- Prescriptive analytics is moving beyond what used to be its core community: operations research and management science professionals. It's now becoming increasingly embedded in business applications and thus being leveraged by business leaders and analysts.
- The above trend is largely due to the fact that vendors are making their prescriptive analytics offerings easier to use by less skilled 'citizen data scientists.'
- Business leaders are in need of prescriptive analytics to help guide and automate complex decision making, things that Business Intelligence (BI) and predictive analytics are simply not cut out to do.
- Gartner predicts that by 2018, decision optimization will no longer be a niche discipline but a best practice.
In order for companies and business leaders to take full advantage of the major market opportunity in prescriptive analytics, people must educate themselves on things like:
- What decisions / planning processes are best suited for prescriptive analytics?
- What decisions / use cases serve as good starting points?
- What are the resource requirements to get going with prescriptive?
- What types of technology are on the market?
- What are the expected returns on investing in prescriptive?
and many more...
If you haven't already, grab a copy of our latest e-book: "Prescriptive Analytics for Business Leaders."