Enterprise data & analytics is having a significant impact on every industry, helping companies make better business decisions. It has grown from its roots with power-data users in the financial markets and marketing functions to proliferating across all industries, with the latest technologies enabling businesses to predict future outcomes. We’re even seeing data & analytics play an important role in the public sector, most notably in the recent presidential election.
However, advanced analytics, specifically statistical models used to predict future outcomes, has its limitations and flaws. In the presidential election, polls and pundits alike had Hillary Clinton winning by a wide margin. While Clinton did manage to win the popular vote, she won by a narrower margin than expected. More importantly, there were glaring errors in predicting 4-5 critical swing states, causing Clinton to lose these electoral votes and ultimately, a seat in the oval office.
Why then were so many forecasters, including the popular media, incorrect?
It’s important to remember that predictive modeling and advanced analytics don’t deliver perfect predictions. Rather, they deliver probabilistic outcomes with margin for error. Also, many of these models are also based on the relevant observed history, and for many data analysts, this history began when mass polling became popular in the 1970s, so the sample size is limited to every election between then and now. Finally, these models are all inherently based on the quality of the inputs, i.e. “garbage in, garbage out”. The Trump campaign was not without controversy, which, in retrospect, could have led some polled individuals into expressing false opinions, providing campaign analysts with poor data.
Giving false precision to probabilistic outcomes, flawed models, and poor data quality all affected the false perception held by the media, public, and even candidates.
Enterprise data & analytics is still in its early innings and has plenty of room for improvement. The use of predictive analytics & modeling is nascent, with lots of ground to cover before it can perfectly predict an outcome, and savvy investors and larger corporations remain very interested in the space.
To that end, there continues to be significant M&A and investment activity in the enterprise data & analytics space, including:
- Informa (LSE:INF) acquired Penton for $1.6bn,
- Salesforce (NYSE:CRM) acquired Krux for $340mm,
- Morningstar acquired Pitchbook Data for $225mm, Salesforce (NYSE:CRM) acquired BeyondCore for $100mm,
- Wavefront raised $52mm in funding from Tenaya Capital,
- BitSight Technologies raised $40mm in funding from Globespan Capital Partners,
- Paxata raised $33.5mm in funding led by Intel Capital, Datorama raised $32mm in funding from Lightspeed Venture Partners,
- 360Insights.com raised $30mm in funding from Sageview Capital,
- LexisNexis acquired Intelligize for an undisclosed sum.
We are active in the enterprise data & analytics space and are excited that the market continues to be strong for these businesses. We would be happy to discuss how we could help your business achieve its strategic goals – please do not hesitate to contact me.
If you’d like more information on the most notable transactions in this fast growing space, read more in our November 2016 EDA market report here.