Predictive analytics in the cloud is becoming mainstream, with broader and accelerating adoption. We can say this based on recently completed Predictive Analytics in the Cloud Research, from Information-management.com
You can download the full report from the Information Management white paper library, but in this month’s column I thought I would highlight a few interesting results.
The most interesting result is that the number of companies which reported a positive impact from predictive analytics has risen dramatically since 2011. Two-thirds of this year’s respondents told that they've seen a positive impact from using predictive analytics in their organization.
On the other side, there was a similar rise in current and planned deployment of predictive analytics in the cloud since 2011.
For example, more than 60% of respondents said they were using at least one kind of predictive analytics in the cloud.
We can notice that this is is a big increase from 2011. What's even more interesting is that 90% of them said it was likely they would have at least one class of solution widely deployed in the next few years.
Of course, the main reason for all this activity was reduced cost. Advanced analytic applications used to be very high ROI but they were also really expensive.
In the last years, there was a constant pressure on market to deliver solutions which will be more cost effective. And we can all see that this is makeing a cloud deployments of predictive analytics more and more popular.
Meanwhile, data security and privacy, are still the primary obstacles reported.
We can notice that the use of predictive analytics is high in marketing and selling, but there's one more even important message which you should be aware of. It's about customer satisfaction, customer profitability and customer management - they are the main points of focus.
Of course, we all know that big data is a hot topic.
And when respondents were asked about new data types, we can see that more experienced analytic teams show much higher usage than in 2011.
With better skilled and more successful teams using big data it looks like that there will soon be rapid and significant growth in the use of new data types in building predictive analytics. Nevertheless, more traditional structured data remains broadly central to effective predictive analytic models.
Real time and near-real time data grew the most in importance in the last few years. And predictive analytics is focused exactly on this kind of data. This reflects a general shift in predictive analytics. This change is reflected in the increased use of intra-day and real-time data.
Exposure to predictive analytics in the cloud breeds enthusiasm. Those who buy into the promise of predictive analytics and get started like the results and want to do more. Organizations that get started have the opportunity to create differentiation from slower-moving competitors.
One last fact is also really interesting. As we are all aware of importance of embedding predictive analytics in operational systems, we found one result especially dramatic. More than 95 percent of respondents who reported tightly integrating predictive analytics into operations (decision management in other words) also reported transformative or significant impact. The percentage reporting such integration has risen significantly since 2011.
Decision management, with its systematic embedding of predictive analytics into automated decision-making systems, is an ideal approach to maximize the transformative power of predictive analytics and a rapidly growing area.
You can download the full report from the Information Management white paper library, but in this month’s column I thought I would highlight a few interesting results.
Source: Information-management.com