I recently attended the Gartner BPM Symposium in London, and from my observations four key themes emerged, in the era of the social network, Social CRM was topical, mobile, analytics or what I prefer to call predictive processing and of course no IT conference would be complete without some discussion of Cloud computing and indeed the theme "BPM in the Cloud" was discussed.
Today we will look at Predictive Analaytics, the remaining themes will be looked at in the later instalments.
Daryl Plumber, Gartner analyst, predicted that analytics would take centre stage in the next wave of BPM implementations. We are already seeing that in CRM applications for complex cross sell and up sell decision trees for customers Chordiant, now Part of Pega systems provides one the industry’s leading CRM decision engine. Meanwhile my colleagues and I have been defining a defining architecture that incorporates analytics into the continuous improvement cycle. We found that although many of our customers had invested both in BPM and Analytics solutions they had not integrated them in a holistic way. All too frequently raw process data was being fed into analytics engines to be turned into dashboards or worse still static reports.
Today we will look at Predictive Analaytics, the remaining themes will be looked at in the later instalments.
Daryl Plumber, Gartner analyst, predicted that analytics would take centre stage in the next wave of BPM implementations. We are already seeing that in CRM applications for complex cross sell and up sell decision trees for customers Chordiant, now Part of Pega systems provides one the industry’s leading CRM decision engine. Meanwhile my colleagues and I have been defining a defining architecture that incorporates analytics into the continuous improvement cycle. We found that although many of our customers had invested both in BPM and Analytics solutions they had not integrated them in a holistic way. All too frequently raw process data was being fed into analytics engines to be turned into dashboards or worse still static reports.
Managers are already churning through a deluge of data, in the form of email alerts, reports, dashboards and now tweets and blogs. What we want to do is make processes self aware such that they change or at least suggest changes based on real time information. There are endless scenarios and where this could be useful, an insurance company receiving a spike in calls regarding accidents from a certain make of car for example, might want to raise the premium on those models based on the increased risk. They might also want to send a letter to the manufacturer asking them to investigate the pattern and save managers hundreds of hours by having the process suggest or even implement the changes themselves. Rather than waiting for human intervention and potential loss of revenue, customers or damage to reputation.
With the increase in the frequency and volume of data humans are no longer able to digest absorb and make decision quickly enough. More importantly some patterns of behaviour are invisible to the naked eye. Today’s Analytics sophisticated analytics engines are able to read, absorb and interpret, terabytes of data detect and find patterns. These patterns can be translated to rules which we can then incorporate into our processes. We call this predictive analytics and targeted solutions are coming soon.
No comments:
Post a Comment