This is the third part in my Analytics for Talent Management series. In this part I will cover analytics usage in the future and what the future holds.
Predictive analytics are where I predict the future lies (pun intended). Being able to read historical trends in data and provide simulated analytics that predict what will happen in the business will provide exceptional value and allow organizations to shape their strategy and goals based on trends. This is a concept that is used in a number of industries already, although not within Talent Management. If HR could predict future performance, behavior, risks, and growth – rather than use KPIs and metrics that look at past figures – they can focus their efforts to improve areas of concern and also mitigates against potential business risks. Now SAP HANA and SuccessFactors Headlines are making this a reality.
For me there are two concepts in predictive analytics: analytics that show how future trends (predictive) and analytics that can be modeled to show required future trends (modeled). Let me explain more.
Predictive analytics give the organization an overview of how the organization will be in the future, based on current and historical data. That is quite simple, yet extremely powerful. To provide an example, it could be possible to find out which individuals are most likely to a leave the company based on a combination of metrics, such as performance, career goals, time in current position, compa-ratio, etc. The business could then make a decision about compensation awards or merit increases to mitigate the risk of the individuals leaving. Predictive analytics can go a step further than what will happen, by predicting how something will happen and “what if” scenarios such as what is the outcome if this certain situation occurs or if this situation doesn’t occur. Even further it could help you determine how to prevent a situation from occurring or by helping to determine how to repeat a situation.
Modeled analytics could allow organizations to model analytics and then identify what data/actions they need in order to realize that type of analytic. Of course, in order to get this “target” data the business need to formulate a strategy that will deliver the required business results. For a simple example, an organization wants to have a hire to retention ratio of 80% over 2 years. The company inputs the analytic they hope to achieve and the modeler then “works backwards” to provide data on how many hires the organization are likely to make (based on previous hiring data) and also how many of these will have to remain in the business over 2 years to reach their target. The organization can then ensure that they create a strategy and provide programs to achieve this. This is a fairly simplistic example, and I’m sure some analytics experts like Mico Yuk, Ethan Jewett, Ingo Hilgefort, Joshua Fletcher, John Appleby or James Oswald can provide some better examples or insight into how this could work, but I wanted to try and give you an idea of this concept. While I have created this concept for this blog, I’m fairly sure that there are similar concepts in existence that cover this area and will become reality in the coming years. My understanding is that SAP is spending time on this and hopes to bring something to life in the near future.
These types of analytics require powerful processing and SAP HANA is the ideal technology to provide the platform for that level of processing. I know that SAP is looking at providing predictive and modeling capabilities for analytics and for talent activities such as recruiting and succession planning, so for me the future is incredibly exciting. I’ll be watching out for these types of movements within the SAP HCM arena.
Another important topic around analytics in the future is the use of standardized analytics and metrics for organizations. Currently there are no standards and different analytics packages are offering different types of analytical capabilities, both in terms of the types of analytics offered and how they are presented to the user. Different consultants also have different skills and visions when it comes to supporting analytic implementations and on-going usage, meaning that, again, organizations are getting different capabilities from competitors. Of course, this can provide a strategic advantage, but on the other hand some organizations are missing out on value-adding opportunities. If the industry could devise a set of standard analytics for Talent Management then this would drive additional benefits to organizations. The fourth part of my blog series focuses on this topic.
What are the future analytics of analytics?
Well, SAP HANA is going to be the future of processing technology and once SAP ERP HCM and SuccessFactors are running on HANA then technologies like ODP will be able to provide huge value to customers with large datasets. The same can be said for BW on HANA. I would love to think that predictive and modeled analytics are around the corner, but I simply cannot say if this will be the case. Although the tools are ready and customers are waiting for the technology, there is a lack of research in this area that is holding software vendors back.
13,500 organizations have introduced transactional HR with SAP (SAP ERP HCM) to support their businesses. Many of them have slowly moved to using SAP’s Talent Management and the next step for strategic HR is analytical capabilities. Traditionally this has been seen as an area for larger organizations, but it’s only a matter of time before the rest of the players begin to reap the benefits of using analytics to measure and predict how their organization is run. One method SAP is using is to provide Rapid Deployment Solutions (RDS) – pre-packaged solutions that will enable organizations to get going with analytics quickly and cheaply, quickly providing the sort of benefits that the larger organizations have. The SAP Executive HR Reporting RDS that I mentioned earlier is one example of this and the first of a series of releases planned by SAP Solution Management to get organizations quickly up-to-speed with analytics capabilities.
Mobile will certainly play a huge part in the future of analytics. As mobile device usage increases and platforms like HANA support better and faster delivery methods, the world of mobile analytics is opening up for mass consumption by executives and managers on the go. In essence, analytic data can be consumed any place, any time and in real time. The only “showstopper” for those not using SuccessFactors is the high cost and slow uptake of SAP’s on-premise mobile applications.