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5/31/2013
10:09 AM
Doug Henschen
Doug Henschen
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The IBM Way On Analytics

IBM analytic services size up HR data from multiple sources to predict employee satisfaction and retention. Warning: Consulting is required.

There's the IBM way, and then there's how most of its software rivals address customer needs. The difference in capsulized in new IBM Survey Analytics and IBM Retention Analytics capabilities announced Thursday that take on employee satisfaction and retention as a starting point.

The IBM way is to take a comprehensive, holistic approach, usually supported by consulting services. In an application-centric view of the world, in contrast, software vendors tend to look at company needs one RFP (request-for-proposal) at a time.

Plenty of human capital management (HCM) applications, for example, offer built-in analytics, but whether they're on-premises systems (like Oracle PeopleSoft or SAP HCM) or cloud-based systems (like Workday), the analytics are focused on what's managed by those system. IBM is an integrator of HCM systems and other applications (ERP, CRM, etc.), and as an analytics specialist it invariably looks to integrate and analyze information from across many systems, not just one app.

[ Want more on advanced analytics? Read Gartner Magic Quadrant Looks Beyond Business Intelligence. ]

The advantage of IBM's cross-systems approach is that it provides a more comprehensive view. In the case of HCM, for example, many companies have more than one application, with talent management and performance management increasingly handled by cloud-based apps such as Cornerstone, Oracle Taleo and SAP SuccessFactors.

Last year IBM spent $1.3 billion to join the crowd mentioned above by acquiring Kenexa, which addresses talent management, compensation management, employee engagement and leadership assessment with on-premises or cloud-based software.

The Survey Analytics and Retention Analytics services ingest information from across many systems, with HCM systems and Kenexa or third-party talent-management apps being just two options. A key twist with these new services is that they handle unstructured information, like open-ended questions in surveys and comments on internal company collaboration systems. It just so happens that Kenexa has a practice in conducting survey-based company-culture and employee-satisfaction assessments, but plenty of third-party firms do survey work as well.

In the HR context, Survey Analytics helps discern employee engagement and satisfaction, with a visual dashboard providing a visual heat map of sentiment trends broken down by employee segments. Retention Analytics crosses HR system data with internal collaboration data to spot high-attrition areas and the core issues behind those high attrition rates so companies can take steps to retain critical talent.

Survey Analytics and Retention Analytics also can be applied outside of the context of HR, and that's where the benefit of IBM's comprehensive approach really kicks in. Customer satisfaction and retention are the most obvious opportunities, in which case CRM systems, customer-satisfaction surveys and public-social-network data becomes the focus of the analysis. Distributor-dealer satisfaction and retention might be another play. Multiple problems are addressed by one analytic capability rather than creating multiple silos of analysis.

Another differentiator, at least in contrast to the analytics build into most apps, is that IBM generally focuses on predictive capabilities, as is the case with Survey Analytics and Retention Analytics.

"Having 'built-in analytics' tends to mean that you can do reporting, slice and dice the population in various ways and see what each segment of the population is doing," explains Murray Campbell, senior manager of business analytics at IBM Research. "Predictive analytics provides forward-looking insight into what's going to happen."

Beyond just extrapolating trends in data, for instance, predictive analytics can account for seasonality, historical patterns, the latest economic conditions, sentiment scores and other inputs to help you anticipate talent gaps or growing consumer demand that you might have otherwise missed.

The downside of IBM's approach is that everything starts with a consulting engagement, and it's not a one-and-done deployment. Consultants will size up the available data sources and the need and potential for various analyses and then the data-integration work begins. Because they're sophisticated predictive capabilities, Survey Analytics and Retention Analytics will require data-modeling work, both up-front and over time.

"Initially these capabilities are delivered as part of a consulting engagement ... and the models are refreshed as either market circumstances change or the data available changes or the organization changes its priorities," Campbell explains.

Finally, Survey Analytics and Retention Analytics are more open-ended propositions than packaged products or clearly priced services. They can be deployed on-premises or hosted in IBM's cloud.

Though they're described as "services," Survey Analytics and Retention Analytics are essentially custom-built services rather than the quickly deployed, cloud-based services that description might evoke. As described by Campbell, 80% of the service is repeatable -- with the data inputs and algorithms likely to be used known in advance -- but the final 20% is specific to each organization.

So the question for customers is, are you likely to be satisfied with the separate analytic dashboards built into or offered as add-on options to HCM and CRM systems? Or do you want more sophisticated, predictive capabilities that can span multiple capabilities and take in unstructured survey and social sources?

If you do want more sophisticated and flexible analytics, IBM isn't the only option. SAS, of course, also puts analytics first and treats all IT systems as potential data inputs. Among apps vendors, Oracle and SAP have recently amped up their predictive capabilities, and they also have business intelligence platforms can integrate data from multiple systems.

Unstructured data analysis capabilities are also becoming prevalent. SAS does it, Salesforce.com gained customer-centric capabilities with the acquisition of Radian6 two years ago and Oracle and SAP have added sentiment-analysis capabilities within the last year.

Are the other guys as geared up to provide consultative services and highly customized and tuned deployments (or is it all about the deal)? For that kind of care you might have to turn to a systems-integration partner -- something IBM has in house. Let your need for consulting and ongoing support, your desire for a one-stop shop and your budget be your guide.

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