2020-01-23 HR Examiner article john sumser AI and Intelligent Software Implementation in HR photo img cc0 via pexels board game 207924 544x305px-corrected.jpg

“The one thing to keep in mind with early experiments is that improving a single process with an intelligent machine is profoundly different from managing at scale.” - John Sumser

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Get Clarity with your objectives. Never Buy Without A Specific Use In Mind.

ROI is the wrong premise for purchasing intelligent tools. While there is a cash return somewhere down the road, current investments are about maintaining agility and learning to operate in the new environment. It is completely predictable that the technology will change so much that you feel like you are constantly starting over.

The one thing to keep in mind with early experiments is that improving a single process with an intelligent machine is profoundly different from managing at scale.

Early experiments with intelligent tools are partly about the specific task and partly about learning how to manage ‘digital employees.’ The current crop of ‘potential digital employees’ are the worst sort of employee imaginable. They require explicit instructions because they are literal. They keep going until you tell them to stop. They have no conscience or compassion. They must be completely retrained when something goes wrong. They think the entire universe is what they have been programmed to know. And their outputs and predictions are limited by the data set they process.

2017-04-21 HRExaminer photo img sumser john bio pic IMG 3046 black and white full 200px.jpg

John Sumser is a Principal Analyst for HRExaminer.

It is unlikely that many jobs involving more than repeatable administrative tasks will be automated any time soon. Instead, job holders will get new digital interns who require a great deal of supervision. Having a clear problem to solve makes it easier to get comfortable with noticing when the machine is wrong and learning how to fix it.

And still, this is the separating point between 20th and 21st century work realities.

Costs Of Management, Maintenance, And Training.

Intelligent tools use new kinds of technology, make new kinds of mistakes, and may produce inconsistent results. Staff members will have to learn how to take care of the tool and help the organization up the learning curve when data models, sources, interfaces, or integrations change abruptly (as they will). It will pay to overestimate the costs of operating a system of intelligent tools.

Many vendor’s claims depend on the client’s ability to deliver specific documentation online. The cost of and schedule for developing the material must be a part of the conversation.

Should you purchase a Suite or Point solution?

The narrower the focus, the deeper the solution. It is not possible for a provider of a comprehensive set of services to provide the depth of a vendor who is focused on a single problem. While many practitioners can imagine a perfectly integrated set of tools built from ‘best of breed’ products, the reality is that aggregated tools inevitably run into prioritization problems that eliminate the possibility.

There are significant risks and benefits associated with choosing a suite solution. This category includes all legacy providers who are fielding intelligent solutions across the subset modules in their solutions. These vendors have tons of historical data with which to train their intelligent tools. They have deep experience across the depth and breadth of HR. They are uniquely suited to providing cross-functional insight. Many are building ‘ecosystems’ of providers who provide supplemental tools for their ‘platform.’

The problem is that buying into a single system locks you into a point of view about what’s important, what should be managed, and what needs attention. As long as your company world view aligns with the vendor, no problem. Shifting vendors becomes more and more difficult as your measurements are aligned.

For example, nearly all intelligent tool providers offer some sort of ‘flight risk analysis.’ There are no standards for what data is best to predict whether an employee is likely to leave. The data model simply has to be able to predict prior year history to be validated. A time and attendance company with historical data will build an entirely different model than a talent management suite. There is no current method for comparing and contrasting. This raises the possibility that if the different programs were run on the same population, employees who would be on one list may not be on the other. Yet the premise of the tool is that who appears on the list is a critical component of management.

When your management practice is built on a foundation of one vendor’s point of view, it is difficult to switch to another.

There is also no central force that mandates data governance concerns for intelligent tools.

And the difference between tools as part of a larger suite and point solutions for specific tasks matters. Management tasks that are simply handled by the suite provider are the day to day headaches of the owners of point solution collections. While point solutions are often hands-down better at the unique tasks, they can also be more expensive for overall HR Management because they are not integrated into other tasks and functions and require separate attention.

The choice is not simple and bears close attention.
Next week, we’ll pick up the next chapter in this series with data cleanliness, data model standards, and process governance.

Catch Up on the Series

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