HR people are always sharing technology horror stories such as, “we had 12 different applicant tracking systems” and “we couldn’t share data between our performance management and compensation systems.”
These stories always lean towards a longing for standardizing around one vendor and buying full suites. So are we on our way to the nirvana of having one hulking ERP that does everything?
Based on what I see out there, probably not. However much HR may want to have as few systems as possible, there seem to be little devils that are multiplying systems as fast as we consolidate them.
More new systems every year
One of those is acquisitions, and as long as companies are buying one another, HR is going to find that it has numerous systems to manage.
Another desirable devil is decentralization. Decentralization is, in many ways, a great thing. But what starts as a little local application, one that doesn’t touch anything else in the firm, can grow to be something of substance that needs to integrated with the other HR systems.
The other thing that always astounds me at the HR Tech conference is how many new vendors there are, each one keen to add to the already long list of applications you manage. You may have firmly decide that you won’t add anything new and then you come across something like EmpInfo which automates responding to tedious queries about an employee’s status (e.g. from a car dealership providing a loan) and you think “Well, we have to have that.”
There is a lot of “We have to have that,” and it’s true, you do, so maybe we should just embrace the reality of multiple systems just like we accept the enduring reality of our messy garage or disorganized closet.
What is interesting?
- Despite our ceaseless effort to reduce the number of different HR applications, new ones keep cropping up in our organizations.
What is really important?
- Since we are unlikely ever to reach the point of one system that rules them all, we should take seriously our need to be skilled in managing multiple vendors and integrating diverse data sets.