Below, compiled from some recent reactions to industry developments, and colored with some excellent ideas from founders I’ve met in the space, are three issues in enterprise HR that I believe can and will be solved through HCM software in the near term. If you have any reactions to the below as you experience them in your organization, are founding a company to solve any of these problems, or know of any great tools that address them, I’d love to hear from you:
1. Career advancement / restructuring — Comparison of performance and role / salary / comp structure to make sure that employees aren’t being undervalued. Imagine something that would automatically provide a list of suggested promotions / demotions based on corporate priorities vs. actuals. We’ve been doing this for years on a high level with financials (e.g. where are the shortfalls and why). Moving closer to the source, optimization and A/B testing are now helping us to make good on these opportunities. And we are already starting to do this in the planning / internal phase of things, namely via new DevOps practices and finally directly within Product Management groups (cf. startups like Wizeline, which is full disclosure one of ours). I posit large companies have huge invisible costs tied up in the gap between comp structures (based on qualifications / original expectations of performance ability upon hiring) and actual performance shortfalls due to structural inefficiencies.
2. Identify employees at risk of plateau / stagnation / flight — Turnover is a huge invisible cost for organizations, one I’ve written about before. If you could identify specific cases and likelihood accurately, this solution alone would be a potentially big software product. E.g. Joe is a 85% likely flight risk in the next 6 months due to various factors (e.g. performance, last promotion, salary vs. peers, commute time, marriage status, etc.). A nod to Darren Kaplan of HiQ, a great startup addressing this very issue. To some extent this is a data collection issue and solving it properly likely requires ML expertise (def. data-science heavy at the least). Ever work for a huge company, or know of someone who companied of “lack of visibility” or rigid management structures? If so I bet you know this problem first-hand.
3. Improve collaboration + influence intra-organization — This is a bit more of a vague one; tougher to determine what the “hard ROI” would be. But think about the proliferation of enterprise communications data we only recently have access to that’s going relatively unused. Theoretical example: John and Stacy are structured in the org together but only communicate 50% of the average. Or, looking at X company, outperformers email 100 times a day, while underperformers email 500 times a day (implication: initiative to reduce email). Also figuring out a way to make great / more experienced employees a resource for others (e.g. training young employees, solving point problems, for idea generation, or even just to maintain a healthy culture).