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3 Big Issues In HCM: 2014

June 20, 2016

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).