Highest Paid Person's Opinion (HiPPO) vs. Geek - Why Human Resources Needs To Get More Geeky

This week Razorfish Global hosted its annual technology summit here in New York. We had a really awesome line-up of speakers - both internally and externally, but my favorite was Andrew McAfee, co-author with Erik Brynjolfsson of Race Against The Machine and The Second Machine Age. Andrew's work, as most of you may already know, is the inspiration for lots of my concepts around the future of work and HR. 

During his talk, McAfee illustrates the impact technology will have on the work that we humans have been good at for centuries. Years ago we thought that cars would never be able to drive themselves but now we find Google with their autonomous cars and realize we were wrong. We professed that a machine could never win at Jeopardy and after a few years, IBM Watson handily won against the best players. My favorite part of Andrew's presentation is when he talks about the battle between the Geeks and HiPPOs. He explains that with all this data and information available to us, we continue to rely on the decision making of what McAfee calls HiPPOs (Highest Paid Person's Opinions), instead of the Geeks. His main message is to encourage each of us to become more "geeky".  

A very compelling argument, McAfee goes through a bunch of examples of where geeks (or a person focused on data and results) were more accurate in their predictions than the HiPPO. He references Robert Parker, who is the most influential critic in the wine industry, also known as, the "million dollar nose". Parker, as McAfee describes, is a classic HiPPO. Then enters an economist named Orley Ashenfelter, who says "I want to be more geeky about this approach" and uses public weather data to determine the quality of wine and prices. The wine world freaked out at first, but his predictions were actually very good. Many people who make investments in wine now reference Ashenfelter's newsletter. 

The HiPPO effect is widespread in Human Resources and Talent. For years, we were led by HiPPOS (I wanted to link to a twitter list here but held back) that used their gut information to drive decisions and suggested programs. In this new paradigm, led by companies like Google, we all need to be more data driven.  Here is how to start thinking about pushing more of a data-driven decision-making within your talent functions:  

• Recruiting - we have lots of data in recruiting, but in most cases we are looking at the wrong data or not using it to make business decisions about where to find the right talent. We don't truly get an idea of referral source (using our website as a referral source is a bad idea), we don't tie hires to performance, thus we are tracking information and data - but it's the wrong data.  
• Performance - this information, in most cases, is completely useless. Managers go through a process of 60 questions where they are more likely to score you safely than an actual representation of your performance. Add in self and peer reviews that are based on your last project or the last 30-days and all this information is just misguided. What we need is to get smarter and "more geeky" here and find tools that allow us to track performance over a period time, based on real world events that take place, whether projects or events. A technology that can pull from existing systems and create an awesome data set that can be used to guide performance and coaching at the right moment in your career cycle.  Ask me about the SWAN project.  
• Learning - in some cases, we continue to throw darts in the dark. It's rare that we are able to truly understand the needs of the business and how learning can drive it forward towards its goals. We instead make gut decisions and take HiPPO advice on what courses to provide, when to provide them, and the methods to which they are delivered.  We have a ton of data in our learning management systems that can help guide us on the content that is interesting and more importantly the content that folks are not engaging with, so can focus on the stuff that works. We can also look at broader business data to understand what the business needs to succeed (e.g. delivering a storytelling class before a business pitch) or where we are missing the mark with our talent. 
• Data & Metrics Focus - if you are lucky, you have a bunch of folks that actually provide you with data on a regular basis. If you are this lucky, then look at the data and figure out what is helpful in making decisions and what is "just data".  Measuring headcount probably has no business impact unless you are a building a new location, but turnover could be interesting if you can dive deeper into the numbers to find out timing, the discipline or manager responsible, the stage of career, as well as other elements. The key to all of this is to let data drive discussions and program changes.  

The HR profession is plagued by HiPPOs, so as McAfee suggests, I think it needs to be more geeky.