December 2014 | Riviera Partners
First-time startup founders may know how to run a company, and they probably have a good idea about what makes a good product, but many don’t know what makes a great hire. New CEOs often have misconceptions about hiring, both when it comes to what...
First-time startup founders may know how to run a company, and they probably have a good idea about what makes a good product, but many don’t know what makes a great hire. New CEOs often have misconceptions about hiring, both when it comes to what they need and what candidates are looking for. While there are exceptions to every rule, we often witness four common mistakes–here are some tips on how to avoid them.
Don’t View Candidates as Commodities
New leaders can have a tendency to view candidates as commodities rather than people, and they treat hiring as a transactional process when it should be about building relationships. The fact is, you need to earn the right to vet and must be very hands-on in the front end of the process. There’s a huge amount of effort required when it comes to recruiting “branded” candidates who have worked for the likes of Google or Amazon. Keep in mind that people with high-profile experience aren’t going to flock to you just because you raised a big round. Everyone else is after these candidates as well, so you need to convince them that your “new and different” thing is really what they want to do.
Remember, Time is Valuable
Oftentimes, there’s a lack of understanding in the trade-offs that come with going after the subset of candidates that everyone else also wants, and one huge one is time. Time kills and it’s the only thing you can’t get back. A narrow view of what makes up the relevant candidate pool can lead to wasted weeks or months. Or even worse: bad hires. Either of those things can be deadly to any startup. Remember to always balance time invested, compensation and ultimate cultural fit.
Always Think Ahead
It’s important to realize that what you are now is not necessarily what you will become. Just like software, startups are version one of what they will be. Attend events, ask around and listen to the market (and those living in it) to get an honest appraisal of your brand and its future. This can help you make the right hire–and quickly. Also, when hiring, you should consider your needs two to three years in the future. Thinking holistically will ensure that you end up with a team that works together successfully.
Let Imagination Fly
Many first-time leaders have a lack of imagination around the best possible hire. When it comes down to it, branded candidates may not be the best fit for your company. Consider that many of these people bring a static way of doing things, which is generally not what a startup needs. Think outside the box and get creative on the type of person that could fit a particular position. Some of the best hires at companies like LinkedIn, Twitter and Uber came from non-obvious backgrounds.
A willingness to look past the likely suspects can help you to truly hire the stars of tomorrow and make a dramatic impact on your company. Remember, the goal should be to make the best hire, not achieve the biggest Techcrunch news release–the latter is fleeting, while the former can help lead to the success of your company.
November 2018 | Riviera Partners
Finding a new job is almost always a strategic career move and announcing that change to your network should also be approached thoughtfully. Jodi Jefferson from our New York office shares some guidance on how to approach sharing this exciting news with your network. (AlleyWatch) How...
October 2018 | Riviera Partners
Thinking About Diverse Teams as Systems by Jodi Jefferson, Riviera Partners It’s been a busy year for diversity in the news. Since the Google Manifesto and the Uber debacle, it has become clear that even large, forward-thinking tech companies continue to struggle with diversity...
October 2018 | Riviera Partners
Machine learning is a method used to devise complex models and algorithms that lend themselves to prediction – it sounds complicated and cumbersome, but this data really tells a story. Recently one of our engineers questioned why some searches take longer than others and decided...