As an executive recruiter who specializes in placing strategic analytics leaders, I am often tasked with helping CEOs determine the best route to take when making their first data science hire. The term “predictive analytics” sparks excitement in most business leaders, as it should. After all, the idea behind using data to accurately predict what your customers are going to want in the future can provide any organization with substantial growth opportunities. The problem, however, is that most executives don’t know where to start when it comes to implementing an analytics-based strategy.
More times than not, my first call with a new client turns into a strategy session rather than a typical meeting to go over a job description. My firm has always believed that if we can help nail down the needs based on what a client is looking to accomplish, we can truly add value in helping determine the best hire for the company. When we are asked to find a company’s first data scientist, our initial questions are always the same: What are you hoping to achieve by adding a data scientist? What are the predictions you are hoping to make with the use of analytics?
Often, our clients have a difficult time answering these questions. They know that predictive analytics can ultimately make their company more money but tend to underestimate the time it takes to make this happen. That’s why when I’m working with a client, it’s important for me to first figure out what stage of data maturity & analytics adoption that they’re in: the crawl stage, the walk stage, or the run stage. Because, just like anything that you’re starting off for the first time, you need to crawl before you walk, and walk before you run.
The Crawl Stage
The crawl stage is where the company is still determining how they want to specifically use analytics. They are in the process of identifying which areas of business can produce data to be used in this way. The best way to explain this is to think of analytics strategy the same way as any other business units.
For example, try to think about what it took to develop your sales team. Successful sales strategy typically doesn’t start with the hiring of a junior account executive, handing him or her a phone and saying, “Make us money.” The same goes for your analytics strategy. Hiring a data scientist, handing him or her a computer, and telling them to make predictions will end up in failure just as fast as that junior account executive with no direction.
So how did you set that junior account executive up for success versus failure? Chances are you first brought someone in to set the overall strategy of business development. This sales leader decided if your product or service is best sold via inbound marketing, grass roots campaigns, or channel partnerships. They helped you decide if SEO was the right route to take or if an investment in building an outbound sales team made more sense.
Your first data science hire should be someone you can lean on to determine the roadmap involved in achieving success in utilizing analytics. This should be someone who has previously overseen strategy—not just a mathematician, statistician, or engineer—and can help you figure out how you want to use data and where exactly the data will be coming from.
This person can show you how to direct your employees in logging crucial events and activities in a way that makes them easy to read in the form of a data set. He or she can also teach you how to use your reported data to track all areas of your business whether that be marketing, sales, finance, or even HR & operations related. The goal of all of this is to take everything that happens each day at your company, and use it to create readable data that can be analyzed and researched. The perfect person to do this is usually a Chief Analytics Officer or VP of Analytics.
The Walk Stage
Now that you’re crawling along as a data-driven business, it’s time to consider your next round of analytics hiring. This hire is going to be your walking step. This person should essentially be an expert on accurately reading and creating reports about the new data being collected by your company. They should be highly skilled at creating easy-to-understand dashboards for you and the rest of the executive team.
When you are walking successfully, you and your team of decision makers should know the ins and outs of what’s going on in your business simply by reading a report that tracks your data. You should be able to look at these reports and be able to see things that will help you capture the best return on all of your investments as a business owner or CEO. You should be able to determine from the reports the sales strategy that takes the smallest investment of time versus producing the best results, and you should even be able to make determinations about points in the month or quarter when your cash flow tends to get a little lighter.
It’s a satisfying feeling to know exactly where each department in your company stands by pulling up a quick data reporting dashboard, rather than digging through records to tediously figure this out. When you feel comfortable enough with these reports and the insights they are providing, you have officially mastered walking.
The Run Stage
The final stage is learning how to run. This is without a doubt the most fun part of the entire process. At this stage, you can use your newfound insights to make accurate predictions that leads to business growth. All the data you have been collecting and interpreting can now be used to build models or predictions.
With the help of programming and some advanced mathematics, models can be your fortune teller. They can tell you what your customers will likely want later in the year based on their previous actions and behaviors. They can tell you how to prepare your finances for upcoming investment opportunities, and even tell you the perfect benefits and compensation structures to select for your HR team.
The return on investment that you will see when you are finally up and running with predictive models is massive. From here on out, the only ads you invest will be the ones that bring you the most revenue. Your product and service offerings, at any given time, will perfectly match the current needs of your customers. This is the point where your business has finally achieved “data-driven” status.
Running is best served by true data scientists. These are highly educated modelers who know how to combine computer science with mathematics. This stage is when you can implement the machine learning and artificial intelligence strategies you have been reading about. This is the stage when you truly enter the race against other data-driven competitors. The more data you create, the more reports being read, and the more models being built will allow you to continue running faster. That is how you ultimately win the race.
So when you decide as a business leader to make the transition to “data-driven,” make sure you are asking yourself: Where are we right now? Are we learning how to crawl? Is it time to start walking? Or are we truly ready to run at this point? When you can accurately answer these questions, you can then position yourself in making the best data science hire for your company.