Earlier this month, Forrester Research published a report on the scarcity of skilled marketing scientists, or those in the role of “converting ever-increasing amounts of customer data into more profitable customer relationships.” According to the report:
McKinsey projects a shortage of at least 140,000 “deep analytic talent positions” plus a deficiency of 1.5 million analysts and analytics managers by 2018.
As an industry reliant on customer centricity, this certainly poses a problem for retail. Now, more than ever, retailers have an increased need to understand their customers – where, why and how they shop – in order to create more effective marketing programs that are tailored to each individual shopper’s needs. Yet, 71 percent of marketing decisions today are made without applying analytics (source: The CMO Survey). It’s mindboggling to think that 71 percent of companies are flying blind when it comes to their marketing decisions.
And, as the report points out, not only do good marketing scientists need to have technical acumen, but the most productive are those who understand business and have strong communications skills in order to translate their data findings into knowledge that can be shared amongst their colleagues. To top it off, good marketing scientists know their worth and are demanding top dollar for their talent.
Top dollar AND their pick of industry and company. Because they are in such high demand, data scientists look for the “cool”, high profile jobs – you know, those with a sprawling campus, free food and other amazing perks. This is in no way a knock on retailers, but if you were a data scientist stud looking for a job and excited to change the world, would you accept an offer from Instagram/LinkedIn/the “next” Google…or would you choose to work for Boot Barn? If you loved retail that much, my guess is you might go to Amazon before anyone else.
But hiring is not the only problem. Even if you are lucky enough to snag a top-notch data scientist, you need to build an internal team around them – managers who can lead them (and recruit more), technical capabilities to support them, and engineering who can to turn science projects into production systems. It’s not as easy as hiring a scientist, giving them a Hadoop instance and watching the money roll in.
So what’s a retailer to do? Forrester recommends several options, including using fewer analytics techniques, and hiring multiple people to perform the tasks of one scientist. These don’t seem like very good options to me. Do less analytics? Or hire more, less qualified people to do highly complex work? Really?! Their final recommendation, however, makes more sense: contract for specialized analysis.
Why apply a do-it-yourself approach to such an important part of your business when there are companies like CQuotient (shameless self-promotion) that can do all of this for you. If the real challenge with big data is finding the right people with the right skills to make it a success, consider partnering with an organization that lives and breathes retail data. Not only do they understand how to harness the power of your data, they know how to act on it. Not only do they understand the underlying technology, they understand your business and what insights will be most impactful to your bottom line.
As McKinsey points out, this problem is only about to get worse in the years ahead – at the same time your shoppers are expecting more personalized experiences based on all that data you have on them. How will your retail organization rise to the challenge? Leave your comments below.