by: Ken Kanara
“Rome wasn’t built in a day” is an adage attesting to the importance of time in building great things. The same is true when it comes to big data and advanced analytics, but if you actually talk to small business owners in the middle market, they feel like it’s too big of an undertaking. According to a report from Score.org, more than half of small business owners believe analytics are critical, but only 45% track the data. There is general consensus that they could probably drive better earnings and profitability, but it’s not the biggest opportunity in front of them. So why is this?
Donald Rumsfeld was famous for drawing the distinction between ‘known unknowns’ and ‘unknown unknowns’. In many ways big data and advanced analytics is full of the latter for most business leaders. We constantly hear people use buzz words like “AI” or “machine learning”, but are afraid to ask what they are talking about. On some level, we know the biggest companies in the world are using technology to grow. On another level, we don’t even understand what questions we should be asking. For example, did you know there are 4 basic types of data analytics…and you’re probably doing some of this already:
- Descriptive: What’s happening in my business?
- Diagnostic: Why is it happening?
- Predictive: What’s likely to happen?
- Prescriptive: What should I do?
The reason I defined those topics is because I often hear about companies that want to “do advanced analytics and AI”, but don’t truly understand what they are asking for. The good news is you can educate yourself, and take it slow. Start with descriptive analytics and tracking your data in a disciplined and consistent manner. Then, try to visualize the data so you can run basic diagnostics and understand why certain things are happening. Crawl, walk, run…but understand there are a lot of unknown unknowns you need to conquer along the way.
If you want to leverage data and develop an advanced analytics capability, it does require a significant financial investment. There are a few components to this, but in the most basic terms, you’re talking about people, process, and technology. The good news is most of the technological capabilities required have been developed and can be used ‘out of the box’. They range from basic tabular structures like Microsoft Excel to real-time business intelligence solutions like Google Looker. There are a range of options, with an even wider range of price tags.
If the technology is out there, why aren’t all companies using it to automate their business, so CEOs can spend time on their yachts? Like most things in life, it’s not that simple. For example, salesforce has revolutionized the CRM industry, but if you’re like most companies using the product, the biggest issue is compliance not technology. Meaning you have the right tech stack, but lack the processes required to make it valuable for your organization. The same is true for most companies venturing in to big data and advanced analytics. (Again, crawl, walk, run)
If you don’t know what you want to do, or how you’re going to do it, how could you possibly hire the right people to do it? This is a mistake I see over and over with medium and even large size companies. The story goes like this…
- The board meets and decides “we need to build an advanced analytics capability” or “we need to invest in big data”
- The CEO hires someone to lead this, but she doesn’t even quite understand what the broader business objectives look like
- An ambitious, mid-senior level exec is hired and immediately asks for budget to develop the team, processes, and technology
- There is no budget for this initiative and 12 months later everyone agrees “we did what we could, but this isn’t the biggest opportunity in front of us”
If that’s how things fail, what can you do to not share the story above? I’ve seen things work best when a CEO hires a former management consultant, usually from McKinsey, Bain or BCG, to develop a basic data capability around a certain function. Once they have proven the ROI, they expand outwards from descriptive analytics to predictive and prescriptive. The reason this works well is because you’re starting small, but consultants also have the ability to look at the business more holistically, and understand where analytics is and isn’t valuable. Once the value proposition is clear for that particular function, the CEO can have this person hire others across the business to do a similar thing (and the original hire usually leads those individuals).
It’s a great way to slowly build your Roman….I mean Data Empire (but not in a day)!
Ken Kanara is the CEO & President of ECA Partners. He specializes in working with middle market private equity portfolio businesses on their most strategic hires, including CEO and CFO roles.