Business Intelligence (BI) was first formalized in 1865, as an observer noted how a French banker was routinely gathering, analyzing, and acting on data before his competitors. While this may have been the first recorded observation, it’s hard to imagine humans discovering (or inventing, depending on your perspective) data for decision-making but a few decades ago.
Be that as it may, it wasn’t until IBM began popularizing the concept – to sell more hardware, no doubt – in the 1950’s that BI caught on. The early years were spent gathering digital data on new storage devices while the 80’s onward were focused on leveraging rapidly-advancing computing power to sift through the data. As a profession, data analysts started making their value known to the market in the 1990’s, with peak interest probably occurring around 2010 with the confluence of “Big Data”.
Since then larger companies have employed scores of analysts whose job it is to ask data questions in search of useful answers. Often times this means sorting through database tables and using interfaces that are extremely open ended. Here’s a picture of the query interface for Splunk, a product we use.
It should be obvious to any non-technical person that the query in the search window is less than ideal.
But the value of BI is almost entirely lost on brick and mortar. If you think that’s just hyperbole, let us prove you wrong.
First, merchants are generally apathetic about data. Leading point of sale (POS) providers, who supplied systems where arguably the most important data (i.e. transaction data) is stored, haven’t been forced to make data available, or useful, for merchants. Hell, these POS providers even went so far as to purge the data after a few weeks. Why? Because neither merchants nor the POS provider (who, by the way, are former merchants about 90% of the time) understood data to be valuable.
Second, even if merchants desire to nominally jump on the BI/Big Data bandwagon, they have an enormously difficult time attracting and retaining good talent. Imagine you were a quality engineer. Would you want to work at a firm that supports and appreciates engineering talent, or one where the executive team struggles to interpret a pie chart? Go look through the executive ranks of retailers and restaurants: your odds of finding someone at the senior levels with a technical background, or even someone with a high level of business acumen (think investment banking or consulting), is about the same as finding Bigfoot.
“Executives” in brick and mortar have worked their way up because many are simply unemployable in any other industry. 9 out of 10 restaurant managers began at the entry level, and 8 out of 10 restaurant owners started their careers in entry-level positions. In other words, there’s no inbound sophistication; the acumen needed to run a grill is not exactly what’s needed for strategic M&A is it.
Just apply this to your personal life. Would you want to hire someone who can’t make objective decisions? Someone who can’t respond to emails with professional decorum? Someone who believes that being the oldest person in the room means you’re the most qualified?
Lastly, and because of the second point above, there’s a lack of culture that trusts and operates on data. Even if someone (most likely an activist investor) convinced recalcitrant merchants to invest in BI, nearly none of them would take action on the output. They would spend material amounts of money on solutions and people only to end up at the same conclusion they have today:
I’m the oldest, so I know best!
Look at Pizza Hut if you’re still a denier. Even though Domino’s proved the value of consolidated POS data in 2008, Pizza Hut still doesn’t have a centralized POS system. Yes, a low-margin operator has had nine years to feel the industry leader continually kick it in the pants but still hasn’t rationalized the value of data.
This is why, absent radical change, BI is doomed in brick and mortar. In order for BI to succeed, you need three core truths:
- The data. Cloud POS is storing and making said data available, but a dismayingly large number of merchants don’t care and are still using old technology
- The people. Good engineers will ask good questions and know how to sort through the data to find answers. Downplaying the importance of data does no favors in attracting good people.
- The culture. Leadership needs to trust and embrace data for decisions. The industry needs to change from mediocrity to meritocracy.
We would venture that 99% of merchants using BI solutions today are wasting their money. It’s not the fault of the solution providers but the operators; a failure across all three of the BI core truths means you have unqualified people looking at crappy data only to present it to leaders who just want to get their shareholders off their backs so they can make their next round of golf.
Data tools are only as useful as the user’s ability to ask intelligence questions and synthesize actions. In brick and mortar, that has proven to be asking too much.