NRF: Why Are Retailers Still Complaining About Big Data?

We hear the complaints about all the data that is now being captured from TLogs in the store and online leading to "a plethora of data but a dearth of wisdom." After walking the floor at NRF, I am confused why anyone would say this. I was amazed at the number of BI (business intelligence) vendors ready to help retailers cope with the volume of data they are collecting. Representatives from Teradata, Aldata, 1010data, and Micro Strategies were among the ones I saw or spoke with about this complaint. Further, ARTS (The Association for Retail Technology Standards) has created an RFP for BI solutions that describes the features necessary in a solution. Yet the complaint persists. I have come to the conclusion that there are plenty of viable solutions; the challenge for retailers is knowing what to want from the data.
BI tools open a whole new opportunity for gauging business performance. More importantly, new message-oriented interfaces make it possible to provide real or near-real time performance information for store operations. This combination of detail and timeliness makes it possible to provide feedback while there is still time to correct a bad situation. For example, knowing that sales on a promoted item have stopped is a sure way to warn people in the store that the shelf is empty. On the other hand, seeing that an item has higher sales than expected may lead to a special offer on another size of the same product. Targeted markdowns by store allow control of individual store inventories based on actual sales so that overstocks and returns are minimized. TPIs (tactical performance indicators) can be developed from the data that are focused on job performance and provide employees feedback on their efforts. TPIs also highlight the advantage of equipment upgrades or an improved business process.
The use of BI to evaluate consumer behavior, however, is still more art than science. But even here the retailer is striving for only three possibilities: the consumer buys a higher gross item; the consumer shops a department they have not previously shopped; or the consumer buys more of an item they are already using. Switching the consumer to a different item based on BI clearly depends on the category; few people will switch to private label cigarettes, for instance. But the BI tools should be able to tell in which categories the consumer buys multiple brands and enable the retailer to suggest better items.
The propagation of BI solutions raises another question: who really should be influencing consumer item selection; the brand product manager or the retailer? Retailers would naturally want to shift their customers to the higher gross private label items — probably not what the brand manager wants.
Discussion Questions: With tools apparently available, why are retailers still complaining about the difficulty in extracting wisdom from Big Data? Do retailers know what they want from the data? How are you seeing BI tools changing the influence of brands at retail?
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23 Comments on "NRF: Why Are Retailers Still Complaining About Big Data?"
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Having supplied brands and retailers with recommendations and guidance based upon quantitative data and analytics, I’ve found that they are drawn to the absolute nature of data but often lack the commitment and cultural collaboration to respond to what the data is telling them. People want ‘actionable data’ but seem to be reticent to actually respond to the required action that the insights are suggesting. The insights often require a cross-functional (departmental) response and that becomes difficult to actually execute.
There is certainly an interest to value data and BI that supports an existing agenda or initiative, but when the insights suggest a different compass heading, the head winds that would be encountered to facilitate a change are often too difficult to overcome. Retailers tend to be focused on operational issues and look for the ‘quick fix’ on existing processes and workflows rather than designing innovative (and often disrupting) strategies based upon quantitative data and customer/business intelligence.
We are not in the business of generating or selling data. We are in the business of helping people figure out what to do with data — and that does not mean “tools.”
Bill hits the nail on the head. Databases are like dungeons. If you don’t know what you are looking for before you go in there and don’t have a torch to light your way, you will never come out.
Data mining and needing a true use for the information, let alone knowing how to use the information, are the key issues. At the heart of all of this is that retailers are capturing data, but truly have no use for much of the information. Data mining is a solution looking for a problem. Retailers KNOW that they have to prevent OOSs, give better customer service, and keep their stores clean, clear and easy to navigate for their customers. Training their staff, and maintaining low prices are the other side of the coin (sometimes). However, these key basics are still not addressed enough, let alone what to do with the data that their POS system captures every minute of every day. The expertise at retail is the customer’s retail experience, NOT how to mine data to squeeze every bit of information about a particular product, category or time period. This is why Data Mining and use of this information continues to be ignored….
The powers that be in retail intuitively want big data and all that it brings. However, the reality is that they can’t execute against it. It tells them that the way they have been operating (from their gut) for decades is wrong. Big data is going to tell them to change the way they address customer acquisition, the way they handle inventory and the way they project their sales.
The challenge is not to collect data (retailers have plenty of data to mine) nor even to find a software to make sense of it. Retailers must work in partnership with their software vendors to go beyond a laundry list of features and benefits and produce the reports that really matter to them. What matters the most to retailers is neither the quantity of data nor the software features, but the access to actionable reports that retailers could use as coaching tools. Very few software vendors actually take their clients from viewing to doing.
Big data tend to be anecdotal talking points among people who are not in the trenches. After doing some work in the trenches in retail, I realize that “small data” is very important.
I believe many BI companies are trying to bring slow corporate BI practices to fluid environments such as retailing. Retailers are complaining because KPIs and dashboards do nothing for them when the weather forecast is predicting rain for the next several days.
Retailing needs real-time data in small chunks at all levels, not past 12 year forecasts and trends. I would argue from my experience, retailers need more “predictive” data that can monitor real-time data and detect and respond to patterns in real time.
Bill: Great insights, and I think you hit the nail on the head: retailers are complaining about big data because they don’t know what they want from it. Big data won’t help you if you don’t have a strategy already.
The other problem is the age-old “in-house” syndrome. Too many retailers want to manage these massive data sets internally, when they are clearly beyond internal capabilities.
Big data is clearly the future of successful retail, but effective use will require new skills, a willingness to outsource, and a clear strategy.
Okay, I sort of think we’re missing the point. The value of “big data” is getting actionable insights at a granular level QUICKLY into the hands of decision-makers (NOT score-keepers). That has never been possible before. Moore’s law, wide data pipes to stores, and mobility has helped make that possible.
So what retailers need may be the same, but the speed at which they can get it has changed – dramatically. That’s what big data is all about. It’s a short-cut for “actionable insights at granular levels delivered in near-real time into the hands of decision-makers.”
That’s a very new story, not an old one at all.
Retailers who complain about the challenges in translating data into actionable insights are simply not prioritizing. It’s now easier and less expensive than ever to manage Big Data but retailers consistently under invest and shift priorities.
That said, it’s still not easy as it takes people, tools and discipline that is generally not resident within most retail organizations. The good news is that this is changing and every day we see more retailers investing in this area. Whether it’s through an innovation group or marketing or even IT, it’s happening and will continue to happen at better retail organizations.
It’s very clear if you read the quarterly earnings reports and listen to the conference calls, the retailers that understand Big Data and focus on customers, best exemplified by Amazon, are the ones that are thriving and putting the others out of business.
Across industries, executives are swamped with data. Many companies extract the needed information. The big problem is the look and feel of what is reported. It’s up to the buyer and user to determine what they need and how best to report it for action. Accepting the typical template and dashboard can lead to feeling bombarded rather than supported. Business intelligence can only be activated when those examining it can easily determine what they need to know. A little up front planning as to how to organize and show the output can make the difference between data and insights.
This one is simple. The grocery industry as a whole has inadequately invested in systems and personnel since the first round of scanners hit stores. Many are currently saddled with legacy systems that need to remain in place for purely financial reasons.
To make matters worse, we are now living through a period where a popular strategy is to delay capital investments. So, instead of moving into this decade’s opportunities to use new technologies in more forward looking applications, many companies are content to wait just a bit longer. Heck, we don’t even really forecast in this industry — we scenario plan. Not too many math research degrees in the halls of grocery companies.
The answer is simple, but execution is always the challenge. In order to leverage the data and transform it into something actionable, a retailer needs to do one of two things: 1. Hire the skilled personnel who understand the business and the tools needed to extract actionable information, or 2. Hire a partner who can do the same.
The problem is that the data so far outweighs intuition and ‘innate retail intelligence’ (i.e. gut) within retail orgs now that most people reading the data don’t know what to do with it. As in any research, there’s always a qualitative factor…why are the numbers saying that? What should I ask these numbers for? Etc. Who would know that now? The CEO that was a CFO?
Goes back to another retail dilemma; are we hiring the right people? Are we hiring too many scientists and too few merchants? I personally think, yes, the latter is true.
The article missed the point. What Teradata, Micro Strategy, etc, offer as analytics solutions have been around for some time. The advent of Big Data is also not new, albeit with a different name — item level data, RFID data etc., Application logs have been in existence for ages. The existing analytics apps as-they-are cannot address these volumes of data, their asynchronicity and demand for low latency.