Are retailers organized for analytics?

Discussion
May 07, 2015

Through a special arrangement, presented here for discussion is an excerpt of a current article from Oracle Blogs.

Most business leaders now acknowledge the value of Big Data analytics. For many, the lens has shifted to the question, "What’s the business value to my organization and how do I get started?"

The majority of content at the Retail and Consumer Goods Analytics Summit in Chicago last week was about the discipline of data science. Sessions were designed to help retail and consumer goods companies understand how to organize for analytics.

To this end, data science leaders from Walmart and Macy’s were on the agenda. Well-funded and visionary companies are at the bleeding edge of leveraging multi-structured data to drive their businesses forward. Meanwhile, many attendees reported their organizations struggle with operational reporting issues.

There is urgency to act now with respect to analytics. Companies employing advanced analytics throughout their operations are proving every day their advantages over less insight-driven competitors. The challenge is acting with precision when you are just getting started. Embarking on a journey to becoming data driven isn’t easy, but the Summit offered recommendations on how to approach this imperative:

Are retailers ready for big data?

  • Understand what Big Data represents to your business. Rather than simply viewing Big Data as a chance to save on data storage costs, the real opportunity is in asking questions of your business that current capabilities cannot support — or in discovering questions you never considered.
  • Those in data science straddle the business and technology sides of their companies. One presentation suggested successful companies were establishing Centers of Excellence for Data Science.
  • Walmart Labs’ data science leader Esteban Arcaute said a bigger challenge than recruiting analytic talent is developing data driven managers. For suppliers to and competitors of Walmart and Macy’s, the situation can be intimidating. What’s needed is a precision effort around developing and applying data science to the highest impact use cases.
  • Identifying and recruiting business leaders who understand the value of analytics is critical. To approach this conversation, it’s helpful to align with the commercial execution of the business. For example, focus on the consumer’s journey, and all the actions that both retailers and suppliers take to influence this process apart and in collaboration with one another.
  • To extract the most value from data, it should be managed as a secure unit, and its value exposed appropriately to users throughout the analytic value chain; from those requiring access to daily sales reports to those mashing up multi-structured data to understand and improve a critical customer process.

 

How prepared today are most big retailers and suppliers to extract meaningful benefits from Big Data analytics? How would you recommend companies that are late to the game go about catching up?

Braintrust
"Retailers have been sitting on a gold mine of valuable shopper data for a long time and have not yet fully leveraged this asset and turned it into value on a consistent basis. Retailers need a consistent analytical process rather than one-off analytical projects."
"On a scale of one to 10 with 10 being fully prepared, I would say three. It’s early in the big data game so 98 percent of retailers are still trying to find their way. No one, NO ONE, has this 75 percent figured out and it’s a journey that will evolve over time."
"Data is free. Insights can be useful and inexpensive. Analytics combined with insights offer solutions — they are priceless. Retailers can look to several sources from which to catch up in quick fashion."

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12 Comments on "Are retailers organized for analytics?"


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Chris Petersen, PhD.
Guest
2 years 8 months ago

The problem with “big data” is, well, it’s BIG. It can be really HUGE.

Most retailer systems were not set up in size, scope or function to handle BIG data. Retail systems were set up to “count the beans,” manage inventory and manage distribution. Retail IT departments are typically underfunded and have challenges keeping up with the core fundamentals, especially if operations now involve both stores and online.

True analytics to extract intelligence require substantial infrastructure, systems, resources and talent, which are all in short supply in retail these days. A major success factor is that leadership must view big data as strategic, not operational.

The best place for retailers to start is to realize that it is not the DATA itself, but asking the questions that need to be answered. Retailers are already drowning in data, what they lack are insights and intelligence on consumers and what drives conversion — online and offline.

Graeme McVie
Guest
Graeme McVie
2 years 8 months ago

Retailers have been sitting on a gold mine of valuable shopper data for a long time and have not yet fully leveraged this asset and turned it into value on a consistent basis. Retailers need a consistent analytical process rather than one-off analytical projects. They also need mechanisms in place that interpret the analytic outputs and enable the decision-makers across the company to take concrete actions based upon the analytical insights.

Part of the challenge is that retailers need the analytical and technological capabilities and people to be able to perform the required analyses. They then need business-oriented people who can take the outputs and translate them into insights that can be leveraged by category managers, marketing managers, store managers and senior managers. And they need to tie the analytical outputs to definitive business decisions managers can execute on a day-to-day basis. The analytics and technology have been available for some time, but it is the changing management element that has prevented retailers from fully capitalizing on these essential and valuable capabilities.

Dr. Stephen Needel
Guest
2 years 8 months ago

I’m not sure anybody anywhere is really prepared to extract meaningful benefits from big data analyses. This is very new and I think we only know some of the basic questions to ask of the data. Those who want to catch up need people who are good at manipulating and querying the data, understand the business issues, not just the statistics, and need managers who are willing to consider the implications of the data.

Doug Garnett
Guest
2 years 8 months ago

I find that data science is like research: In order for it to have positive impact on a business, it’s most critical that management knows how to listen to the findings, challenge the findings and implement action based on what’s learned.

Right now companies are so absorbed in merely doing the “data science” that they aren’t yet rising above it to learn how to learn strategically from what’s found.

And if research usage is any indication, only one in four companies will sort this out. And that means we need to take care right now. As with erroneous use of traditional research, erroneous use of data science can just as easily destroy your efforts as build them.

A healthy skepticism continues to be needed in this realm.

Bill Davis
Guest
2 years 8 months ago

On a scale of one to 10 with 10 being fully prepared, I would say three. It’s early in the big data game so 98 percent of retailers are still trying to find their way. No one, NO ONE, has this 75 percent figured out and it’s a journey that will evolve over time. The biggest impediment is often data quality and that’s an issue that still impacts every organization whether they are willing to acknowledge it or not.

Start slow, focus on data quality and master data management and don’t try and do everything all at once as that will only slow things down. The high-end skill sets are challenging to find and more often that not retailers aren’t offering a competitive enough compensation package to attract them. Stay focused and and increment your capabilities as Rome wasn’t built in a day.

Naomi K. Shapiro
Guest
Naomi K. Shapiro
2 years 8 months ago

Retailers should approach big data analytics initiatives urgently — and wisely. There are many wonderful companies that can help you survive the “disruptive innovation” of ecommerce and the complicated, competitive marketplace, and, most important, the understanding of your data — as well as of your competitors.

These are mostly SaaS (Software as a Service) companies, who provide the software and savvy to help you wrangle and manage your pricing and merchandising data, and understand and act on it in the most effective (profitable) ways.

We listen to our clients, and have learned that they want these services (emphasis on services), and support (consultation), rather than wrestling with, or bringing in, outdated, unwieldy services.

Roger Saunders
Guest
2 years 8 months ago

Data is free. Insights can be useful and inexpensive. Analytics combined with insights offer solutions — they are priceless.

Retailers can look to several sources from which to catch up in quick fashion. First, check with you current vendors who supply insights and bring them in to discuss examples of how they can support your interest in analytics.

Second, look to universities in your area. A number of leading schools are setting up data science degree programs. They are eager to work with companies.

Third, ask your associations or the associations of your vendors to provide examples of analytics that can apply to your business.

No charge for these steps. It does take initiative to make a couple of telephone calls. Analytics does not represent some mysterious science. It is a step in supporting retailers needs to make better decisions, faster. Keep in mind, it’s not about Big Data. It’s about developing Smart Data from the insights you may already have in hand.

Shep Hyken
Guest
2 years 8 months ago

Analytics are what the big retailers do best. They have amazing stats and facts on what merchandise is moving, the demographic of who is buying, what’s trending and what’s not, and much more. The key is to know what analytic data is most important and useful. It’s easy to get caught up in too much data — much of which is interesting but really useless.

I can’t imagine that a company is late to the game of understanding basic analytic information. Even at a very low level, they can tell when items are selling or not. Still, sophisticated understanding gives retailers a leg up in understanding their customers and inventory management.

Vahe Katros
Guest
2 years 8 months ago

Benefits are the outcome of a set of steps. Let’s forget all the things you need to do with the hiring, the data, the software, the algorithms, even the analytics/data presentations … and lets get execution. That single step involves creativity and tradeoffs and it’s really the beginning of the process of extracting benefits.

It’s so easy to sit in front of a screen and click here and there, create new reports, talk about this and that and then get burnt by the costs of execution that the willingness to act becomes stifled. That’s part of the journey. That’s the intangible; it’s very human.

The best thing to do is start and start small — now (he said after being burnt). Build a solid base; don’t get too fancy. Modern systems can take analysis paralysis to a new level. Stop trying to find the needle in the haystack; try to move the needle and develop a method you can reproduce.

Gordon Arnold
Guest
2 years 8 months ago

The correct question is, exactly what does sorting through countless redundant files of any and all kinds of information do for you? There are mountain ranges of piled-high useless information technology systems that promised those that wasted their money every thing they needed.

Complex information systems designed and built for very specific tasks are paying back their investors every minute of every day. These same investors will gladly share with any and all willing to listen what their systems can do. In addition to insight and value for the hardware and software they use for success they might give you some advice as to what vaporware is and how to recognize it before you invest.

Any information that is available can be obtained for a price. If you not sure of the way to produce it without paying too much talk price with the ones that can and do for a living, be sure to take only what you can use or again you will pay too much.

Mihir Kittur
Guest
2 years 8 months ago

Most big retailers and suppliers are not really prepared. Some have recognized and have started taking steps in the right direction, but a majority of them don’t know how to get started.

Retailers will need to make a commitment to this from the top. They will need to invest in learning about the possibilities via success stories from other retailers and industries and figuring out possible applications and benefits to their business. They will need to prioritize problem areas where they would like to attempt to seek some of the benefits. The will need to invest the right talent and analytics partners to help them get to success sooner.

They will then have to take this across other problem areas across the organization and continue to invest in learning, testing, deploying the benefits of Big Data analytics.

That being said, one must note that every test of a big data analytics engagement may not always meet expectations.

Arie Shpanya
Guest
2 years 8 months ago

Some larger retailers are ready, but the majority could use a little extra help. Competitive intelligence companies are helping retailers bridge the gap by taking raw data and presenting actionable insights.

Here’s an article for further reading on why big data is so important in retail and different ways retailers can use it.

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Braintrust
"Retailers have been sitting on a gold mine of valuable shopper data for a long time and have not yet fully leveraged this asset and turned it into value on a consistent basis. Retailers need a consistent analytical process rather than one-off analytical projects."
"On a scale of one to 10 with 10 being fully prepared, I would say three. It’s early in the big data game so 98 percent of retailers are still trying to find their way. No one, NO ONE, has this 75 percent figured out and it’s a journey that will evolve over time."
"Data is free. Insights can be useful and inexpensive. Analytics combined with insights offer solutions — they are priceless. Retailers can look to several sources from which to catch up in quick fashion."

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