April 2, 2013
Will Sears Succeed By Selling Faster Data Solutions to Others?
Okay, so Sears Holdings has been promoting its technological advances for some time, although it is hard to see how these have helped either Sears or Kmart in any substantive way. Fortunately, this is not an article to recount the company’s numerous retailing missteps over the years.
Last April, Sears Holdings announced it had created a wholly owned subsidiary, MetaScale, to offer data management and analytics via the cloud for large-scale enterprise projects.
As an Advertising Age article points out, at the core of MetaScale is Hadoop, a file system for companies "looking to transform traditional data operations to enable speedier access and analysis."
MetaScale is seen as a leader in the field and was chosen along with Netflix and Yahoo to run an educational track last June at the 2013 Hadoop Summit in San Jose.
Philip Shelley, CEO of MetaScale and also CTO at Sears, told Ad Age that the progression into data management for others was a natural for the company because it was "leading edge" when it came to the use of "big-data tools."
In an April 2012 RetailWire poll, respondents were evenly split on whether the creation of MetaScale was a good or bad move for Sears Holdings.
BrainTrust
Recent Discussions
Discussion Questions
Will other retailers trust MetaScale to help improve their management and analysis of data, or will the overall performance of Sears and Kmart affect their decision making? What technological or human advances are necessary for retailers to take the next big step with Big Data?
Poll
There are several skill sets needed to progress from data to improved business health. MetaScale appears to have the first sets in the sequence. Any retailer using their services needs to have skilled analysts, merchandisers and leaders in their own organization who can take the big data handoff and run with it. Sears and Kmart fumbled.
(Disclosure: I am engaged as a consultant by Teradata, which supplies Sears/Kmart with data warehouse and Big Data solutions) Given this disclosure, I’ll just address the second question.
To get real benefits from Big Data, retailers need to ensure that data and analytics are flowing to and from the point of customer interaction and the point of supplier interaction seamlessly and in real time. Easy, especially at retail! Of course, a lot of variables come into play with the flow of information—mistakes and inaccurate data, timing and scalability issues, execution problems on both ends and the always fickle shopper.
A few low hanging Big Data analytics fruit for retailers include activities like digital marketing optimization, fraud detection and prevention and social network and relationship analysis. From there, retailers can look at iterative, on-the-fly data exploration and analysis to rapidly uncover new and changing shopping patterns. The Holy Grail for Big Data analytics is knowing what the shopper will buy next and not only having it when and where she wants it, but being able to sell her a few extra profitable items along with it, all the while making her feel like she’s getting a bargain.
Sears and Kmart are continually searching for a life raft. I do not think this is it. This is not going to bring more customers to the checkout line. How could the mighty have fallen so far that they have become the last resort?
Depending on the retailer’s needs and issues, going forward with a big data project can be simple to complex. The key question is are they going to use a platform designed for dealing with retail big data or create one themselves?
There are many solutions to some core retail issues that leverage big data. Some that I know very well use the the most advanced in-memory processing techniques AND leverage the Hadoop attributes. No matter the technology, the retailers need to truly know the focus of their project and leverage the best solution to address the project. Big data is used when the best answer and tight project control is critical. It is not a space to cut corners and the ROI that I have seen retailers making with retail big data solutions is proof of this. Put the investment in the right place and stay focused, and the pay back is huge.
Go big..leverage the data!
Tom…hoping to soon use Hadoop for my phone directory….
Nothing is going to fix Sears and Kmart. Why do we seem to expect this to happen? The owner isn’t even trying to fix them and everybody in the industry knows it. These are dead retailers and the only reason they exist is for their real estate.
If MetaScale provides a resource for handling Big Data, then it will be successful. The spin-off makes perfect sense. It maximizes the value of the asset. Sears Holdings should be selling any assets that provide value.
When I first read this discussion question I was looking for the April Fools ending. First no one has the best or only transaction analysis tool. This world is still evolving as the data improves in quality and informational content.
Second, why any other retailer would buy anything but leftover merchandise from such a poor excuse for a retailer is baffling. How many quarters of declining sales does one need to say the end is near?
This attempt is not new. Some years ago A&P was selling its software and only the Military Exchanges purchased. Only our government purchases old ideas as new.
“…it is hard to see how these have helped either Sears or Kmart in any substantive way…”
The scary thought, of course is that it HAS helped them (i.e. they would be performing even worse without it). But in answer to the question, I think that if (other) retailers are evaluating competing providers, and determine MS is the best choice, the pedigree is unimportant.(Relatively speaking…I’m sure someone in the approval chain will say “Sears?!”) OTOH, if a MS salesperson approaches someone unsolicited, the discussion will be a short one.
Of interest to me is the fact that MetaScale has attained leadership status and yet their owner is far from a leader. This is an area—analytics—that when applied correctly can change the field. If they haven’t been able to do this for Sears, how did they become a leader? And with that said, how then will they be a life raft for Sears? I don’t get it!
Human advances are more about an organizational commitment to using the data to transform the customer experience. The best way a company can advance with Big Data is by using its insights for the purpose of being customer committed. Customer-committed organizations use a careful balance of data and innovation to design an experience that is meaningful.
This level of intimacy is ultimately accomplished through a practice we call Enterprise Loyalty, which is the sharing of consumer data beyond the marketing department so that every part of a company can benefit from the insights, from merchandising to pricing to store planning. By doing this, everyone can align their priorities against high-value, high-potential customers, identify the critical customer encounters that define the brand’s unique value, and change their activities with the express purpose of better serving those customers.
On the technology side, it’s about finding the right tools to support the decision-making process and activating meaningful change management against this. The tools exist but the commitment does not yet.
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There are several skill sets needed to progress from data to improved business health. MetaScale appears to have the first sets in the sequence. Any retailer using their services needs to have skilled analysts, merchandisers and leaders in their own organization who can take the big data handoff and run with it. Sears and Kmart fumbled.
(Disclosure: I am engaged as a consultant by Teradata, which supplies Sears/Kmart with data warehouse and Big Data solutions) Given this disclosure, I’ll just address the second question.
To get real benefits from Big Data, retailers need to ensure that data and analytics are flowing to and from the point of customer interaction and the point of supplier interaction seamlessly and in real time. Easy, especially at retail! Of course, a lot of variables come into play with the flow of information—mistakes and inaccurate data, timing and scalability issues, execution problems on both ends and the always fickle shopper.
A few low hanging Big Data analytics fruit for retailers include activities like digital marketing optimization, fraud detection and prevention and social network and relationship analysis. From there, retailers can look at iterative, on-the-fly data exploration and analysis to rapidly uncover new and changing shopping patterns. The Holy Grail for Big Data analytics is knowing what the shopper will buy next and not only having it when and where she wants it, but being able to sell her a few extra profitable items along with it, all the while making her feel like she’s getting a bargain.
Sears and Kmart are continually searching for a life raft. I do not think this is it. This is not going to bring more customers to the checkout line. How could the mighty have fallen so far that they have become the last resort?
Depending on the retailer’s needs and issues, going forward with a big data project can be simple to complex. The key question is are they going to use a platform designed for dealing with retail big data or create one themselves?
There are many solutions to some core retail issues that leverage big data. Some that I know very well use the the most advanced in-memory processing techniques AND leverage the Hadoop attributes. No matter the technology, the retailers need to truly know the focus of their project and leverage the best solution to address the project. Big data is used when the best answer and tight project control is critical. It is not a space to cut corners and the ROI that I have seen retailers making with retail big data solutions is proof of this. Put the investment in the right place and stay focused, and the pay back is huge.
Go big..leverage the data!
Tom…hoping to soon use Hadoop for my phone directory….
Nothing is going to fix Sears and Kmart. Why do we seem to expect this to happen? The owner isn’t even trying to fix them and everybody in the industry knows it. These are dead retailers and the only reason they exist is for their real estate.
If MetaScale provides a resource for handling Big Data, then it will be successful. The spin-off makes perfect sense. It maximizes the value of the asset. Sears Holdings should be selling any assets that provide value.
When I first read this discussion question I was looking for the April Fools ending. First no one has the best or only transaction analysis tool. This world is still evolving as the data improves in quality and informational content.
Second, why any other retailer would buy anything but leftover merchandise from such a poor excuse for a retailer is baffling. How many quarters of declining sales does one need to say the end is near?
This attempt is not new. Some years ago A&P was selling its software and only the Military Exchanges purchased. Only our government purchases old ideas as new.
“…it is hard to see how these have helped either Sears or Kmart in any substantive way…”
The scary thought, of course is that it HAS helped them (i.e. they would be performing even worse without it). But in answer to the question, I think that if (other) retailers are evaluating competing providers, and determine MS is the best choice, the pedigree is unimportant.(Relatively speaking…I’m sure someone in the approval chain will say “Sears?!”) OTOH, if a MS salesperson approaches someone unsolicited, the discussion will be a short one.
Of interest to me is the fact that MetaScale has attained leadership status and yet their owner is far from a leader. This is an area—analytics—that when applied correctly can change the field. If they haven’t been able to do this for Sears, how did they become a leader? And with that said, how then will they be a life raft for Sears? I don’t get it!
Human advances are more about an organizational commitment to using the data to transform the customer experience. The best way a company can advance with Big Data is by using its insights for the purpose of being customer committed. Customer-committed organizations use a careful balance of data and innovation to design an experience that is meaningful.
This level of intimacy is ultimately accomplished through a practice we call Enterprise Loyalty, which is the sharing of consumer data beyond the marketing department so that every part of a company can benefit from the insights, from merchandising to pricing to store planning. By doing this, everyone can align their priorities against high-value, high-potential customers, identify the critical customer encounters that define the brand’s unique value, and change their activities with the express purpose of better serving those customers.
On the technology side, it’s about finding the right tools to support the decision-making process and activating meaningful change management against this. The tools exist but the commitment does not yet.