Retail: Lessons Learned from the First Data-Driven Business and Future Directions

Executive Summit
Location: Mission City B1
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(1.73, 11 ratings)

This presentation is part of the "Executive Summit":

Retailers and their suppliers are the most aggressive civilian users of analytics and data science in the world. Their roots run deep: evolving from internal paper inventory records to mainframe EDI networks, to EDI over the internet, to RFID, to multinational collaborative forecasting, to real time inventory decisions based on weather forecasts. Retail’s exponential data growth, its past success with analytics, and the relentless competition by its suppliers for shelf space as well as its own for consumer attention, ensures that the retail industry will continue to drive much of the innovation in the data science space.

The introduction of what many of us now consider “mainstream” devices, processes, and practices—such as VPNs, RFID, environmental sensors, location tracking, real time logistics and supply chain management—were driven by the needs of the retail sector. Why is retail at the forefront of the data capture, management, and analysis movement? The answer is quite simple. Retail is one of the most data rich industries with some of the smallest margins.

No retailer or supplier can survive without being able to track, analyze, and predict the effects of the 4 Ps—Price, Product, Place, and Promotion—across their entire business. Now, with new issues such as track and trace, brand protection, cold chain management, and stricter government regulations across the globe, their ability to execute on the 4Ps becomes far more complicated. In retail, data science excellence is a pre-requisite for survival.

The scope of this problem is large and growing at an exponential rate: a domestic mid-size manufacturer will produce on average 655 billion data points a year. Consider how much data must be tracked by a large retailer who deals with thousands of manufacturers. It’s easy to understand why Wal-Mart is broadly considered to have the largest civilian data warehouse in the world. And with the addition of loyalty data and robust e-commerce channels, the amount of data and associated challenges continues to grow.

The retail industry, with its extensive use of data, has also been at the forefront of dealing with new challenges, such as the myriad of cultural and privacy issues that accompanies any accumulation of data this large. It also continues to struggle with the issue of collaboration and sharing of data: when does it make sense and when is it a threat to overall business? Moving forward, these challenges need to be addressed.

Where is retail heading? There are a number of trends coming into play:

  • Barriers to widespread adoption are disappearing. More cost effective and ROI conscious technology solutions, a laser-like focus on analytics as both a science and a business enabler, as well as the increasing availability of analytics expertise ensures an even more aggressive data science approach by companies of all sizes. Well known giants like Wal-Mart will no longer be the only data science “players” in the retail sector.
  • New approaches make all data more valuable. More data and data sources are driving advances in real time track and trace, forecasting, in store behavior tracking, and RFID “usefulness.”
  • Mobile devices will cause a major upheaval for traditional aggregators like AC Neilsen. These devices will reshape how we all “do our jobs” and the disintermediation effect of this technology will impact traditional data aggregators.

These trends, in turn, will change the very landscape in which retail does business. What does a more “perfect market” mean for retailers and manufacturers when improved logistics and more consumer information come into play? What happens when consumers can compare prices immediately on their mobile phones and order from the cheapest source? What effect will companies like Amazon, who offer sophisticated logistics and marketing services to tiny companies which enables them to operate as their much larger counterparts, have on the retail landscape? How will being able to access the opinions of thousands in real time on a particular product or a particular store affect what consumers buy? Will retail consolidation continue and how will data science affect the outcome?

The Internet has completely changed the game for brick and mortar businesses of all sizes. Advances in data science will do the same, impacting not only the retail sector but the lives of consumers everywhere.

Marilyn Craig


Marilyn Craig, the Senior Director of Worldwide Sales & Marketing Planning and Analysis at Logitech, has a wealth of in-depth, real world experience in retail channels and consumer insights, particularly in the use of analytics to drive sales, with over 16 years of experience in both traditional marketing, market research, and business development for some of the most well-known brands in the world, including Logitech, Hewlett-Packard, and Intuit.
At Logitech, Marilyn is building a worldwide team to own and manage the advanced analytics, long-term planning, and enabling processes and tools for both the sales and marketing organizations. At Intuit, Marilyn’s go-to-market and retail channel strategies for Intuit’s Quickbooks’ product line resulted in revenue growth from $110 to $140 million. At Hewlett-Packard, Marilyn designed and developed the retail channel information system—the first of its kind in CES, including reporting and analysis capabilities—for its multi-billion printer business.

Prior to Logitech, Marilyn was a founding member and Chief Analyst of PatternBuilders, which provides an advanced technology platform suitable for analyzing and forecasting the vast amounts of data available to 21st enterprises. While there, Marilyn helped PatternBuilders’ customers in multiple industries use the platform to improve their operations and profitability with advanced analytics.

Throughout her career, Marilyn has been at the forefront of the techniques and systems used to capture market data as well as the application of sophisticated analytics to that data to produce actionable information. Marilyn received a Bachelor of Arts degree from the University of Texas at Austin with honors and has an M.B.A. from the University of California at Berkeley.

Photo of Terence Craig

Terence Craig


Terence Craig is CEO and CTO of PatternBuilders, a big data analytics companies that produces advanced applications for financial services, retail and other data intensive industries.

Terence has an extensive background in building, implementing, and selling analytically-driven enterprise applications across such diverse domains as enterprise resource planning (ERP), retail sales channel optimization, professional services automation (PSA), and semi-conductor process control and analytics in both public and private companies. He has been part of the ERP/SCM industry as it has evolved, from the VAX and HP 3000 to its current heyday of client-server, GUIs, and relational databases and is looking forward to exploring what the next generation of solutions, powered by the Internet of Things and big data analytics, will look like.

With over 20 years of experience in both executive and technical management roles with leading-edge private and public technology companies, Terence brings a unique and innovative view of what is needed—from both an operational and technology perspective—to build a world class analytics platform that is focused on the innovative development of analytic applications designed to improve companies’ and organizations’ profitability and efficiencies. He is also a speaker, blogger (on all things big data and analytics plus lots of other stuff), and author of Privacy and Big Data.

Comments on this page are now closed.


Picture of Mary Ludloff
Mary Ludloff
02/24/2011 10:59am PST

Since we are an analytics company, we feel the need to make a statistical observation on our presentation rating: we received just 11 ratings out of what we were told was a 200+ audience which is not a great sample set. That being said, we take ratings to heart because we like to incorporate feedback into what we do in terms of presentation topic, depth, and coverage. However, outside of the rating itself there was no other feedback given. Other feedback we received after our session was positive, including a blog post review from Strata attendee, Ted Leung, as well as a positive comment (above this one) and even a request for our slide deck. Hopefully, most of the attendees had a similar impression as Ted’s. If not, we would appreciate any comments regarding what we could do better!

Picture of Terence Craig
Terence Craig
02/15/2011 3:26am PST

Hiroshi – thanks for the kind words. Please rate the presentation as well – postive feedback like yours helps O’reilly set the agenda for future shows.

Regarding the slides – I sent a question to O’reilly on whether we can share them directly with you. We would also need your contact info. Send me an email terence(at) patternbuilders . com and I will do my best to get you a copy.

02/12/2011 11:21am PST

it’s a great presentation.I got a lot of insights. Would it be possible to obtain the slide used for the presentation?


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