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:
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, 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.
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.
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