Published on 08-Jan-2013
"For a 2,500-chain store, like one of our largest clients, you're talking about having to calculate 15 billion forecasts within a couple of hours. We have to basically crunch through a lot of analytics in a very short period of time. " - Brian Stankovic, vice president of business development, Market6
PureData System for Analytics (powered by Netezza technology), PureSystems, Big Data, Data Warehouse
A predictive-analytics solution provider in the United States increases processing speed, improves forecasting processes and gains the ability to offer its customers the analytics capabilities they need to enhance inventory management, drive sales growth and improve customer retention, when it implements an IBM PureData System for Analytics solution to perform complex analytics quickly.
With the retail industry experiencing a significant blurring of channels, Market6, Inc. recognized that more and more companies needed ways to understand and use the increasing amount of data being generated to remain competitive. Market6 wanted to help its customers effectively capture and manage their information to determine what products to keep stocked and predict how much of a specific product to purchase; optimizing the flow of inventory is a critical factor in better managing inventory, controlling costs and avoiding waste.
Market6 implemented an IBM PureData System for Analytics solution, which is powered by IBM Netezza Analytics technology, to house and process more than 100 TB of data. The client uses the platform to operate its information services, so that retailers and manufacturer customers can view the same information at the same time. Further, Market6 uses the platform to power its customer-demand-forecasting model, which provides its customers with detailed reports to predict the optimal level of inventory.
By implementing an IBM PureData System for Analytics solution, Market6 gained the ability to provide its retail customers the information they need to increase competitiveness, improve customer retention and drive sales growth. The IBM Netezza Analytics technology's extremely fast processing speed, storage capabilities and efficient input/output (I/O) flows help the client improve forecasting and execution of data workloads. Integrating information from predictive and operational analytics will provide the client's customers with the ability to execute business decisions even faster.
To provide better logistics for its manufacturing customers, Market6 had to draw better insight out of 100 terabytes of data. Turning to the IBM PureData System for its data processing rigor, Market6 was able to bring together operational analytics and unstructured social media data to improve the digital path for retailers and manufacturers.
Brian Stankovic – VP of Business Development – Market6 Inc.
Market6 is a company that enables both retailers and manufacturers of consumer package goods to prevent out of stocks on shelves by incorporating predictive analytics in with their data sets.
It’s critical to have product on shelf and historically the way that stores and retailers handle that was ordering too much product and then selling through it eventually. Well, you can’t do that with perishable product. An inventory is very expensive to hold any today.
A company can go ahead and take a look at the forecast against the inventory positions to be in a better position especially when those critical targeted promotions come up.
Systems like PureSystems being able to enable the processing and the storage of all that data that you need to execute against something like that is critical and is going to become more important in the future especially when you start overlaying everything coming in from social media and the Internet.
Think about the 100 plus terabytes that we process and store. You know, it is basically impractical to to crunch through that volume of data information on a daily basis.
We started using the Netezza system so that has enabled that fast processing, the storage of the information, the input, output flow through that we need in order to basically turn around significant number of forecast, retail execution alerts, work flows, planograms, information like that to be able to turn that around every single night.
We’ll be able to utilize the advanced capabilities of Puredata system for analytics will bring us by migrating the operational analytics that we do today with the social media and the other unstructured data to basically integrate those two together to kind of highlight the digital path to purchase for both retailers and manufacturers.
Products and services used
IBM products and services that were used in this case study.