Wednesday Nov 04, 2015

Collaboration, Creativity and Contribution: Observed Characteristics of a Successful Category Management Strategy

Author: Amber Trendell, Director of Retail Marketing, Oracle 

The Annual Category Management Conference had a strong underlying thread that weaved all of the sessions together this year and that was the demonstrable upside when retailers and suppliers collaborate. And that collaboration starts with data. Lots and lots of data. From consumer insights to store transactions, category managers have one thing in abundance and that is information. On the flip side, category managers on both sides of the fence are stretched super thin as they attempt to create compelling, localized assortments that are varied enough to make consumers feel they have the best selection and targeted enough to maximize space and revenue. 

So how are category managers successfully transitioning from tactical to strategic and delivering wins for their business? I heard three primary messages at the event this fall: Collaboration is key, Creativity is not a luxury but a necessity, and with the right strategy and tools you can clearly demonstrate Contribution to the business. Here's some additional detail:

Collaboration: when retailers and suppliers work together to identify upside and define a collaborative strategy the results can be phenomenal. Take the case study presented by Wawa and Redbull. Redbull knew empirically that Wawa lagged behind its competitors in the energy drink category and based on their projections demand for the product is on a steady climb well into the future. By working together to define a strategic goal of making Wawa the destination for energy drinks the C-store not only took the leadership role in the category but enjoyed double-digit organic growth. If we extend this concept of collaboration further to include technology and data science-as-a-service there is far more upside to be captured. Learn more about leveraging Science to Drive Profit and Differentiation in Grocery Retail here.

Creativity: it's likely safe to say that virtually everyone in retail knows that the impact of eCommerce on stores is really only in its infancy. If stores become an experience destination and media becomes the new eCommerce vehicle as predicted by Doug Stephens in his keynote session, how will category managers for products that may not translate as exciting or engaging ride the wave of store as experience destination? The answer is creativity and that is not something you can aggregate, pivot and deliver a report on. You need time to think and interact and actually go out into the field and experience your stores. So where is the time going to come from? By transitioning space optimization, consumer decision trees and demand transference analysis to a partner like Oracle you can effectively get out of the business of data crunching and into the business of experience orchestration.

Contribution: understanding the future of retail and how to capitalize (or just stay relevant) is important but where the rubber meets the road is in your ability to demonstrate lift and value to the business today. Oracle Retail has thoughtfully designed its planning and optimization solutions to align with varying degrees of business maturity particularly in respect to retail science and cloud applications. Whether you're just getting started or are ready to apply advanced retail science to your data, we have options.

Download the recent Oracle OpenWorld presentation on our planning solutions from retail expert Marc Koehler: Planning: Consumer Inspired Assortments

Monday Jul 20, 2015

Unlocking the Secrets of Big Data with Science

Buzzwords abound in the tech world, and mobile, social, big data, and cloud are the four horsemen.  Of those I think big data is least understood, but possibly the most powerful as exemplified by my favorite quote:

“Data is the new oil; analytics the new refinery.” -- unknown

The retail industry has always been dealing with large volumes of data; it's just that now the velocity and variety have dramatically increased. So the problem for retailers is two fold: first, how do they convert all that data into meaningful information? And second, how do they make the information relevant and actionable to employees?

Oracle Retail's answer comes in two families of cloud services: Oracle Retail Advanced Science and Oracle Retail Insights.  Continuing our momentum in delivering cloud services, these products simplify implementations allowing retailers to realize value faster and with less IT effort.

Oracle Retail Advanced Science Engine

We have a long history of employing data scientists that cull through donated data to find useful insights that can be productized in algorithms.  Over the years we've led the industry in areas like demand forecasting, markdown optimization, and localized assortments.  To make it easier to bring new algorithms to market, we've built our Advanced Science Engine, a platform tuned for analyzing data at scale and exporting the results.  Over the past six months, we've adjusted the architecture to provide this in a cloud deployment.  The specific science being offered is packaged into three separate cloud services:

Advanced Clustering

This solution provides insight into how store clustering best benefits the business.  It helps to answer questions such as:

  • What categories or merchandise classifications benefit most from clustering?
  • At what level of product or location hierarchy should clusters be created?
  • What product/location attributes should be leveraged?

The solution automatically selects the best clustering method depending on the clustering approach selected, and allows for what-if scenarios that help explore the data.  Is scores clustering approaches for comparison, and recommend the optimal number of clusters.  This fosters consumer-centric assortments that ultimately increase sales.

Customer Decision Trees & Demand Transference

CDTs map the decision process made by shoppers to purchase items.  They help a retailer understand if they have the right variety of sizes, flavors, colors, etc. in their assortment.

Suppliers often provide consumer decision trees that help retailers understand the impact to assortment decisions based on "generic" consumers.  But when a consumer is identified, they become a customer.  Our solution focuses on customer decision trees, which reflect the actual customers in your stores.  The solution even allows a side-by-side comparison of imported consumer decision trees alongside the calculated customer decision trees.

Using this science helps to reduce duplication in assortments, and prevent dropping unique items to which customers are attached.  Demand transference helps forecast if customers will switch to alternatives so that the number of variety of items offered can be optimized.  This solution often works closely with Category Management.

Assortment & Space Optimization

This solution helps to identify the optimal targeted assortment withing the space constraints.  It understands shelves, pegboards, and freezers and incorporates various business rules and visual merchandising standards.  The what-if analysis is very helpful in exploring options while seeking to maximize profits for any given space within the store or store cluster.

Integrated Planning

These cloud services can be used with existing planning products, or with Oracle Retail planning solutions such as Category Management Planning & Optimization, Macro Space Optimization, Retail Demand Forecasting, and Advanced Inventory Planning.

Tuesday Jun 23, 2015

Perspective from NRF Protect 2015: Adidas Uses Oracle Retail XBRi to Reduce Fraud at the Point of Service

Analytics and exception-based reporting, made available across all stores brings Big Data-style science to loss prevention

In advance of NRF Protect, here is a look at what some of our customers are doing to reduce and respond to fraud in stores. This is the first in a two-part series. To learn more, be sure to visit us at the Oracle Retail Booth #1227 at #NRFProtect this week in Long Beach, CA. 

Retail loss prevention professionals are well aware that employee theft and employee-related fraud account for the biggest single segment of shrink. According to the November 2014 Global Retail Theft Barometer, employee-generated shrink accounted for just over 40% of the previous year’s $128 billion total, even more than the one-third generated by shoplifting and organized retail crime.

Given these facts, retailers have a compelling interest in understanding and curtailing employee-generated shrink. The conundrum, however, is that no retailer can effectively investigate every single transaction in every single store. Fortunately, employees who commit fraud tend to follow specific patterns. By using tools that apply science to the problem, retailers can shift this challenge from a Big Data problem to an opportunity for insight.

One of the most important loss prevention tools is exception-based reporting, using advanced algorithms to constantly monitor point-of-service (POS) activity, identify potentially fraudulent transactions, and alert specialists automatically. Trends, outliers and “red flags” can be measured and tracked by region, store, or individual employee. By providing essential data to multiple levels of staff – from individual loss prevention specialists in the field to regional managers – an organization can effectively empower their team to root out fraud, and act quickly to resolve it. Doing the same thing manually is impossible when transactions multiply over dozens or thousands of locations. 

For adidas, the global designer and manufacturer of athletic shoes, clothing and accessories, it was nearly impossible to consistently identify the causes of shrink and fraud in its 2,470 stores worldwide. The company was unable to perform loss prevention exception reporting and faced operational challenges including lack of data protection, multi-system misalignment, difficulty adjusting to time zone and language variances, and system failures resulting in non-compliance issues.  In a recent Chain Store Age article, adidas shares how it reduces fraud in employee and administration losses following its implementation of Oracle solutions. Adidas shared their experience at Oracle Industry Connect. You can download the presentation adidas: Measuring and Managing Loss to Preserve Profit from the Oracle Retail RACK. 

Now available as a cloud service, Oracle Retail XBRi Loss Prevention Cloud Service captures all POS transactions and then administers advanced business analytics that apply a laser-focused look at key loss patterns. Designed to be completely agnostic to the POS solution and source data, XBRi integrates with both Oracle and third-party POS solutions – even multiple solutions – giving retailers flexibility and freedom of choice. The cloud service shifts funding from a potential capital investment in software and IT infrastructure to an operational expense. 

To learn more, be sure to visit us at the Oracle Retail Booth #1227 at #NRFProtect this week in Long Beach, CA. 


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