Download PDF
Cashing in on Improved Profitability through Pattern Detection and Big Data Analytics
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Retail
- Telecommunications
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- Data Science Services
- Software Design & Engineering Services
The Challenge
Extreme SKU proliferation created long customer lead-times and a time-consuming sales quoting process. With thousands of different product choices, salespeople and customers had to contend with endless options, often leading to a pricing war and expensive, custom product builds. Due to a lack of a unified view and insight into their data, the organization suffered the following challenges: A reactive approach to the market due to a disconnect between product management, sales and the supply chain. An incomplete view of customer buying patterns and a lack of, multi-dimensional sales analytics. Data was stored in separate data warehouses and existing tools were not designed to unify or optimize the data accordingly. Guesswork and process inefficiency in sales due to a disconnect between the sales funnel and the ordering system. For example, each unique proposal entailed 38 steps and about 30 minutes to create a single configuration file. The qualitative impacts of all of these factors resulted in lost sales, slow response time, reduced sales efficiency, long lead times, and more. Product variety equated to millions of dollars in wasted productivity. NCR knew that the information contained in their data, such as customer buying patterns, is the life blood of their company, but the question was how to bring it together. NCR needed a way to gain a unified view into their data to more accurately sense and shape demand and apply that intelligence across Sales, Operations, and Solutions Management. They sought a simple way to improve visibility into their product offerings to ensure they were selling the right product to meet customer needs, improve profitability and accelerate commission payments.
About The Customer
NCR Corporation is a global, computer hardware and electronics company that sells self-service kiosks, point-of-sale terminals, automated teller machines, check processing systems, bar-code scanners, and business consumables. It is also a solutions company, selling total solutions in the retail, financial, travel, telecom and technology, and hospitality industries. The company has a product line of more than 150,000 uniquely order-able products offered in more than 130 countries.
The Solution
NCR chose Emcien because it’s software could analyze unstructured product data in the context of sales, marketing, design, finance and operations. Additionally, NCR had a goal shape demand toward the use of high volume product configurations and to use guided selling, instead of just reacting to demand. Mike Groesch, NCR’s VP of Sales and Operations Planning, and Kate Lisska, NCR’s director of sales operations, realized that the Emcien approach would break down the walls of functional silos that are an impediment to the entire product development process, from product planning to building to selling and then delivering the final product to the customer. “We saw this is an opportunity to bring three disparate departments together onto one tool set,” said Mike Groesch, VP of Sales and Operations Planning, NCR Corp. “The idea of Solutions Management, Sales and Operations together in one environment to enhance the performance of our new product introduction, improve our sales enablement, and to give the supply chain a better demand signal was really compelling.” “Emcien provides information on actions we need to take – right out of the box – which is superior to business intelligence tools,” said Groesch. Solutions managers now leverage Emcien’s pattern detection platform to identify connections in customer-buying patterns, reveal exactly which product configurations customers are actually buying, determine the most popular feature combinations by market segment and then optimize the product mix accordingly. This enables solution managers to reduce the number of product offerings while continuing to meet customer demand. This type of Big-Data-driven intelligence arms Operations with the insight required to build products more cost-effectively with shorter leadtimes. Solutions managers then push optimal product configurations to the sales force in real-time. “The actionable nature of the Emcien solution set was really compelling,” said Groesch. “Emcien provides us with a systemic way to communicate with Sales in the way that Sales would respond to, quite simply.” Sales can guide customers more quickly and seamlessly to the configurations that offer the best blend of features, lead-time and price for their needs.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Case Study
Digital Retail Security Solutions
Sennco wanted to help its retail customers increase sales and profits by developing an innovative alarm system as opposed to conventional connected alarms that are permanently tethered to display products. These traditional security systems were cumbersome and intrusive to the customer shopping experience. Additionally, they provided no useful data or analytics.
Case Study
Vodafone Hosted On AWS
Vodafone found that traffic for the applications peak during the four-month period when the international cricket season is at its height in Australia. During the 2011/2012 cricket season, 700,000 consumers downloaded the Cricket Live Australia application. Vodafone needed to be able to meet customer demand, but didn’t want to invest in additional resources that would be underutilized during cricket’s off-season.