CASE 11.1 OPENING CASE Safeway and PepsiCo Apply Data Visualization to Supply Chain PepsiCo and Safeway The goal of Safeway's Data Visibility program is to improve supply chain visibility with key vendors, such as PepsiCo. Figure 11.2 Deloitte Consulting partnered with Deloitte Consulting partnered with PepsiCo and Safeway to help PepsiCo and Safeway to help them PepsiCo worked with major analyze huge amounts of visually analyze POS data at the customers to improve demand Deloitte Analytics HIVE, short for forecasts in order to minimize point-of-sale (POS) data at its Highly Immersive Visual inventory on-hand. state-of-the-art visualization Environment. center called HIVE TABLE 11.1 Opening Case Overview Companies . Safeway, Inc., a $44.2 billion grocery chain incorpo rated in Pleasanton, CA. . PepsiCo, a major food and beverage company head- quartered in Purchase, NY, with 274,000 employees and 2013 revenue of $66.4 billion. Locations and . Safeway is a food and drug retailer in North America Industries with 1,335 stores in California, Hawaii, Oregon, Washington, and the Mid-Atlantic region. . PepsiCo is a food and beverage manufacturer whose Supply chain visibility is products are marketed in more than 200 countries the awareness and sharing and territories. of POS data and data about Deloitte HIVE is a physical environment where people can product orders, inventory Consulting's examine the latest analytics approaches themselves levels, demand forecasts, HIVE using their own data. transportation, and logistics by trading partners from raw Business challenges Inventory management is crucial to retail operations- material to delivery to end and a challenge throughout the supply chain. customer.SUPPLY CHAIN In an effort to improve supply chain visibility, Safeway implemented data-sharing VISIBILITY programs with PepsiCo and other key vendors (Figure 11.1 and Table 11.1). Benefits of improved visibility are increased sales and millions of dollars in reduced costs along the entire supply chain. 369 370 Chapter 11 Data Visualization and Geographic Information Systems In 2012, Clay Broussard, Director of Customer Supply Chain & Logistics at PepsiCo, contacted Safeway's Kirsten Curtis, Director of Demand Planning & BI. Clay explained (Curtis, 2013): Safeway's Data Visibility program is very forward thinking Paired with PepsiCo's 360" Retail execution program, our teams are equipped to improve an already lean supply chain. But if we really want to take it to the next level, we need a different way to view the data. Deloitte Consulting has offered to part- ner with us to provide an effective way to interpret massive amounts of data at its state-of-the-art visualization center called the HIVE .. . are you interested? Kirsten was interested because she believed a data visualization strategy was vital to Safeway's success. EXCEL-BASED In the past, when Safeway wanted answers about stockouts, managers used spread- ANALYTICS sheets to gather and compile inventory data and see how stocksouts trended across the company. With spreadsheets, managers could discover general trends over time, but they could not identify trends across a specific brand or universal product code (UPC). Trends about each brand required more data than could be represented in rows and columns of a spreadsheet. Spreadsheet limitations ultimately led the com- pany to try data visualization. In August 2012, representatives from Safeway and PepsiCo came to Deloitte's HIVE for a day-long design session to analyze many terabytes of data. HIVE Deloitte hosts meetings with business leaders who want to understand business analytics better. These sessions are tailored to address their business challenges. At the HIVE, executives get help with analytics tools using their own data. The HIVE gathers together a wide range of the latest analytics technologies from all over the world. In a very short amount of time, executives can learn what might otherwise have taken months of meetings, demonstrations, and business pitches. Data Visualization Process at the Hive PepsiCo and Safeway participants collaborated to understand how to reduce the "number of days of supply" from their supply chain while maintaining service levels. This project would save PepsiCo and Safeway millions of dollars each year. During their session, data visualizations were built to explore questions about stockouts. The data included brands, UPC barcodes, costs, districts, store numbers, out-of- stock scans, and out-of-stock reason codes. After Safeway and PepsiCo decided on the visualization technique that best represented their supply chain, they needed to design three processes to operationalize it. The three processes to be designed were: 1. How to feed the huge datasets into the visualization software 2. The best ways to display the data visually 3. How to gather feedback Within 40 days, Pepsico and Safeway implemented their initial data visualization with dashboards and drill-down capabilities, then spent another 20 days refining it.\f372 Chapter 11 Data Visualization and Geographic Information Systems one category. In general, reporting tools show what has already happened in a busi- ness. Analytical tools show what might or could happen in the future. LEARNING, EXPLORING, When companies, political parties, sports teams, or fund-raising agencies invest AND DISCOVERY in campaigns, promotions, special events, or other projects, they want to learn something from them. Learning is the basis for continuous improvement, such as improved earnings as you read in the opening case. Visualization is also used as a data explorer or for data discovery -discovering hidden relationships. Like Safeway and PepsiCo, companies across industries are discovering new relationships and learning how to improve performance using data visualization. Enterprise visualiza- tion apps for Androids, Apple iPads, and Blackberry Playbooks are replacing static business reports with real time data, analytics, and interactive reporting tools. Visuals Examples of visualizations are dials, charts, graphs, timelines, geospatial maps (refer to Figure 11.1), and heat maps. The tricolor heat map in Figure 11.4 instantly alerts the viewer to critical areas most in need of attention. Visual displays make it easier for individuals to understand data and identify patterns that offer answers to business questions like "Which product lines have the highest and lowest profit margins in each region?" Interactivity and drill-down capabilities are standard features. In Figure 11.5 are two other types of heat maps, both based on the same dataset and created with Tableau Desktop. Notice how visual display depends on what you want to learn or convey. As you read in Chapter 3 and Figure 3.1, human expertise is an essential component of data visualization. A common mistake is to invest in the analytics foundation-tools, quality data, data integration, touch screens-but overlook the most crucial component-namely, users' ability to interpret the visual reports and analyses correctly. DATA DISCOVERY According to Gartner's research, in 2014 the data analytics market split into two MARKET SEPARATES segments: the traditional BI market and the new data discovery market. Data FROM THE BI MARKET discovery software had been viewed as a supplement to traditional BI platforms. Now it is a stand-alone alternative to BI. This split occurred because today's data Country RISKS code Capital Financial Inflation Economici Social Goverment NA-1 NA-2 SA-1 SA-2 SA-3 SA-4 SA-5 AA-1 AA-2 AP-1 AP-2 Figure 11.4 This heat map uses three colors to convey information at a glance. The heat map is like a spreadsheet whose cells are formatted with colors instead of numbers. (Moody's.)11.1 Data Visualization and Learning 373 Region Product Cate.. Product Sub-Category Central East South West Furniture Bookcases 72 -10,151 -22.417 676 Chairs & Chairmats 37.920 23,583 34,026 44,409 Office Furnishings 26,293 14,523 25,121 30,941 Tables -19,777 -60,677 26,172 -16,990 Office Appliances 22,960 16,812 26,906 21.276 Supplies Binders and Binder Accessories 73,961 71,420 89,530 92,273 Envelopes 10,825 7,482 19,182 11,222 Labels 2,429 4,041 3,479 3,740 Paper 11,047 13.510 10,997 10,432 Pens & Art Supplies 2,781 1,397 510 Rubber Bands -174 156 170 Scissors, Rulers and Trimmers -1,765 -1,179 -2,903 -1,953 Storage & Organization -7,233 11,238 -2,018 Technology Computer Peripherals 11,971 14,808 30,475 37,280 Copiers and Fax 512 67,264 83,590 26,997 Office Machines 30,876 47,277 129,060 61,377 Telephones and Communication 79,293 73,715 78,905 14,860 Technology Technology Office Supplies Telephones and Office Machines Binders and Binder Communication Accessories Office Supplies Office Appliances Supplies Paper Technology Technology Copiers and Fax Computer Peripherals Office Supplies Envelopes Furniture Furniture Furniture Chairs & Chairmats Office Furnishings Tables (b] Figure 11.5 These heat maps represent the same dataset using red and green and color intensity to show the profitability of three product categories and their subcategories. In (a), data labels show detailed profit, while in (b) the area of each segment is used to make comparisons