Business Intelligence in the Retail Sector RITU RATHOD

Business Intelligence in the Retail Sector RITU RATHOD JENNIFER DOWNEY

WHAT IS BUSINESS INTELLIGENCE Business Intelligence: • The practice of collecting, integrating and analyzing data. • A process in which raw data can be transformed into useful and meaningful information. • Main purpose of BI is to support better decision making. Three industries that widely use BI • Oil • Retail • Apparel Business Intelligence in Retail: • Retail industry continues to accelerate rapidly. • Retailers aim to deliver a seamless experience across stores and on their websites. • Use of BI enables retailers to gather insight through data. • Helps retailers formulate marketing strategies. • Predict future requirements of customers.

Business Intelligence in Retail Traditionally BI and Analytics has provided actionable insights that can help corporate executives, business managers, and other endusers make more informed business decisions based on historical data. Today, BI and Analytics solutions provide the ability to: • Optimize internal business processes • Increase operational efficiencies • Identify market trends • Drive new revenues • Forecast future probabilities and trends

Business Intelligence in Retail - Purpose Allows the retailer to gain high quality information through the use of BI tools like data warehousing, data mining, and online analytical processing. BI allows organizations to predict the behavior of their competitors, suppliers, customers, technologies, acquisitions, markets, products and services. BI helps retailers use such as Point of Sale transactions and social media gives unprecedented access to the customers’ mind. Retailers are also using retail management technologies like Self Checkout POS, RFID and Cloud Computing for them by providing a real time integrated and collaborative information system. BI further helps the retailer keep a vigilant eye on business activities by estimating the long and shortterm demands, notifications of low inventory and monitoring factors that influence customer buying decisions. BI is becoming a “mission critical” application. Retailers are looking beyond reporting capabilities to applications for syncing information from a wide variety of systems to analyzing performance of sales, margin, supplier delivery times, effectiveness of promotions and allowing them to effectively react to business insights

Business Intelligence in Retail – Dimensions of Data Customers - Loyalty cards, Credit Card Tracking, IP address, registered user logins, social media, user-generated content, and linking data with a customer-relationship management (CRM) system. Products - SKU collection, enriched data like brand premiums, similarity links, link customer tie ins that are micro-target to customers, allow for more attributes that increases product modeling. Time - Increases size of collection because real time collection allows for continuous measurement of customer behavior, product assortment, stock outs, in-store displays, and environments. Location - Use of geo-special location and purchase history can tie products to a region. Data allows for targeted marketing and product placement. This can allow for short-term revenue maximizing especially if customers purchase history is tied to what they are physically near. Channel - Increase is ways that consumers are purchasing products including a tendency research shop (accessing info on one channel but buying through another). Leads to collection from multiple touchpoints and helps retailers with : (i) understanding,

Business Intelligence in the Retail Sector In Store Uses (I)/ E-commerce Uses (E) Marketing • Loyalty Scheme Data (I/E) • Track Consumer Preferences • Personal Promotional Offer • Real Time Sales Data (I/E) • Price Decisions • Layout – heat maps, customer buying habits (I) • Layout – Shoppers platform acceptance (E) • Consumer Insight to Substitution acceptance • • • Inventory Optimization Stock Deployment (I/E) Replenishment Procurement SKU Analyzation SKU Deployment • Store Layout – Maximization in minimal space. • Logistics Optimization • Service Level Optimization

Business Intelligence in Retail – Example of a Data Capture Map

Business Intelligence in Retail –BI Example of Price Decisions

A Look Into Two BI Superusers WALMART – IN STORE AMAZON – ONLINE

WALMART Dependent on data to make shopping experience memorable. Reasons for use: 1. Check in to pick up an online order at their store, refill pharmacy prescriptions. 2. In-store maps with product locations help finding items easier. 3. Analyze demand make products available- improved the apps capabilities to ensure products are in stock.

METHODOLOGY - HOW WALMART USES BI Helps make Walmart pharmacies more efficient: -BI allows Walmart to understand the number of prescriptions filled in a day. -Determine the peak time during each day/ month. -Scheduling manpower, thereby reducing the time and labor needed to fill perceptions Improve store checkout: -Uses predictive analytics to anticipate store demand (use of data to identify likelihood of future outcomes) -Helps determine how many associates are needed to man registers. Managing the supply chain: -Uses simulations to track number of steps - dock to store. Strategy also pinpoints the number of times a product gets touched along the way to the customer. -BI helps reveal transportation lanes and routes for the company’s trucks- keeps transportation costs down. Optimize product assortment: -Analyses customer preferences and shopping patterns that help with stocking shelves and displaying merchandise. Personalize shopping experience: Uses data analytics to anticipate customer needs then creates personalized mobile rollback deals for shoppers.

CHALLENGES Walmart has been making big investments in its online business – adapt to preferences and compete with rival, Amazon. BI tools can get complicated to use and only a few individuals know how to use them. Data spread across different systems and software (ERP, CRM, excel spreadsheets), can get difficult to gather. Getting your way around data buried in your systems – get data when you need it can be an extremely painful process. Delivering mobile BI; managers and senior executives should be able to access insights easily, as and when required.

FUTURE Walmart scan and go:

FUTURE AI and Robotics: - New shelf scanning technology being tested in a few Walmart stores - Simplifies routine work - Uses data and vision technology to find items that are out of stock, make changes and identify products with missing labels - Helps locate items and check inventory levels on the shelf - Technology is focusing on tasks that are repeatable, predictable and manual to free associates to spend more time serving customers

AMAZON Dependent on data to drive business and create innovative solutions in retail. Reasons for use: 1. Gather information to drive sales and market products. 2. Analyze demand make products available with improved product monitoring capabilities to ensure products are in stock 3. Optimize Logistics and Supply Chain methods

METHODOLOGY - HOW AMAZON USES BI Personalized Recommendation System: - Uses Comprehensive collaborative filtering engine (CFE) -BI allows Amazon to analyze previous purchase to suggest new items -Uses your recommendations to suggest new purchases to others who bought similar items -Pulls info from your search and wish list to recommend new purchases Book Recommendations from Kindle Highlighting: -Uses social networking services to send Kindle highlighted notes to others for book discussions -Uses highlight function to determine what other books you might like One-Click Ordering / Price Optimization -Auto fills in shipping and payment methods to allow for quick purchase. -Sets prices based on activity on website, competitors prices, product availability, item preferences, order history, expected profit margin. Product prices change every 10 minutes as data is analyzed Anticipatory Shipping Model: -Uses big data to predict when you are likely to order the same product again and prestages the items a dc close so it is ready to ship -Uses predictive analytics to increase product sales by suggesting its time to by or creating personalized sales for items pre-staged Supply Chain Optimization: -Links to manufacturers to track their inventory -Uses analytics to determine warehouse closest to customers -Uses graph theory to help decide best delivery schedule, route and product groupings to reduce

CHALLENGES Amazon has been making big investments in its big data analysis – they will continue to be industry disruptors, but will find challenges BI tools to increase channel expansion, high growth pains, and evolving Business Models How to use data to digitize real world experiences to create a sense of wonder for visitors. Expanding their mobile first commerce as trends show that by 2022, $175. 4 B in retail sales will come from mobile devices Changing government regulations regarding BI especially as they expand their international ecommerce retailers and customers.

FUTURE Amazon will use BI for customer reach and optimization. - Expanded go stores - Drone delivery - VR real world shopping experience

Business Intelligence in Retail –Benefits to BI The benefits associated with BI adoption in the retail sector include accurate decision making, efficient service delivery and competitive advantage. These benefits include - Better customer focus - Ability to anticipate changes in the market earlier - Ability to manage prices better - More efficient service delivery - More robust forecasting of future trends - More efficient use of resources - Improved sharing of inter-department knowledge - Easier to manage costs - Strengthens strategic planning - Better quality of information for improved decision making - Stock management optimization

Business Intelligence in Retail –Measuring Benefits

Business Intelligence in Retail – Conclusion Using BI tools in the retail industry is the key to revealing relevant insights, increasing profitability, and improving brand awareness. The right BI analytics can help uncover new markets, identify areas for future development, track the responses to marketing strategies, and much more. In the research it was found that BI and analytics plays a crucial role and the use of integrated BI tools makes decision making easier and faster. For big data in retailing it is important that data quality is improved rather than merely a rise in data volumes that drives improved outcomes. Increases in quality comes from a mix of new data sources, a smart application of statistical tools and domain knowledge combined with theoretical insights. Improved data results in improved forecasts of customer demands, planning, pricing, stock optimization, clear operatives, as well as strategic decisionmaking Developing and implementing software solutions that help retail businesses to streamline their operations as more and more organizations in the retail sector are calling for the necessity of business intelligence (BI) reporting.

Business Intelligence in Retail – Thought Provoking As you keep the reasons and ways that BI is used in retail wrap your mind around this final statistic: Walmart collects around 2. 5 petabytes (1 petabyte = 1, 000 gigabytes) of information every hour about transactions, customer behavior, location, and devices

THANK YOU

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