Business Intelligence In Retail

Mktng ‘B’

E - BUSINESS [BUSINESS INTELLIGENCE IN RETAIL] Analysis of use of Business Intelligence in Retail Industry. Here the Business Intelligence Market is taken into account and a brief study is made.

 Submitted To:

Submitted By:

Prof. T R Vaidyanathan

Gaurav Kumar 08PG304 Marketing ‘B’



BUSINESS INTELLIGENCE Business Intelligence (BI) refers to skills, processes, technologies, applications and practices used to support decision making. BI technologies provide historical, current, and predictive views of business operations. Common functions of Business Intelligence technologies are reporting, OLAP, analytics, data mining, business performance management, benchmarking, text mining, and predictive analytics. Business Intelligence often aims to support better business decision-making. Thus a BI system can be called a decision support system (DSS). Business intelligence connects people with information in an easy-to-use way so they can make better decisions. With BI software you can: Set targets, see results and understand what drives the numbers. Identify trends that may be benefits or threats. Take action with a common context for decision-making across every department. Identify and analyze opportunities and trends. The best business intelligence software:  Delivers trusted information for a single version of the truth.  Lets you work with information the way you want—reports, dashboards, and scorecards.  Puts tools in your hands to author and share information as you require. Business intelligence applications can be: o Mission-critical and integral to an enterprise's operations or occasional to meet a special requirement o Enterprise-wide or local to one division, department, or project o Centrally initiated or driven by user demand Business Intelligence helps organizations to leverage technology and best practices to deliver management insight from enterprise applications and data. Combining business intelligence tools

and applications with effective structure, quality improvement and information governance and learn to maximize payback while minimizing risk. Business Intelligence is a broad field of study. The major thrust of business intelligence theory looks at certain factors to make high quality decisions. These factors include customers, competitors, business partners, economic environment and internal operations. Here is some more information on how these factors help businesses make quality decisions. Customers: Without customers a business can't survive. Businesses need to sell their products and services. Business intelligence helps businesses understand their customers better, looking at their preferences, helping businesses adapt to their customers demand. Business intelligence is used to collect data from customers usually within the marketplace. There are many ways to collect data from your customers; it can be as easy as a POS system (point of sale), collecting data on what customers are buying and which products they are not interested in, collecting data on customer habits and preferences by asking them in surveys or polls. There are even marketplace specialists that watch customers behavior in the marketplace and report back to the companies giving them insight into how their customer respond to stores, personnel and product and services that a business sells. Once this data is collected, it is up to an organization to use this data appropriately. Business intelligence is a process in which vast amounts of data can be viewed and vetted giving managers and business owner's important information that can be resourceful. Competitors: Not only do businesses have to keep customers satisfied buying their products, they also have to compete with competitors that are constantly looking to poach a businesses customers and make them their own. Businesses today must constantly evaluate the effectiveness of their competitors and choose smart strategies that not only hold their competitors at bay, but also grow their own businesses market share. Business intelligence can help a business determine the strategies that your competitors are using to steal customers away, as well as help your own business to differentiate itself from others, effectively growing a larger and more profitable customer base. Business Partners: Business partners are essential to any business, whether it is suppliers, payment processing companies, customer support companies or delivery companies that help

your business throughout its cycle, it is important to make sure that all businesses partners associated with your business are in balance with you. Having a supplier that isn't able to keep up with your demand or having a customer service contractor that is unable to help you with certain support problems can cause your business to fail. If you want your business to work smoothly and effectively, all business partners must be in line with each other. For instance, today many businesses share key data with their suppliers so that their suppliers can anticipate present and future inventory levels and make adjustments, which inevitably help your business. Sharing information is key and being able to gather information and sharing appropriate information is where business intelligence is important. Economic Environment: Another way that business intelligence can help an organization is by taking into consideration key economic indicators such as consumer spending, inflation, unemployment, upturns and downturns in the economy, etc. Without business intelligence, your organization can't process information effectively in order to modify strategies that fit the current economy. Internal Operations: Internal operations are usually defined as the on going day to day activities of a business or organization. If any business wants to be successful, it needs to be able to view your business's strengths and weaknesses on a daily basis. It also needs to see at any moment, just how much profit the business is making and the liabilities. Without decent foresight, you might make hasty decisions such as commit to new spending or paying off debt when your business could allocate those funds some where else. Business intelligence is extremely important to gauge the organizations‟ current state of business, as well as all parts that constitute the whole of the business together to see where funds are needed, what part of a business is weak and what parts of the business is strong. Once businesses know what to look at to give them information that they need to analyze, it is important to gather this data and then use business intelligence methodologies to sift through the data to provide solutions to common everyday business problems. One of the ways to accomplish these tasks is with Key Performance Indicators. KPI, are a way that business intelligence can analyze and evaluate the current state of a business and then use this information to choose a strategy and then execute this strategy.

Some businesses track Key Performance Indicators each year or quarter, some each month or week and if you have the means, many corporations try to track specific data daily in order to fine tune or tweak their strategies. Computers, databases and a group of analysts usually work on business intelligence's methodology. Usually each company has their own business intelligence methodology that fit their specific needs. Some of the more popular ways to create Key Performance Indicators are through Goal Alignment Queries, Baseline Queries and Metrics related Queries. Goal Alignment Queries are a way to determine what your businesses goals are in using Business Intelligence. Is it your businesses goal to grow more market share, to make more profit per item, to start a new revenue stream, to find new manufacturer or suppliers, etc. Baseline Queries help you understand your current approach to collecting data and whether or not this approach is satisfactory, where its weaknesses are and what its strengths are. For instance, if you would like to monitor your customers actions more closely, what are the current tools in place (POS systems, surveys, market research, etc), how do these current tools perform, which are weak, which ones need tweaking and what tools can be added. Metrics Related Queries are extremely important in the Business Intelligence process, because data can only be beneficial to a company if you can come up with a way to measure it. Metrics related queries looks at data and comes up with solutions to accurately measure data to meet businesses needs. Once data is measurable, you can easily analyze it and determine what is working and what is not. Business intelligence is a very broad topic of study, however If you would like your business to succeed, it is extremely important to understand the factors of business intelligence and learn how analyze and use the data created by this methodology.

AIM : Introduction To BI Market Increase of investments in improving customer service, productivity of customer-facing employees, marketing automation and sales force automation are driving sales of CRM applications. Further, the recent slowdown in the US economy creates opportunities for CRM vendors as companies are in a cost-cutting mode and are forced to rethink how and where they spend their marketing and sales promotion dollar. In addition, due to the increased cost of customer

acquisition,

customer

retention

has

become

much

more

important.

The software-as-a-service (SaaS) or on-demand CRM market is expected to give stiff competition to the traditional on-premise CRM and is forecast to account for a significant share of the market. Further, the ongoing cycles of market consolidation and innovation, combined with convergence of BI with enterprise applications, such as CRM, and growing volumes of data are driving the demand for BI applications. The need for linking business processes with partners, suppliers and customers to have a comprehensive view of operations beyond the organization, is also expected to drive the demand further. In addition, a shift from spending on planning, forecasting and analytical applications to spending on packaged analytical infrastructure technologies — data warehouses and data marts is expected to drive the market through 2012.

Predictions by Gartner about the Market:  Because of lack of information, processes, and tools, through 2012, more than 35 percent of the top 5,000 global companies will regularly fail to make insightful decisions about significant changes in their business and markets  By 2012, business units will control at least 40% of the total budget for business intelligence

 By 2010, 20% of organizations will have an industry-specific analytic application delivered via software as a service (SaaS) as a standard component of their business intelligence portfolio  In 2009, collaborative decision making will emerge as a new product category that combines social software with business intelligence platform capabilities  By 2012, 33% of analytic applications applied to business processes will be delivered through course-grained application mash ups. MOST SIGNIFICANT OF ALL - New license revenue in the Asia/Pacific business intelligence market will reach $259.3 mln in 2009. It will grow at a compound annual growth rate of 13.6%, Gartner says. The market for Business Intelligence (BI) platform software in Australia is forecast to reach A$174.8 million (US$152 million) in 2009, up 16.8 percent from A$149.6 million (US$130.1 million) in 2008, according technology research and advisory firm Gartner, Inc. Gartner analysts says that BI platform purchases should be more resilient to a recession compared with some other software areas, but a tougher economic environment, together with stronger pricing pressures, would still hamper growth during the next five years. Additionally, many organizations are still trying to get value from their BI investments, according to Gartner. Further investments by these organizations will be constrained until they determine how to get value from the investments they have already made. For the fourth year in a row, BI applications have been ranked the top technology priority in the 2009 Gartner Executive Programs survey of more than 1,500 chief information officers (CIOs) around the world. Mature markets such as Australia and Singapore continue to make investments but struggle with a gap in implementation skills. Limited BI skills in Asia Pacific will inhibit growth in license revenue, but it also represents an opportunity for service providers. Software vendors should work on improving usability, design appropriate learning programs, propose alternative delivery models and form strategic partnerships with local service providers.

The overall Asia Pacific BI platform software market will continue to grow at a respectable compound annual growth rate (CAGR) of 15.3 percent through 2012, reaching more than US$510 million by 2012, according to Gartner. Australia will remain the biggest BI platforms software market in Asia Pacific through 2012, reaching A$243.8 (US$212 million) in revenue, followed by China. The local BI market will be sustained through maintenance revenue, which will become more pronounced in the slowing economic environment.

BI IN RETAIL The competitive game is changing for retail. As the industry continues to consolidate, retailers have begun to realize that using technology to better understand customer buying behavior, to drive sales and profitability, and to reduce operational costs is a necessity for long-term survival. The effective use of Business Intelligence (BI) tools is fundamental to success in a complex and competitive retail environment. Stock forecasting and planning are often carried out across hundreds of stores, with sales results judged against the previous month, week, or even day. In a retail organization, managers and supervisors are constantly juggling multiple activities that need to be continuously monitored and adjusted to increase efficiency, improve customer service and increase sales. Such "juggling acts" are repeated on a larger scale throughout the retail enterprise. That's why providing easier access to appropriate, accurate, and timely information, allowing people throughout their organization to make faster, more-informed decisions, is a business imperative in retail. Retailers are now paying significant attention to BI software, specifically in the areas of merchandise intelligence (including merchandise planning, assortment, size, space, price, promotion, and markdown optimization), customer

intelligence (including marketing

automation, marketing optimization, and market basket analysis), and operational intelligence (including IT portfolio management, labor optimization, and real estate site selection). There are many factors that have led retailers to adopt BI software: increased competition, the need to squeeze more profitability out of less space, prevalent credit card usage, the Internet‟s role as an alternative sales channel, the popularity of loyalty cards, and soon, RFID (radio frequency identification). These milestones have created a wealth of data that retailers are now beginning to

appreciate and use. With BI, retailers can meet their growing demand for actionable informationfrom top executives to store managers, within an organization and throughout the supply chain. The BI addresses the concerns and presents innovative solutions for high-performance retail business intelligence. The retail industry‟s requirements for fast, easy access to their business information have evolved to meet user demands at every level of the enterprise. Business intelligence for the retail industry, delivers secure, scalable access to critical sales, customer, and inventory data to make the most effective performance decisions every day. BI enables researched insights into buyer behavior and the purchasing process, the marketing strategy that is developed for the retailers will be based on quantitative facts rather than qualitative indicators. With BI managers from a Retail industry can get answers to one & many of the questions like:  What items should be included in the inventory  What pricing and promotional strategy is the most effective  What the demand will be for a select assortment of merchandise  What impact an incremental price change will have on demand  Which floor plan will sell more designer apparels  Which customers will respond to a direct mail or exchange offer  Where to place retail outlets  How many of each size or color of an item to put in each store  When and how much to discount The effects of these decisions can save or generate millions for retailers. Helping retailers gain competitive advantage, BI delivers performance management capabilities for reporting and analytics that can transform decision-making from reporting to actionable analytics enabling decision-making for every role in the organization. Most of the retailers that successfully transformed their legacy reporting systems with more sophisticated BI technology in the past decade would say that the journey was ultimately worth it, but often hampered by numerous implementation challenges. Retailers were forced to build from scratch—often at a great expense— such essentials as a workable data model, data loading

routines, and even the most basic report templates from within very complicated and expensive BI development environments. This often led to budget overruns and delayed deployments along with merchant stakeholder skepticism. However, once deployed, new abilities like drill-down reporting and daily insight were considered major advancements from the often batch-oriented, weekly canned reports most merchants had been receiving. Unfortunately, the total cost to deploy these was prohibitive for many retailers, especially Tier 2 and Tier 3 retailers that could not seem to make a benefits case for the investment. Traditional BI vendors strengthen their products with more industry focus - The depth and breadth of capabilities seen from the BI suite vendors was often viewed by retailers as both a blessing and a curse. With almost limitless options for building reports and analytic applications, this blank-slate approach often paralyzed retailers that were hoping for more industry-centric functionality to help them get quick wins in their enterprise data warehouse (EDW) and BI projects. Vendors have responded, with many creating retail industry teams to help expand specific products inside their portfolios targeted directly at retailers. Companies like Business Objects, Cognos, Microstrategy, and SAS have not only added industry experts, but also have begun to add important base functionality like an initial data model, extraction, transformation, and loading (ETL) functionality, and retail key performance indicator (KPI) libraries. They have also added initial application designs targeted at different functions like merchandising, vendor analysis, or store operations. And vendors like Actuate, Hyperion, and Information Builders have a number of retailers as clients, though they tend to place less emphasis on industry-specific systems in their product strategies and more on deeper enterprise BI and EPM functionality. We also can‟t ignore Microsoft, with its aggressive entrance into BI, along with its major internal investments in retail and a burgeoning partner portfolio targeting specific industries. A new breed of application is helping retailers‟ kick-start BI and EPM projects - Another major change in the retail BI landscape has been the rapid evolution of new vendors providing a hyper-

focused applications layer on top of established BI platforms. They have drawn major interest from retailers, especially Tier 2 and Tier 3 retailers implementing their first formal BI strategy and looking to fill two needs: rapid deployment (targeting less than 100 days) and lower total project costs resulting from lower implementation and consulting expense. Many are partnered with specific toolkits (most often Microstrategy) and retail-centric data warehousing platform vendors. Vendors in this newly developing category include QuantiSense, Manthan, MI9, and Seatab.

Business Intelligence Advantages in Retail Industry:  Improved business by collecting and analyzing data from various systems (financial, point of sale, inventory, distributors, and customer relationship management systems) in various formats.  Help managers design marketing campaigns for specific products by identifying opportunities.  Integrate financial data to control operation costs and optimize business performance with better profitability.  High capability of calculating costs and profits using „combine and recombine‟ methodology for various business drivers and delivers information via BI dashboards and BI reports.  Highly sophisticated planning performance intelligence that directly affects your business value proposition.  Unmatched scalability to process gigantic data flows at lightening speed and cater information hunger of a variety of users simultaneously.  Standalone Business Intelligence solution for retail sector for business strategy planning, location wise analysis, quick response to market volatility, cash flow management and inventory rationale, and to merge data from varied internal as well as external sources.

Players in BI market (Retail): A. IBM COGNOS

B. SAS

C. Microsoft Dynamics

D. SAP

E. SRIC BI

F. WebFOCUS BI

G. QLIKVIEW

The present system and how they generate MIS reports: The Business Intelligence Solution gives you a way to achieve strategic value more quickly by avoiding the delays and expenses of both proprietary and “built-from-scratch” solutions— enabling you to take advantage of tried and tested applications and technologies that integrate with and empower your existing skills and assets. Demands on your staff are minimized so they can maintain their current focus without being consumed by a massive warehouse planning and implementation project. Plus, there is no inherent requirement for new or complex database administration skills.

The Business Intelligence Solution is simple in structure but powerful in function—an advanced information foundation designed to support highly sophisticated, real-time and relevant business intelligence solutions. BI gives extensible warehousing engine with advanced data-mining features, industry- leading query support, sophisticated analytics and much more. The architectural approach also allows people from your stores, corporate offices and other operations to take an active role in its implementation and evolution; the resulting information and insights are relevant, actionable and aimed at improving both your top-line and bottom-line results. The BI enables insight and action all the way to the point of service in the store. And no wonder—only BI has a deep understanding of both retail business intelligence and retail selling environments. The BI helps you follow through on customer-centric strategies by integrating both product and customer information to yield deeper, actionable insights into not just what is selling, but to whom it is selling and why. RBIS supplies an extensive set of retail business solution templates that cover the gamut of retail operational and analytic reporting.

The Need for Implementation of BI in Retail: BI will be defined by the retailers that have figured out how to maximize customer satisfaction and profitability with the right combination of quality products, friendly and efficient service, unique value, a differentiated shopping experience, and a business model that truly serves its community -- locally and globally. How will this be accomplished? It starts with understanding the customer and then linking that insight into every decision that is made, from merchandising to marketing to distribution to store operations to finance, so that retailers can predict how to best serve their customers' ever-changing needs and desires. Our vision for the future of retail BI provides for that very scenario, through our intelligence platform and our solutions for customer, merchandise, operations, and performance intelligence that are combined in a suite designed to equip retailers to become truly innovative. A solution seeking to use customer behavioral data to make better merchandising or marketing decisions needs to interface with sales transaction systems, loyalty systems, in-house credit systems, coupon redemption systems, catalog and Internet customer data systems, and so forth. A system that recommends optimized price changes should interface with the price management system, the item master; the system that generates labels, etc.

Specific Areas in Which Retailers can Benefit Most Include: Merchandising-- This is clearly the most important area of a retailer's business area where retailers are beginning to exploit the full value of BI. Analysis of past performance, combined with plans and forecasts of future customer behavior, leads to more accurate initial allocations of merchandise across channels and stores. Assortment and size optimization that are based on customer demand patterns ensure that the correct assortments, size, and case-pack distributions get sent to the correct stores. Daily price, promotion, and markdown optimization ensures that items are priced for optimal profitability, both preseason and in season. Space automation and optimization ensure that departmental sales and profit per square foot are maximized, and products are given the correct inventory and space on the shelf or on the rack. Optimized fulfillment ensures that products are allocated or replenished based on demand. Accurate

analysis also results in a more efficient use of manpower in picking, packing, and shipping the first wave of product, while minimizing additional, costly payroll expenses to facilitate transfers between stores, vendor returns, changing signage and labels for markdowns, and otherwise correcting mistakes. Marketing-- By understanding customers better -- whether by profiling, segmenting, gauging propensity to respond, or using market basket analysis -- retailers can create better-defined targeted campaigns, reducing expenses (printing, paper, postage) while increasing response rates, revenues, and gross margins. Also, as retailers gain a better understanding of their customers' buying behavior, this analysis can then be used to create more effective merchandising plans for the next season. Operations -- Understanding and predicting changes in demand -- by hour, by day, by location, by promotion, by price change-- means that the store floors, the catalog call centers, and the fleet crews delivering replenishment orders from the DC to the store are all appropriately staffed. This understanding also leads to optimal productivity since store-level human capital costs can be scheduled better and managed more efficiently.

The Strength of the Market for BI in Retail Today: The market is very strong and getting stronger. While it is difficult to find a comprehensive suite of retail-specific BI offerings that spans the spectrum from competitive intelligence to merchandise planning and optimization (product, price, promotion, and placement) based on customer insight, to knowing how to maximize the ROI on the next marketing campaign, to understanding where to build the next store, to reducing supply chain costs. Retailers are telling us over and over that they are seeking a single, stable, reliable, and proven provider of superior BI solutions. They are implementing projects that span multiple years and will deliver value for years to come.

Analysis: Industry has to put up with loads of data volumes, specially with the checkout basket data, constantly being revised products and their SKUs, stock availability data, commercial data to calculate margins, delivery van slot availability, product substitution data, customer acceptance data, customer services data, new customer master data etc. At the same time, timely information should be available for the various departments like: Finance, Operations, Supply Chain, Marketing, Customer Services, Analytics, Commercial, and Business Development. Information is also required at different tiers of the organization like, Operational, Department and Corporate, mainly for running, managing and monitoring the business. We can add one more important tier in the information pyramid, called Analytics. This one layer works across the different departments and functions, brings in in-depth understanding on data. Operational Reports can support operational activities, but can be mostly be supported by the various OLTP reports. This leaves the reporting at Department level, Corporate and Analytics for the BI arena. I think, the BI Arena can be classified under 3 categories as: 1. Business Development Area: Campaign management & Promotions fall into this category, customer segmentation, market place etc., 2. Customer Engagement Area: Complaints, Returns, Refunds fall into this category etc., 3. Business Reporting: Budgeting, Actuals Analysis, Transaction & Operations monitoring etc., fall into this category These 3 areas can also be called as categorized as per relative importance. The first 2 are more or less customer facing, whereas, the third one is internal facing.

Let us take a close look at the kind of data elements that we have to deal with in this Retail BI arena. We can categorize these data types into Master Data, Transaction Data, Derived Data, and Analysis areas. Most of the Master data is around Customer, Product, Merchandising, Vendor, Employee, Campaigns and promotions. Most of the Transactional data is around Sales Baskets, product pricing, discount coupons, returns, refunds, complaints, fulfillment, and inventory / stock. Some of the Derived data is around customer loyalty, customer segmentation etc. I think we can safely call the following to fall under Analysis Areas: Segmentation, market basket analysis, returns analysis, failed deliveries, inventory analysis, fraud analysis, customer service, delivery options, and basket & spend analysis, marketing, profitability analysis etc. The first 2 categories are also covered in this paragraph. Let us also look at the Business Reporting area. Most of the retailers operate on periodical reports in this area for their business monitoring. They use weekly / monthly periodic reports in this space. It is observed that most of the efforts are spent towards preparation of these reports, albeit manually, at most of the Retail companies. After understanding the requirement categories and data elements that are involved, let us take a look at the users' convenience in BI. We can possibly, list these as follows: 1. Should provide standard reports in a scheduled manner 2. Should provide on-demand reports 3. Should provide self-servicing facility for specific user groups 4. Should also provide analysis areas / sandbox areas for specific analysis

Let us also look at some useful architectural guidelines that can help our cause. They are as: 1. Provide an Integrated information platform that makes actionable information available, and decision making easier for the concerned information consumers 2. Reporting Platform that supports standard reports, ad hoc and analytical reports 3. Platform that can be extended to accommodate Dashboards and Balanced Scorecards, for senior management, if required 4. Provide customer segmentation and any other analytical data required by campaign management, web analytics and personalization applications 5. Provide a sandbox / playpen area for occasional analytics 6. Maintain historical data at the most granular level, so that it can be used for performing any kind of analytics Meanwhile, let us look at some of the very important applications like Product Induction Applications and Commercial applications, which create new product offerings, help categorize them, and provide cost price information. Retail supermarket chains keep adding / amending new products almost on a daily basis, and also experience cost price fluctuations (albeit in a narrow range) from their vendors / suppliers. Let us take a look at the last 2 BI categories (before we go on to category 1 for more analysis) namely, Customer Servicing and Business Reporting. Actually, I feel that both the Customer servicing & Business Reporting fall in the same category of reporting. Now I am not comparing them on importance, but the data management and data arrangement portions only. Both these BI Categories need information to their respective users on the following items (not an exhaustive list):

Finance figures on: Sales, Margin, Gross margin, contribution, Payroll, Orders, basket size, promotional sales on various dimensions like Target, Actuals, comparison with previous few periods etc. Customer figures on: Number of new customers added, complaints, refunds, returns, substitution acceptances, product availability, active customers on various dimensions like Target, Actuals, comparison with previous few periods etc. Fulfillment productivity figures on vans, pickers, pick rates, missing items, items per order on various dimensions like Target, Actual, and comparison with previous few periods etc. There will be more interesting items such as: System availability, Advertising revenues, stores utilizations, Basket size analysis, average items per basket, product availability, refund summaries, returns summary, substitution acceptance, website statistics, discount coupons summary, Fraud details etc. Usually, this info on these items is provided to the business users across hierarchies, on a periodical basis. We also need to understand the fact the business users' information needs keep changing quite frequently, and sometimes they also need more information that what is provided to them through standard reports. Sometimes, they also demand information on a more frequent basis. This kind of information availability is easy through proper data management and its arrangement rather than creating complex reports. Creating an aggregated and dimensional layer will be useful for the business users information needs. Using a ROLAP environment is going to be more useful compared to the MOLAP environment, as it involves too frequent cube refreshes. Cube refreshes take more process window, and also necessitates historical data storage and processing. Now, let us take a look at the first BI category "Business Development Area". This covers items like Campaign management & Promotions, customer segmentations, market basket analysis, etc. I recommend creation of some bridge tables to the already existing master data dimensions to indicate these analytical divisions. These bridge tables also prevent frequent updation of the original master data dimensions. These could also help in understanding the history of changes done to the master data dimensions. Analysis areas need very thorough and expert hands to

dissect, analyse and understand data. Usually, the methods used in these types of analyses keeps changing over a short period of time. Creation of data marts etc., to perform these analysis is usually not recommended, as they will use-up lot of memory and hard disk space. Usage of Sandbox / playpen areas to perform these analyses is recommended. These sandboxes / playpens can have minimal persistent data. These kinds of analyses usually require the most granular data. Hence, historical data is also kept at the most granular level. Considering handling loads of data on a regular basis, it is always recommended to use BI Appliances.

These appliances use brute force to handle loads of data to provide useful

information quickly.

Benefits: Business intelligence and collaborative solutions making use of real-time analytics solutions offer the following benefits: o Make faster, more-informed decisions for better overall performance of the organization by integrating and analyzing information from a variety of sources, including a current data warehouse, store transactional information, legacy applications, enterprise resource planning (ERP), customer relationship management (CRM), and external sources. o Improve business processes in areas such as real-time fraud detection, out-of-stock monitoring, equipment maintenance, task management, and optimized processes for cash register and store openings through enhanced integration, analysis, and reporting capabilities. o Use sophisticated analytics to help with price, merchandise, and promotion optimization. For example, retailers can customize the merchandise offer to the profile of a store or channel; maximize sales at full margin when there is the demand; and react quickly to reduce slow-moving stock to make way for new lines. o More easily share accurate product information, with improved communication and interaction with customers, employees, headquarters, and suppliers.

o Enhance customer service levels by supplying employees with product information; the ability to address out-of-stocks; and the ability to handle complaints in real time, through handheld devices for use on the store floor. o Enable suppliers to more easily access appropriate, predetermined information that can help speed replenishment and anticipate stock-outs. This type of collaboration could include sharing sales data, forecasts, and production information, as well as exchanges of documents such as purchase orders, Advance Shipment Notifications (ASNs), invoices, and credit notes.

Synopsis: TODAY IN EVERY BUSINESS the most challenging job is to make you efficient enough for surviving in this volatile market place. The only solution to this problem is to have as much actionable information of the respective field that gives an insight to the current market trend, thereby advocating an intelligent business decision. Business Intelligence tools and software are now used in all most all-major industries and so in the retail sector. BI tools like data warehousing, data mining, and OLAP can help in keeping an eye on different retail organizational functions and hence can play a vital role in analyzing customer behavior that in turn assists to meet their ever-changing needs.