Presentation on theme: "Business Intelligence Solutions for the Retail Industry"— Presentation transcript:
1 Business Intelligence Solutions for the Retail Industry Syscon Infotech Pvt.Ltd.# 250,5B – Sanjay Building, Mittal Industrial EstateMarol Naka, Andheri –Kurla RoadAndheri –EastMumbaiTel:Fax:
2 About UsA professionally managed company with over 15 years of experience spanning Consulting, customized technology development, implementation and training.
3 Syscon Differentiators as a Source of Competitive Advantage Ability toRecommendFocus on Customer needs & Business valuesMulti-Vendor Skills15 Years ExperienceStrong Manpower resources and capabilities.Broad portfolio of solutions and services.Power toImplementSpeed,Quality &FlexibilityProven Methodology and Tools.Full Cycle of Implementation experience.Flat and flexible structure.
4 What is Business Intelligence ? Business intelligence (BI) is a process for increasing the competitive advantage of a business by intelligent use of available data in decision making.Business intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information and sometimes to the information itself.BI systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data. Software elements support the use of this information by assisting in the extraction, analysis, and reporting of information.
5 BI is a set of concepts and methods to improve business decision making by using fact based support systems. It refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information.BI systems provide historical, current, and predictive views of the business operations. They combine data management (consolidating, organizing, cleansing huge amounts of disparate data from varying systems and platforms) with predictive analytics (data mining, forecasting, and data optimization).
6 Relevance of BI in Retail Industry Globalization, deflation, diversification of sales channels and, most of all, changing customer demands have merged to create a cutthroat environment in which retailers struggle to turn a profit. Sales remain flat as many companies don't understand customer behavior and buying habits well enough to make the right decisions about product, price, promotion and placement. And without the ability to explore every facet of the organization across business units and geographies, it can be a struggle to understand and manage the costs and other drivers required to do business.Syscon BI Solutions for retail turn data about customers, merchandise and operations into knowledge that provides greater insight into performance and empowers retailers to make more informed decisions, gain a competitive advantage, strengthen customer and vendor loyalty, and improve profitability.
7 The GapTechnology plays an important role in supporting the backbone of retail businesses. Typically, in a retail environment, operational and transaction systems, such as Point of Sales (POS) systems are efficient in what they are intended to do – record and retrieve large volumes of transactions and operations. Embedded in the POS is a “treasure trove” of dormant often unused information about what has happened in the business in the last week, last month, last year, etc. Traditional reporting systems present historical information in standard static layouts. These reports can neither be viewed from different perspectives at deferent times nor can they provide critical insight for retailers to help them make basic operational decisions.
8 Realizable Value Real value comes from systems that go beyond the limitations of operational software alone, andtake the operational data to create enterpriseintelligence and predictive insights.With this information retailers can make sense ofcustomer, product, supplier, and operational dataand draw insights that will help them run theirbusinesses better and more profitably. This isexactly where Business Intelligence comes intoplay.
9 Data Warehouses / Data Marts: MakingDecisionsData Presentation:Visual, Tabular, Graphical viewsOf the InformationIncreasing Potential to support Business DecisionsData Mining:Discovery of Information from the DataData Exploration:Querying and Reporting the Organized dataData Warehouses / Data Marts:Analyzed, Processed, Aggregated, Organized dataData Sources:Papers, Files, Databases
10 Syscon Retail BI solutions Large to medium size retail organizations have adopted ERPs successfully, resulting in automation of all their transaction processing. This has now created a good foundation (and opportunity) for Business Intelligence applications in terms of:Businesses possess huge and rich data resource.Businesses have seen the benefits of huge investments in IT.Businesses are keen to have insights into their own performance and discover opportunities for improvement on continuous basis.Businesses would like to discover new business opportunities from their existing customer base, market reach and so on.
11 Communications Gap in Business Intelligence Though retail houses implemented sophisticated systems for each functional points, most of the cases that do not communicate with each other not effectively integrated into a common “analytical layer” that utilizes common databases and information delivery mechanisms. As a result, even at the biggest retail chains, the larger dimensions of Business Intelligence — analytics, applications and platforms — can be surprisingly archaic .
13 Customer Intelligence Helps retailers identify, acquire, activate, serve and retain the most profitable customers.
14 Merchandise Intelligence Helps retailers drive revenue, protect margins and earn customer loyalty with optimized merchandise plans, assortments, pricing, promotions – all driven by unparalleled demand forecasting and predictive analytics.We provide complete planning capabilities for the merchandising process, including performance analysis, financial planning, assortment planning and more.
15 Operations Intelligence Helps retailers leverage organizational assets to trade with vendors and serve customers more efficiently and profitably.
16 Supplier Relationship Management Helps establish sound supplier evaluation practices and reduce enterprise spend by consolidating and prioritizing your supplier base and reducing supplier risk. This solution offers strategy alignment ,commodity classification, opportunity exploration, detailed analysis and decision support.
17 Financial Intelligence Helps retailers focus on specific financial business processes – planning, reporting, budgeting, consolidation, risk assessment, forecasting, strategy development, the audit process – and develop more predictive, accurate, relevant and timely results.
18 Human Capital Management offers the organizational insights that enable retail organisations to plan effective human capital strategies and then measure and compare their company's best practices.
19 Performance Management Solutions Provide the ability to analyze, forecast and maximize profits across the entire retail enterprise by monitoring cost and performance, helping retailers drive disparate functional units toward common goals.
20 Activity Based Management provides accurate financial information in a form that mirrors the day-to-day activities of the people, equipment and processes that directly impact a retailer's bottom line. This solution provides profitability analysis and forecasting to help retailers look to the future with a reliable picture of operating costs.
21 Strategic Performance Management allows executives to track key performance indicators (KPIs) across the entire retail enterprise, from merchandising and marketing to distribution and store operations, to analyze, learn and plan strategically. Executives can then quickly communicate goals and strategies throughout the organization.
22 Skill Set Data Management Manage large volume of data OLAPBuilding data ‘cubes’Studying datapatterns by slicing,dicing and drillingMaking inferenceStatistical AnalysisExploratory analysisConfirmatory analysisModel buildingSimulationsData MiningSamplingBuilding valid modelsMaking predictions –scoringData ManagementManage large volume of dataBuilding Data Warehouse or Data MartBuilding OLAP CubesBuilding ETL processes for extracting and transforming data from independent systemsWorking on multiple platforms – MS SQL, Oracle, SAS
23 Analytics Scope - Illustrated What sells where and howProgramsPromotionMembershipChannelMarketProductLocationTimeKey Data ElementsSales and Growth (Targets if Any)Frequency of PurchasesAvg. Sales Value per TransactionAvg. Sales Value per Customer per MonthNo. of Items per TransactionAnalysis Techniques (Illustrative)Data MiningClusteringMarket Basket AnalysisStatisticalDistribution AnalysisPareto AnalysisTrend AnalysisCorrelationsOLAPHigh performersLow performersOutliers
24 People Team of 150 people consisting of: Statisticians (Ph.D. and Masters in Statistics)Statistical software developers (Masters in Statistics)MicrosoftSASData Analysts and Business Intelligence solution designersand developers (MBAs and Masters in Statistics)Data Managers (MCAs)Information Technology managers (Engineers and MCAs)
25 Execution Approach Set Up BI Platform Build Data Warehouse, including DataCleansingData Updated – Weekly / MonthlyProvide on-line access to Client Managersand Agency ExpertsTheme based Analytics ServicesResults to be Published on BI Platform
26 Critical Success Factors Executive sponsorship is key for corporate supportDecisive project managementProactive management of scopeMeeting deliverablesUnderstanding the solution is evolutionaryDedicated project team resourcesData quality extracted from source systems
27 Primary factors impacting the length of a DW&BI project In general, a DW & BI Project will be of shorter duration and will more likely be successful if:A predefined data model, specific to the industry, is used,the team is skilled and committed,the team includes end users who understand the business processes and their data,there is a clear, valuable objective of the project,executive level support is strong,the source system(s) is well-defined; andthe technical support team is strong (data integration, data modeling)
28 Typical BI & DW projects risks Project scope not defined wellBad communicationNo decisions & decision escalation processesLack of or little management supportCustomer team availabilityIncomplete or missing data sources
29 Syscon ExperienceSyscon brings rich experience in BI-DW space with several man-years of design and development experience. Important projects executedTarget, Profit Logic – End to End BI Consulting and solution delivery.Bharat Petroleum, India – monitoring or refinery production and inventory movement.One of the largest news papers in India – monitoring of advertisement share of different media / publishers.Large hotel in India – monitoring of occupancy, customer acquisition / churn and profitability.HR Management for a large Software company in India – monitoring manpower addition, churn, deployment and movement.
30 Current Projects in India Aditya Birla Retail Ltd.- Creation of a integrated BI platform and portal.Shoppers Stop Ltd.- BI Analytical tool for the study of re-order behavior.Planet M – End to End to BI Platform.
33 Goals of Loyalty Program Increase MembershipsIncrease Sale Value Per Member per MonthIncrease Realization per BillIncrease in Basket SizePromote purchase of higher value itemsPromote sales of Private Label products
34 Service Level Established Service (Measure)Level EstablishedUpload Sales Data (Days from Receipt)1 (Monthly – should be weekly)New Report (Days from Request)1On-line Access to BI Platform24x7Performance Analysis ReportsWeeklyProgress Report
35 Contribution by Top 25 Cities/Stores to Membership
37 Which Cities/Stores Give High Value per Bill? Note High Sales Value Cities do not give High Value per Bill
38 City A: Membership has stopped Increasing but Sales to Members is Increasing
39 Average Sales Value per Member Average Sales Amount Per Member (INR)Time Year MonthTotal% Change(Jul)335(Aug)45335.34%(Sep)4826.31%(Oct)475-1.42%(Nov)52911.37%(Dec)5728.15%(Jan)550-3.90%(Feb)540-1.84%(Mar)5919.39%Average Growth7.92%