What is a Demand Signal Repository?

Business Intelligence Executive Overview

Presented by Janet Dorenkott [email protected] 440-899-3296 x225

Understanding the DSR Market

Hosted by Karen [email protected] x232

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Janet Dorenkott, BioOver 20 years of experience in information technology. Founded Relational Solutions in 1996 and co-owns with Rob York. Focused on data warehousing, data integration & business intelligence solutionsSpecialize in the complex issues associated with integrating point of sale and syndicated data for the CPG industry & developed applications including POSmart and BlueSky, designed for handling data complexities unique to CPG companies.Member of Retailwires BraintrustFounder of the Demand Signal Repository Institute on LinkedIn.Participated in the implementation of over 200 data warehouse and BI projects for companies that include Chrysler, Chase, Timken, Xerox, Glaxo, Smuckers, P&G and many others.

Property of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Janet has over 20 years of experience in information technology. She started her career with her own desktop publishing business in the late 80s. She worked for a network protocol analyzing company in the early 90s and moved on to Sybase, a database technology currently owned by SAP. In 1996 she founded Relational Solutions and co-owns the company with Rob York.

Relational Solutions has been implementing data warehouses and business intelligence solutions since 1996. The complex issues associated with integrating point of sale and syndicated data led them to their focus on the consumer goods industry, where they have developed applications including POSmart and BlueSky, designed for handling data complexities unique to CPG companies.

Janet is a member of Retailwires Braintrust and founder of the Demand Signal Repository Institute on LinkedIn.Relational Solutions has been recognized as leaders in the area of data integration and business intelligence. They have won numberous awards and have published success stories. Theyve conducted classes for large software companies as well as customers and have been involved in over 200 data warehouse/BI projects, including implementations for Chrysler, Chase Manhattan Bank, Timken Industries, Xerox and others.

With that, Ill turn it over to Janet to talk to you about Big Data. Janet, thank you for joining us today.2Page #

Goals for TodayDescribe DSRsExplain the difference between a Team DSR versus an Enterprise DSR.Offer a methodology and process to start with embarking on a DSR projectProvide expected time frames and benefits.

My goals for today are to Describe DSRs, Explain the difference between a Team DSR versus an Enterprise DSR.Offer a methodology and process to start with embarking on a DSR projectProvide expected time frames and benefits.

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Top 10 Companies on the MoveAcquired BlueSky Integration Studio Best at integrating POS with Internal dataCleveland Weatherhead 100Fastest Growing Businesses

Oracle Developer of the Year

Data Warehouse & BI Consulting

BlueSky Coolest New Technologies

DataStage ETL Best Implementors AwardInformaticas Partner of the Year

Selects BIS to integrate POS & TradeEdgeSelects POSmart to embed in DSR

Best Software Finalist

Company Background

Data Warehouse of the Year!

SAP Certification & PartnershipBest of Cleveland AwardCGT Readers Choice Award


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What it isThe ProcessThe BenefitsA process that on a scheduled basis, integrates POS data into an centralized database for sales reporting.

An Enterprise DSR A central, integrated, truth database with clean, valid POS data that also integrates internal data, third party sources, loyalty data, social media, and any other data source. The architecture is designed with modifiable business rules and the data model supports easy management, growth and change. Supports sales reporting to retailers as well as reporting requirements across many departments.

Set up of jobs that integrate data from multiple data sources. Start with most critical retailers to provided the quickest ROI.

Automated processes that integrate data seamlessly.

Manageable solution that allows for quick notification of data issues and fast resolution to errors.

Data validation process with end users to confirm data is clean and in a format ready to present to retailers, management and other team members.

Improved retailer relationships

Faster access to information

Increased Productivity

Optimized Efficiencies

Maximized Sales

Reduced Costs

Increased Profits

Demand Signal RepositoryProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

So what is a DSR. A DSR is not a thing. It is a process that on a scheduled basis, integrates POS data into an centralized database for reporting.

An Enterprise DSR should be a central, integrated, truth database with clean, valid POS data that also integrates internal data, third party sources, loyalty data, social media, and any other data source. The architecture is designed with modifiable business rules and the data model should be easy manage and designed for growth and change.

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Costs, Savings & Profit!Issues related to OOSIssues related to shrinkInventory CostsInaccurate ForecastsPromotional Costs versus EffectivenessNeed to Improve SalesNeed for Improved EfficienciesAchieving Competitive Advantage

Why is DSR such a Hot Topic?Property of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

so why are DSRs are such a hot topic? The answer is I return on investment. The benefits of implementing a solution that can help you understand your business better and improve your retailer relationship is significant. Not only can companies identify it the hard costs associated with improving out of stock in managing your inventory better but they can also measure ROI by looking at soft benefits as well . For example how can you understand the value of improving your retailer relationships? How can you understand the value of understanding your customer better? How can you put a value on knowing your business more intimately and being smarter about your business?

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US Retailers average approximately 8% OOS during non-promotional periods (Gartner/AMR)US Retailers average approximately 15% OOS during promotional periods (Gartner/AMR)4-8% of sales are lost due to OOS (GMA/FMI)Cause of OOS (Roland Berger ERC)28% due to manufacturers process (case fill, On time delivery & promotion execution)72% OOS caused by retailers forecasting, replenishments and store operationsHuge ROI PotentialProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

this slide gives the some examples of the cost of out of stock for the different retailers. It also gives us a better idea on measurable ROI and how the DSR can help improve ireless Page #

Average supermarket shrink is 2.5% of retail salesBest in class" retailer shrink is 1.5% of salesShrink costs retailers and shoppers over $60 billion each year. Shrink increases the jobless rate grows or stagnates at high levels10% reduction in shrink, delivers the same bottom line benefits as an 18% increase in salesExamples of ROIProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Again, this slide gives examples of where ROI can be achieved. I also have a few examples of ROI comments given by our customers toward the end of the presentation.Page #

Term coined in 2004 by Lora Cecere of AMR & Kara Romonaw of CGTDemand Signal Repository/Demand Sensing RepositoryTypically refers to point of sale/scanned data.Sources include retailers i.e. Food, Drug, Mass, Big Box, Specialty, Department stores, Distributors, Military, Syndicated data, etc.External Formats typically include: EDI, AS2, Retail portals, flat files, third party (FTP), csv, etc.Internal data: SAP, Oracle, SQL Server, Sybase, Access, DB2, MF, Excel, JDE, JDA, etc.Relational Solutions coined the Enterprise DSR and founded the DSR Institute on LinkedIn.

DSR HistoryDSR HistoryProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

so the DSR history is that the term was coined back in 2004 by Laura cesare & karen Romanov. Today we hear it referred to as the demand signal repository, demand sensing and demand management among other things.

A DSR refers to a database containing pos data. It can you include POS from retailers or data coming from third-party data providers like me AC Nielsen, IRI, NPD and others. Relational solutions actually coined the term enterprise DSR to differentiate between point solutions designed for retail reporting and enterprise solutions designed to support the overall business 9Page #

Demand data can be used to create reports regardless of architecture. Data providers trying to redefine themselves. All vendors claiming to be a DSR out o necessity and ignorance.Analysts & Vendors Caused ConfusionIndustry focused analysts understand value of demand data & reporting needs (not much about architectures)Technology focused analysts understand technology (not as much about the business value)Vendors In this industry are traditionally report focusedArchitectural differences Team/Departmental DSRs (silos) - ToolEnterprise DSRs Process & ArchitectureConfusion between operational reports and analyticsWe coined Enterprise DSR to clear up confusion, but now everyone claims it.Confusion in the MarketProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

There is a lot of confusion in the market today. Because the term, DSR, was coined by analysts who specialized in supply chain analysis, they started throwing every company that could provide sales and OOS reports into the same group. Although they are very knowledgeable of the supply chain, they were not technology experts.

As a result, they did not have a good understanding of architectures. So if you had reports that used POS data, you are a DSR provider. In order to try and clear up confusion, Relational Solutions coined the phrase, Enterprise Demand Signal Repository. We did it to explain the architecture differences. Unfortunately, vendors in the space, who didnt want to appear as a point solution, started using the terminology and analysts who again, didnt understand architectures, started using the term as well, without attempting to differentiate them at all. Therefore neutralizing any of our attempts at helping to clear up the confusion.

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Kroger/Publix/Food Lion/RSICostco/Sams/Promo/ForecastsShipmentsOther POS dataEDI/FF/txt/Access, etcOfficeMaxxAC Nielsen/IRI/Spectra/TD Links/etc.

Submit Reports

Most time spent gathering disparate data

GatheringCleaningIntegratingJustifying

?

Inconsistent reports leadto questionable decisions

Target/Giant EagleWal-Mart, Retail LinkEDI/AS2

??????

Home Depot/MeijerPOS Data DilemmaProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

So Im going to start off today with a basic slide that I think very nicely, depicts the POS issue. In the consumer goods industry, you get data from so many different sources. Each source produces its own reports. Analysts spend an average of 85% of their time gathering and pulling together data. When there are discrepancies in the data, Analysts spend more time trying to figure out where the numbers came from. This is a very tedious task that keeps analysts from actually Analyzing the data.

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Enterprise DSRPOSmart

Consistency

Easy Access to InformationImproved Productivity

Streamline DataGathering

Synchronize, Integrate & Validate POSWal-MartEDI /AS2/Retail LinkPromo/ForecastsKroger/PublixNielsenShippingSams/CostcoWalgreensIRIEDI, AS2Target/POL/IRCVS/RSIOffice Max

Productive MeetingsIntegration & HarmonizationProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Data from different sources often leads to a lack of consistency in reports. Peoples numbers dont match and there is a lack of confidence in the data. Analysts spend countless hours trying to manage data discrepancies. Page #

InformationTime

RISK10 DaysEarliest Point when an Accurate Decision can be madeAmount of Information Needed to make an accurate decisionHow Long Does it take to React?Property of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

The idea behind implementing an enterprise solution is to provide a significant ROI to the business.

The longer it takes for people to get answers to questions, the greater the risk involved. Risks include losing sales, a retailer dropping you, making a costly wrong decision, providing inaccurate information, compensating the wrong sales rep, negotiating the wrong discount from a vendor, etc. There are countless issues with having too little or inaccurate information. It all costs the company money.

If a decision needs to be made and all the accurate information has not yet been gathered, that doesnt stop from the decision being made. Rather than having all the information necessary to make an accurate decision, they have to rely on hunch. There is a great deal of risk involved in making hunch based decisions.Page #

InformationTime

LOWRISK

Additional InformationAvailable when integrated

Amount of information currently available to make a decision1 Day

IncreasedEmployeeProductivityEarliest Point when an Accurate Decision can be made is now 1 dayFaster, More Reliable, Consistent InformationProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Providing information to users faster will give decision makers fact based decision capability. Not only will it reduce the risks associated with guessing, it will improve the accuracy of their decision. It will also increase employee productivity. Time once spent gathering information will now be spent analyzing the information and providing MORE information to decision makers. Analysts can actually analyze information rather than spend time gathering it. There will be more information available than ever before and users will have the ability to discover trends and information never before available to them.

So how is this related to a team dsr versus an enterprise dsr?

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Category ManagementForecastsPromotionsNew Product LaunchInventory ManagementSupply Chain Management

Enterprise Integration EngineProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

An enterprise DSR leverages an infrastructure. It has the ability to not only integrate data from many sources, it has the ability to cleans and harmonize that data into a single source of truth.

A true enterprise solution not only integrates new sources of data, but it does so in a way that is both flexible and easy to manage.

Anyone can write code to integrate new data but that doesnt mean there is a long-term infrastructure to support it. Well talk about that in a few slides. But with the right architecture, an enterprise DSR will not only provide reports needed by category and sales teams for their retailer reporting, but it will also support other aspects of the business to help with supply chain issues, marketing effectiveness, forecast accuracy, management reporting and more. 15Page #


Transactional systemDatabase structure designed for data entry, update, and processing.Operational Reports. Reporting users can impact processing - quickly becomes a slow environmentPurchased applications contain standard reportsInconsistent due to twinklingNo access to some infoReports can take days or be impossible to getNormalized model for fast input Data warehouseData model designed for analytical reporting and ad-hoc queries, both from a creation and a performance standpointFrequently contains detail data and pre-aggregated summaries for fast reportingTools allow end users to inquire, drill from summary to detail Reporting users do not impact the transactional systemOften combines data from multiple transactional systemsConsistent Business Rules Typically DenormalizedTransactionalSysteme.g. SAPJDEOracle AppsJDAHomegrown

DataMartPeriodic Data FeedsDataMartDataMartDataMartDataMartDataMartTransactional vs. Analytical Reporting

This is not going to be a technical presentation. Im using this slide and the next to describe, in layman terms, a brief background and description of different types of reports.

So, transactional versus analytical reporting. The easiest way to understand the differences is to think of Transactional systems as those applications that are designed to run your business. Applications like SAP, Oracle Financials, JD Edwards and JDA for example, are transactional applications. These are systems that are modeled for data entry. They are updated constantly throughout the day.

Reports derived from these systems are reports designed to understand what is going on at this moment. For example, what time did my last truck leave? How many pallets shipped today? These are operational reports and your day to day operations depend on them. A report pulled from a transactional system at noon will produce different results than a report pulled at 12:01 because the transactional system is constantly changing. Even reports pulled symotaneously will likely produce different results because of the path each query might take, and who might be updating the system at any one point in time. We call this the twinkling database effect because the data is always changing.

These twinkling databases are fine for pulling operational reports. But trying to produce an analytical report from an operational system is not wise.

First, the data is formatted for entry, not retrieval. Therefore it could can take days to query the system. In addition, this will effect the performance of the operational system as well as the end users trying to enter orders and perform other job functions. Analytical queries will put an undue burden on your network if made against transaction systems. In addition, it will return inconsistent and often times, inaccurate results that could lead to catastrophic decisions.

(click) Thats why data warehouse solutions became popular. They are designed to provide business intelligence that will help companies manage their business. Transaction systems are designed to RUN the business, data warehouses are designed to help MANAGE the business. The database is modeled in a way that business users can easily find and retrieve the data they need. Query tools allow for easy analysis and fast capability to drag, drop, drill, sort, compare and learn about your business. More and more, we are hearing business analysts be referred to as Data Scientists. Because rather than just gathering and reporting information. Data can be put into a usable format for data exploration.

(click) The data warehouse is fed by the operational system and other sources. And is typically updated on a nightly basis. Sometimes more often but most often, nightly.

A data warehouse produces business intelligence reports just like a DSR. An enterprise DSR should work in conjunction with an enterprise data warehouse and even integrate into your enterprise data warehouse if you chose to do so.

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Team/DepartmentalLess expensiveSupports a specific retailer Team & designed for that retailerSpecific reporting needs for buyers (Monday morning reports)One group is main decision makerSilos

Enterprise/OperationalMulti-RetailerDesigned to integrates any data type, including internal dataAbility to integrate silos and Team DSR dataUsers desire to provide additional insightCorporate initiative designed to leverage demand data for many groupsSupports Management & Enterprise reporting needsDesigned for growth & changeRetailer SpecificReporting NeedsSupport Retailer & Internal Business NeedsTeam vs Enterprise DSRProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

So why do we work so hard to differentiate between a team dsr and a true, enterprise dsr? Quite honestly, because most of the vendors dont even understand that they arent enterprise solutions. Most of the vendors in this space actually came from the reporting side. But any IT person can tell you that reports are the easy part. Getting an infrastructure in place that will provide cleansing, validation, alignment, longevity and a manageable solution is the hard part. Anyone can take data from a retailer and create reports. Thats why there are so many vendors in this space. The key is making sure that data is valid and easy to report off of. Otherwise, you have unreliable reports and if they are wrong from time to time, they are useless.

With that, lets discuss how you can tell the difference between different offerings.

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Querying Transaction databases with Access or ExcelSources

Access, Excel & Pivot Tables are Not an ArchitectureProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

If you are accessing a tool that downloads retailer data into Access or Excel to create reports, you are using a team DSR. It has demand data and you might use it to create your retailer reports, but no one else from the company is using it. It is not an enterprise solution. Nor will it become an enterprise solution as vendors typically tell you it will. Page #

Data Movement

QueryingSources

Replicated Data is Not an ArchitectureProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

If you are taking EDI data and storing it in a database somewhere to do some minimal reporting, this is not an enterprise solution. We often hear from IT that the users have the data. More often than not, IT has just taken the data that the retailers have sent them and thrown it into a data base somewhere. The business users may be able to access it, but it is not easy. Its also not in a format they can use. Often there are EDI files are very cryptic and unusable in their raw format. Just because its there, and its in a big database, doesnt mean its clean or usable.

The only thing the replicated data is good for is to access history that might one day be used in a true, enterprise infrastructure. Page #

QueryRetailLink/Shiloh/etc.Accessing a Retailer Portal via third party tool is not an Enterprise DSR Architecture.Property of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Retail Data warehouse

We often hear companies say they have a DSR because they have Retail Link or Solyce or Shiloh. These are just a few examples of what we would term Team or Departmental DSRs. These are tools that were designed to access specific retailer portals. Shiloh for example was designed for Walmart which is why the company name used to be Bentonville Software. Some point solutions understand their strength and focus on focus that strength. Others claim to be enterprise solutions without having a good understanding of what the requirements of an enterprise infrastructure. This has lead to a lot of confusion in the DSR market.

Just because a company recodes processes to extract data from new retailers, so they can call themselves enterprise, does not mean they are enterprise. In most cases, they are still selling silos of information, which is not enterprise. Page #

Data Movement

SourcesQuery

Direct Cube Loading is Not an ArchitectureProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Taking raw data and loading a data cube goes directly against all data warehousing fundamentals. This is a point solution, not an architecturally un-sound plan. The nature of a cube is that it expands exponentially. So as data is added to the cube, the cube creates its calculations and the data expands by several fold. For example, you could put 1 gig into a cube and it can easily become 4 gig.

Cube technology is often called OLAP. It is great technology and an enterprise solution, including our POSmart architecture does leverage cube technology. However, cubes should never be used as the main target of all data. Cubes have their place, but not as the enterprise DSR target. Page #

Receive Retailer POS

SourcesUsers Access & Download Retailer reports

Data Provider Reports for Retailers are Not an Architecture

3rd Party Data Provider Creates Retailer Reports & Sells you reports you pay forProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Third party data providers who offer all sorts of retailer reports with a whole bunch of measures and reports that you can chose from, are not enterprise solutions. They are retailer reports. You can buy raw POS data from them or you can buy the reports they create. You can pick and chose reports you want, but the bottom line is that is a SaaS model, that means software as a service. They are hosting the data and telling you what options you have. You are not telling them what you want. They are not integrating your internal data. There is a difference between SaaS solutions and Hosted solutions. Relational Solutions offers both an in-house or hosted option. The hosted option is in our data center, but we are still integrating it and customizing it with data from your internal systems to provide additional value to other departments along with category management and retail team requirements. Page #

Shipments

Difficult to ManageCode for each data sourceInconsistentWritten by multiple peopleShort lived ArchitectureTargetCVS

Integrated Information

Where is the New Product Info?We just bought OracleCVS just bought another Retail ChainWe just switched shipping companiesWe bought a new Manugistics AppWere merging with our competitorOur Products were re-categorized

Coded Integration Processes is Not an ArchitectureProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

This is the most dangerous architecture for a CPG company. It is expensive and believable. Imaging the 3 cylinders on the lower left are data sources. A vendor has coded Modules by retailer. For example, a vendor might have processes to extract data from Walmart and load it into a database. They also have coded processes, or Modules, they use to extract data from other retailers. Those people who have been in data warehousing for years, remember the data warehouse failures of the 90s. The reason for those failures were that companies were coding all the integration processes. Thats why ETL tools became popular. ETL tools made the integration processes manageable.

Coding a DSR is unmanageable in the long run. That is why we typically see companies out there marketing as an enterprise solution, by in reality, most implementations have only 1 or 2 retailers integrated. They do not have a true integration engine, they have code which is custom and requires the vendor to integrate new data and make changes. The problem with the code is that every time the source data changes, code has to be changed to reflect the changes. Also every time the users want something new or you implement a new application or there is a merger or you get a new customer, someone has to find and correctly alter that code. It eventually breaks under its own weight because the changes become too frequent for the developers to keep up with. Costs get out of hand bringing the consultants back in and the entire thing eventually becomes a throw away.Page #

Military, Distributor

Budget

Nielsen, IRI, TD Linx, etc.

Shipments

OrdersReportsScheduled

Forecast

SourcesRetailers WalMart RiteAid Costco Kroger/DunH Giant Eagle Sams Distributors

POSmart

Integrate, Validate, Synchronize & Manage

BlueSkyOr other BI Tool

Can feed other systemsPOS IntegrationEngine, BIS

EDI, Text, Flat Files, Access, Retail Link, PartnersSAP, JDE, DB2, Oracle, JDA

Users access via web

3rd Party Data:AC Nielsen/IRISpectra

ForecastShipments, Promo, Vendor

Promotions

POSmart

POSmart Enterprise DSR ArchitectureProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

The POSmart architecture is open. The data base is independent and can reside on Microsoft, Oracle, DB2, Teradata, Hana and others. Our architecture uses an actual engine that can access and target virtually any data source thus allowing you to integrate other internal data with POS. Common integrations include forecast data, syndicated data, promotions, shipments (for ship to consumption reporting), etc. As you learn more about your sales, POSmart lets you grow that knowledge by integrating more information, creating new reports and KPIs. End users can also use other query tools in addition to BlueSky. The open architecture of POSmarts database allows other query and reporting tools to access POSmart. The processes are all self documenting throught the graphical interface. In addition, management processes are set up to alert you if certain thresholds arent met or if there is an issue that goes outside the rules we set up for the data. Users can easily access information and reports are automatically cached on the server so they are waiting for the users every morning. But they also have the ability to create new reports and even pull together data from multiple sources and join them together in a single report. The infrastructure is designed to be in incremental approach. Therefore we can deliver information that will offer you the greatest ROI in the first phase of the project, but you can continue to add new data as the needs arise. Page #

Account Reporting

Integrate & HarmonizeSyndicated

SAP/ERP

Orders/Shipments/BillingMasterData

Nielsen/TDLinx/IRIItem MasterItemTimeStoreIRIItemsNielsenItemsConformedDimensions

WalmartSafeway Retailer X, Y, Z

Validate & Cleanse

POS & InventoryPOS & InventoryPOS & InventoryPresentationDatabase

End User Analysis& Internal System FeedsInternal Reporting

Category Mgmt

Market Analysis

Supply Chain Optimization

Inventory Optimization

On-Shelf Availability

Forecasting

Account Reporting

POSCategoriesShipmentsPromotionForecastsSyndicatedPlanogramLoyaltySolution supports the needs of both the team and the enterprise

Feed OtherSystemsMultiple levels of SecurityProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Security is a necessity. In an enterprise solution, security needs to occur at multiple levels. So only those who have permission to access certain data can have access to it. In our POSmart architecture, even if an administrator accidentally sends a report to the wrong person, it wont populate because of our strict security.Page #

Enterprise DSR

Account ManagementSales Teams

Where am I OOS? What is the potential impact on sales? What products and stores are most profitable? How can I serve the customer and my retailer better?

Category ManagementMarketing & Sales Teams

How can I manage my shelf space better? What is my market share? How can I help my retailer sell more product?

ForecastingSales, Forecast, Manufacturing

Are my shipment & order forecasts accurate? Can I automate sales forecasts? How can my sales forecasts be more accurate & help mfg?

Alerts Pin-Point Action ItemsEasy Access to Accurate Information, Robust Analytics POS Data Third PartyLogistics Supply Chain, Inventory

What shipped vs. what actually sold? Where is Shrink occurring? Do I have OOS products at the DC or at least in transit? Do I have product on order? Harmonized, Synchronized, Clean, Valid, Truth Data, Streamlined Efficiencies

Promotion ManagementMarketing & Sales

Are my promotions effective? How do I minimize deductions? What demographic areas & media are my promotions most effective in?

Internal Data Loyalty, Social, etcDemand InsightsMarketing

Market trends? Who is buying my product? What and where are they buying? Are they loyal? What else are they buying?


26A true enterprise solution should support many teams within a company. The account teams should have access to certain information needed for sales. Marketing teams should be able to see promotions, in flight as they are occurring and impacting business every day. Supply chain teams should be able to identify where issues are occurring on a daily basis. Page #

Leveraging Loyalty DataMarket Basket AnalysisImprove understanding of shopper behaviorIdentify and reward best customersTarget shoppers effectively with mailings, coupons, and other promotionsBuilding upon the share of customer Identify customer share-of-wallet [SOW]Improve understanding of shopper behaviorDevelop Expectations based on observed spendingIdentify Loyal versus Non-loyal customers

Leverage Loyalty DataProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

In an enterprise solution, youll be able to leverage new data as it becomes available. Loyalty data coming from retailer for example can help you target shoppers more effectively and increase sales with new offerings and reward your best customers.

The same is true by integrating other new data such as emerging market data or social media chatter or click stream analysis. The more information you have, the better because now youre not just storing it or looking at it like, what am I going to do with this? Now all that data can be leveraged and insights can be gleaned immediately if you have a sound enterprise infrastructure in place.Page #

Integration of Call Center, Returns, Social Media, etcBuilt upon mathematics, probability, statistics and database technologiesRisk Management (Spearheaded by Insurance Companies)Customer defecting (Retain Customers likely to leave)Risk of Fraud (credit card purchases, bogus claims, returns)Precise Target Marketing & Sales ActivitiesNot responding to expensive mailerSuppress Customers not likely to respond saving costsTargeted for phone solicitationRefine buying patterns & Trends1% Improved operating profit margins* 6% increase in customer retention** Eric Siegel, Phd., Columbia University

Predictive AnalyticsProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

On top off identifying insights, measures can be added to create predictions. You can even leverage other solutions that might have measures pre-designed. Page #

Syndicated DataSAP/ERP/CRM

Retailer POS

OLAP

Cached Reports

SpecializedAnalyticsMktg/CRM

SupplyChainManufacturing ForecastsDemantraAgilityManugisticsFeed Operational SystemsPOSmart EDSRSource Data

Feed BI SystemsPOSShipmentsSupply ChainForecastsMaster DataFinance

Leveraging the Future

An Enterprise DSR ArchitectureProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

An enterprise DSR will not only support your business intelligence needs for category managers, brand managers, marketing teams, logistics and executives. It will also have the capability to feed that clean POS data into new solutions that take your teams to the next level in predictive analysis, marketing, forecasting, etc. Page #

Transactional/ERP

Accounting

Shipments

Order Processing

ManufacturingAnalyticalBig DataPhotosSyndicated DataWeb & Outside Data Sources

EDW

CRM

SegmentationPanel DataWholesaler, Distributor & BrokerPromotion ResultsWeb LogsCurrency ConversionWeather TrendsEDIRetailer POSWeb Logs3rd Party DataClick StreamAudioTextual Content Reputation ManagementVideoSocial Media ChatterBlogsLocation Info3-D Content SchmaticsGeo-SpacialSpeech to TextSMS/MSSDemographicsLoyaltyEmerging MarketProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

The Big Data Evolution

On top of that, a true, enterprise solution will support not only new data like loyalty and emerging market, but also big data. Ive written many blogs, articles and chapters on big data. Id hightly suggest you take a look at tem because there is a lot of confusion in the market about what big data is. So I thought Id use my favorite slide to explain at a high level what big data is.

It started with data from applications designed to run your business. ERP or Enterprise Resource Planning, applications, really took off in the 80s and 90s. (click) Companies like SAP, Oracle, Microsoft, Sas & JD Edwards all offer ERP solutions. These are applications that include manufacturing, logistics, accounting solutions. Systems that let users place orders, answer customer services calls, and so on.

(click) In the early 90s companies started getting serious about using the data to improve knowledge, business processes and profits. Data warehousing was at its infancy. There were a lot of failures when companies would spend lots of money to build a data warehouse and they still had inconsistent reports and trouble creating reports.

Thats actually the reason we started Relational Solutions While most consulting companies were focused on Y2K compliance, we focused specifically on the integration of new data types and applying that to an architecture that would provide new business intelligence and insights to our customers over the long term.

(click) Next came cooperation between partners Retailers in the late 90s thought we were crazy to suggest they share POS data with the vendors. But today they get it. Now more outside partners and vendors offer new data & insights. Companies like IRI, Nielsen and NPD offer syndicated data, panel data, demographics, currency conversions and so on. Today, there is also a huge demand to integrate emerging market and loyalty data. Other sources include wholesalers, distributors, brokers and other selling partners.

(click) Now, the latest evolution is called Big Data. Combined, its all big data, but in the pure sense of how software companies refer to Big Data today, they are mainly talking about data coming in from the internet. This includes social media chatter that comes from Facebook, Google+ & Twitter. It also includes Comments, Announcements and posts from professional networking sites like LinkedIn. These are the common areas that people think of when it comes to big data. But there are many other areas listed above.

Think about gaming, speech to text, and things like video content found on YouTube. Theres goe-spacial information or location information associated with application like Waze, Friend Locator and GPS mapping on Google Maps. QR codes that let you download product and seminar information for example. Location information is used by companies to do things like track shipments, identify missing cars, monitor storms, and so forth.

By taking that unstructured data and putting structure to it, we are able to leverage that data to provide new, valuable insights. 30Page #

Leveraging Social Media


This is an example of where weve leveraged chatter to understand if we can identify where there is positive or negative sentiment about our brands and what is being said out there. It gives us direct contact with the customer.Page #

Databases

Integration/ETL

Business IntelligenceSQL ServerNetezzaDB2TeradataSybaseOracleInformixBIS - BlueSky Integration Studio

DataStage Informatica

SSIS/DTS

BlueSkyCognosBusiness ObjectsMicroStrategyBrioDiscovererAnalysis ServicesSPSS (Predictive Analytics)

Tools of an Enterprise DSRExpertise, Expertise, ExpertiseProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

If you were to build your own solution, it would be like building your own data warehouse. Except you would need to understand how to fix all the nuances of POS data. You would also need to know how to align hierarchys, manage new POS feeds, create multiple calendars and reports related to what the business teams want. You would need a database, an integration engine and BI tool. You would need to design a data model and create business rules along with mappings for the retailers. Its not an easy thing to do and thats why we built our solution. A company is 80% of the way there when they leverage our POSmart infrastructure. Page #

POSmart ArchitecturePOSmart IntegratorPre-built retailer mappingsPOS Integration processCustomizable validation RoutinesIntegration objects for Oracle, SQL Server, DB2, Excel ODBC, OLEDB, Teradata, Neteeza, SAP, RL, txt, FTP, Access, etc.SAP DSiMFlexible Data model Design/Retail Calendars/Report MatrixControl Center EditorBlueSky Server & Semantic Layer Analytics, Viewer & ReaderXL Builder BlueSky DashboardBlueSky ReporterPost Promotion Analytics/TPO

POSmart Enterprise DSR SuiteProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

POSmart automates the integration, cleansing and harmonization of POS data with internal and syndicated data as well as other outside data sources. The front end product suite includes analytical tools, a dashboard, reporting tools and editors. Our category management, inventory, forecasting, supply chain and marketing reports leverage the clean POS thats housed in POSmart. If you are interested in seeing a demo of our POSmart suite, please contact Karen and we will schedule a demo specifically for your company.Page #

Improve todays business effectiveness NOW while looking to leap into the future . . .

Enterprise DSRs are Designed for Growth & ChangeProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

POSmart is an Enterprise DSR that addresses the current needs of the business today. It also provides additional information to the business users and allow them to think more strategically about how they can leverage the data to support their retailers and internal company departments better. POSmarts architecture can be leveraged for the future and support the long term vision of the company. Page #

Incremental approach leads to overall data consistencyA staging area is required to cross reference, integrate and synchronize dataStar Schemas are required for certain databasesArchitect before loading cubes Business rules are defined & agreed uponSingle source of information The truth databaseKnowing what a sound architecture is

Architecture FundamentalsProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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In-HouseASP/ HostedIn-House Managed (IMS)Any DatabaseAny Query ToolSource or Target Any Database

A Sound Architecture is Flexible With Many OptionsProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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Identifying Business SponsorBusiness Analysis/Identify business needsDefine Business ProcessesArchitectural Scope - Hardware, software & designIdentify roles requiredIdentify sources, targets, middleware requirementsIdentify tools to be usedDesign data model, mappingsCleanse dataExtract/Transform/LoadImplement change data if neededAudit dataImplement/customize/design front end toolPilot data warehouseKeep it simple and manageable to support end users & ITManagement of MetadataIdentify Future PhasesThe ProcessProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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Requirements gathering / data model X weeksIntegration of Master Data X weeksUpload of History X amt. of timeSource Data integration X weeksSource data extraction X weeksData Cleansing X weeksStaging development X weeksData mart development X weeksQuery tool implementation X weeksUser acceptance X weeksProduction deployment X week

Defining TimeframesProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Establish timeframes for each phase and map them to the appropriate resources. A data warehouse should leverage the skill sets you have in house and bring in a few relevant experts in the areas of business analysis/data modeling, ETL and front end tool implementation. A team of a dozen people is unnecessary if building the application in an incremental approach.Page #

Improved Retailer RelationshipsBetter recognition and reduction of out-of-stocks.Improved demand forecasting through more granular demand inputs.Improved optimization of supply chain.Better and timely collaboration with retailer partners, through shared insight, can be game changingImproved success of new item launches at the retailer and store levelMaximized ROI on trade promotion activitypre, in-flight and post event analysis.Improved product development through enhanced consumer insightBetter visibility of product movement off the shelf for customer call centersExecutive management visibility and reporting - strategicImproved sales and decreased costs

Business BenefitsProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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Lack of leadership Lack of goalsLack of Business SponsorshipStart real BIGDrop the ball on user tool/support/trainingStarting with the wrong usersWrong understanding of deliverablesExpertise is on transactional/ERP systemsThinking a Query tool is an architectureTop Reasons for FailureProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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Architecture Centralized, integratedAttention to DW fundamentalsDistinction between OLTP and DW environmentsIterative approach Clearly defined ScopeMust improve business performanceClearly defined GoalsExpectation managementUser participation & leadershipExperienced ResourcesClean, valid, reliable data Truth DatabaseBusiness Rules clearly definedDSR Success FactorsProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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Underlying ArchitectureA true data integration engine (not code)Visual & Self-documentingIntegrate any data sourcePre-built POS Integration/Validation RoutinesData model (Open, Designed for Growth & Change. Should be database agnostic & query tool agnostic) Staging area, Target, Include Retailer CalendarMeta Data layer that can be leveraged for Predictive AnalyticsFlexible Roll-out options & Database IndependentPOS Data Manager , Security & AdministrationFront End Users can chose what they wantBlueSky is Built on Smart Client TechnologyAnalytics/Viewer/Free ReaderIntegration with Excel (& Exceleration), PowerPointFlexible Export capabilitiesAbility to query multiple data sourcesAdministratorSupport for Promotion applicationsSupport for Forecasting integration

POSmart DifferentiatorsProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

Our data integration engine is a true differentiator. It brings together data from different sources and allows it to integrate with your own data warehouse if you want it to be, or be hosted in our data center. Its EDI stage allows for easy integration of EDI data including 852 files that contain POS data from retailers. Validation processes are built into POSmart Integrator to help identify invalid, missing and duplicate data, saving a lot of time. Its scheduled to look for new data each night and automatically update the database as soon as a retailer has sent new data. Then it automatically updates all the reports which are then cached on the server and waiting for the users in the morning. This allows them fast access to reports that have already been run without having to wait for the query. The reports are then presented through BlueSky.

BlueSky is the user interface which includes secure access for users. Page #

Project: Streamline use of TDLinx data

Quote: This BlueSky reader tool is pretty darn slick! And you guys have the best customer support ever! Sr. Project Manager

-------------------------------------------------------------------------------------------Project: Integrate over a dozen POS sources into DSR for reporting and to feed operation TPO & TPM applications

Quote: Team, Due to your outstanding teamwork and exceptional dedication, we have reached the first of our DSR go-live milestones. On behalf of Sara Lee, I want to thank each and every one of you for your efforts in successfully delivering against this important goal, in accordance with our plan and business requirements. Ill be communicating to the Advisory and Steering Committees that the initial phase of DSR 2.0 has been successfully completed, and that I expect further success in reaching the remaining go-live milestones of this important project. Thanks to an exceptional team for a truly outstanding effort. VP


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Sr. Project ManagerProject: Integration of over a dozen data sources with internal data in a hybrid solution

Quote: We realized the importance in better utilizing our point-of-sale data (and other data sources) POSmart & BlueSky over delivered on our business objectives to improve and streamline our reporting processes without the burden of significant technological changes. Knowing we have partnered with a company that has industry knowledge and know how allows us to confidently trust in the value of information and generate incremental business opportunities with our retail partners."


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CIOQuote: With POSmart, were much more efficient. What used to take us days, now takes us minutes to get answers to.

Project: Analyze sales and returns. Reestablish retailer discounts.


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Quote: POSmart integrates POS and youre the easiest software company we have ever worked with. You are very quick to respond. We consider you a strategic partner and wish all our software partners were as good as you.

Project: Integrate C-Store data from third party with retail chain data and shipment information.

VP MarketingProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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CIOProject: Integration of over 20 retail data sources with internal shipments, budgets and forecasts.

Quote: I am always happy to provide a reference for a quality product or service such as yours. Relational provides the highest quality support. Big companies should learn from you.


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Sr. Marketing AnalystProject: Integration of ten retailers for category management teams. Resolved issues identifying OOS. Quote: I just cant express my gratitude enough for you guys and what you do and what you represent. You guys have just been a great partner to me and to First Quality. And I guess sometimes thanks doesnt sound big enough. If theres some way to say thanks bigger and express that and the way that Im feeling it right now, I wish I could. Just know that I have a big smile on my face right now and just thank you for everything.


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Project: Integration of POS data into Oracle environment using Business Objects. Walmart team working to establish Category Captain status with WalmartQuote: I finally have an application that lets me think like the customer.

PresidentProperty of Relational Solutions, Inc. By Janet Dorenkott February, 2014,

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Take AwaysAn understanding of the different DSR solutionsA description of how to recognize a Team DSR versus an Enterprise DSR.A methodology and process to start withAn expectation of time frames and benefits.

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Thank you & Stay Tuned!Follow Janet Dorenkott on LinkedIn, Email [email protected] us at 440-899-3296, Janet is x225 / Karen is x 232Follow Relational solutions on LinkedIn, Twitter @POSMARTBLUESKY & on FacebookJoin our Demand Signal Repository Institute & Big Data Association Groups on LinkedInSubscribe to the Relational Solutions channel on YouTubeVisit us at www.relationalsolutions.com or call 440-899-3296 x225Learn more from our webinars & Download our WhitepapersSee product demos & download trials from our website

Property of Relational Solutions, Inc. By Janet Dorenkott June, 2013,

With that Ill turn it back over to Karen.

(Karen)Thank you Janet, for that informative webinar. I think we all learned a lot and the goals were accomplished. If youre interested in having a consulting session with Janet to discuss and brainstorm on how your company can leverage social media data, please contact me at x232.

In addition, Look for our next Big Data webinar as well as other informational webinars on our website.You can Download our white papers, follow us on LinkedIn, Twitter and Facebook. Subscribe to our YouTube Channel or simply give us a call. Thank you all again for joining us today for this informational webinar. We hope you found the information helpful. Please send us comments on how you liked the webinar and how we can improve up it. We will follow up with questions that were submitted and related answers. Thanks again and have a great day!51Page #

What is a Demand Signal Repository?

Data & Analytics

Transcript of What is a Demand Signal Repository?