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Client Guide to theData Warehouse Category Management

Version

Confidentiality StatementThis along with all attachments hereto shall be considered s

Proprietary/Confidential Information


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gantthead.com Client Guide to the Data Warehouse

This Guide describes the CLIENT Data Warehouse and how to use it via BusinessObjects for the purpose of Category Management Analysis.

Note: This document contains British spellings.

2007 gantthead.com 2


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Table of Contents

1.1.Category Management................................................................................6

1.2.Sales............................................................................................................6

1.3.Trends..........................................................................................................6

1.4.Customer Information..................................................................................61.5.External Data...............................................................................................6

1.6.Sales............................................................................................................7

1.7.Supply........................................................................................................13

1.8.Inventory....................................................................................................14

1.9.Promotions.................................................................................................14

1.10.Core Records...........................................................................................15

1.11.State System............................................................................................15

1.12.Items Below Cost Report.........................................................................16

1.13. New Line Sales Exception Report..........................................................161.14.Inventory Review Report.........................................................................16

1.15.Item Review Report.................................................................................16

1.16.Maintenance............................................................................................16

1.17.Procedures and controls..........................................................................16



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1. Introduction

The Data Warehouse is a relatively new invention for most people. In its simplestterms, a Data Warehouse is a repository of data - a place where data from all parts ofthe organisation (and beyond) can be gathered together for the practical purpose ofreporting and analysis. There are many technical considerations involved in selecting,building and maintaining a Data Warehouse but the vast majority of theseconsiderations are of little interest to Data Warehouse users and therefore will not bediscussed in this paper.

This paper addresses the things that users want to know

What is a Data Warehouse?

How do I use it?

Whats in it for me?

This document begins with a generic discussion of Data Warehousing, but only as a

means to explaining the CLIENT Data Warehouse. The reader will find an explanationin business terms of what is available, and how he may benefit by using the DataWarehouse. There are two goals for the business user:

1. How can I do more easily what I am already doing today? (the sigh of relief goal)

2. What can I do now that I couldnt do before? (the brainwave goal)

If these two goals can be achieved, the Data Warehouse will not only become a usefultool in doing your work but something that you rely upon to do your job.

To learn how to use the Data Warehouse with CLIENT information there are many

things to remember.

Each subject area is detailed in Chapter 4 followed by explanation of the standardreports and how to access them.

Administration issues and the future direction planned for the CLIENT Data Warehouseare discussed before the Appendices cover the What, Where and When of the Dataavailable for category management and a list of all the Business Objects classes.

2. What is a Data Warehouse?

Traditionally, a warehouse is a place where goods are stored until required. A quick

check in your PC thesaurus will show that other terms for a warehouse arestorehouse, depot or repository. A Data warehouse should be thought of as astorehouse, depot, or repository of data. In a conventional warehouse, goods arecollected, arranged and stored for easy access when required. A Warehouse may storegoods from many different vendors. In the same way, a Data Warehouse may collect,arrange and store data from many different sources (legacy systems). The data hasbeen extracted and then combined into various subject areas within the datawarehouse. The data warehouse attempts to arrange and present the data in a waythat turns data into information. Users are not interested in sterile data but in what thedata means in business terms. This is the role of the Data Warehouse and in particularthe access tools that business people use. In the case of CLIENT - the data could



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come from legacy, MMDS or from some external agency that can supply data ofinterest to us. The similarities between the retail warehouse storing goods for sale andthe Data Warehouse storing data for analysis is shown in the two diagrams below:

Warehouse

Vendors Stores

A goods warehouse

Vendors send

their goods to one

central warehouse

Stores send requests

to the warehouse for

goods when required

Data

Warehouse

Users

A data warehouse

Legacy systems provide

data to one central

DATA warehouse

Users send requests

to the DATA warehouse

for information when

required

Legacy/Production

3. CLIENT Goals and Benefits

For many years CLIENT has survived collecting massive amounts of data about thebusiness and its customers in separate systems without having an efficient way ofcombining the data in one place in order to analyse and derive benefit from the

collection of data.

The Data Warehouse has arisen in the last few years to solve this problem, and manyother companies have already built and are using Data Warehouses today. Ourcompetitors are among them.

In business today it is increasingly difficult to obtain competitive advantage throughproduct, service or price. Companies are more quickly able to maneuver and counterofferings based on these criteria. The most powerful weapon today is information. Manycompanies are moving towards customer pricing where knowledge of the individualcustomer allows pricing specific for that customer - and this can be used to monitor



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profitability and ensure customer loyalty. The Data Warehouse will enable CLIENT tomove in strategic directions that otherwise would not be possible.

1.1. Category ManagementAccess to information has been a major drawback within CLIENT. The implementationof Category Management requires the managers to have current (or at least very

recent) data pertaining to all the aspects of the job. Receipts, Issues, Stock levels,Sales and Promotional Income are all required by category managers to enable aholistic view of the performance of the products within their category. Effective categorymanagement would be impossible without access to this information. There are severalspecific benefits that the Data Warehouse offers for category management:

Direct access to information

Data combined into a business view

Access to historical data to give trends

Data arranged to allow users to look at their own data

The flexibility provided by user created queries rather than hard copy reports

Specifically, ranging decisions have in the past been made based on issues from thewarehouse. With access to the Data Warehouse, those performing the ranging task canhave access information on sales. This will enable ranging to be based on movement ofstock out of the store rather than movement of stock into the store.

1.2. SalesPreviously, the information on sales was inflexible and incomplete. The DataWarehouse provides a category manager (or any other CLIENT employee with accessto the Data Warehouse) the ability to request specific information on Sales. This couldbe the performance of a product, department or store as recently as yesterday.

1.3. TrendsNow, users can track the performance of a product, category or store over time.Comparison on a weekly, monthly or seasonal basis will be possible once enough datahas been collected.

1.4. Customer InformationThe Data Warehouse has vast capacity. There is enough room to capture informationby customer and to keep a record of all the customers purchases. The back end (i.e.,the data warehouse) is able to do the analysis, however changes to the front end

systems (i.e., cash registers) are required before this becomes a reality.

1.5. External DataA common practise within Corporate Data Warehouses is to analyse competitor dataand information on the community within which the business operates. These types ofanalysis are on the drawing board for the CLIENT data warehouse.

Loyalty programs can be implemented once the customer data is captured andprocessed.



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4. Subject Areas

1.6. SalesSales data was the first to be loaded on to the Data Warehouse and is available in twoforms:

Scanned Sales - available from April 28, 1997.

Department Sales - available form December 30, 1996.

The difference between the two is that Scanned Sales is information on product salesand Department Sales is information held by Store Department. Department sales (orsales that do not involve scanning or weighed items) do not appear in the scannedsales figures and so there is a slight discrepancy between the two Sales tables,approximately 1.5%.

The diagram below illustrates the flow of data from register sale to data warehouse.Each register in a store collects data into three filesitem, department and total.Scanned items pass through to the data warehouse on a daily basis. Data from the

department and total files do not reach the data warehouse until they have beenreconciled within Treasury on a weekly basis.

Scans

Non-scans

Totals

Items Departments Transactions

NCR 3600

Daily

feedsDaily

feeds

Reconciled

TuesdayDaily

Scanned

Sales

Department

Sales

Data

Warehouse

3 Register files

Scanned

&

Department

Sales

1.6.1. Scanned Sales

Scanned Sales data is product level information on items scanned at theregister. The data is loaded for the previous days trading and is normallyavailable by 2 pm. The introduction of MMDS may accelerate this, but for now,the following guideline is true - when you get back from lunch, yesterdays datashould be available. An email is sent out by the Operation and TechnicalSupport group to notify all Data Warehouse users when the information isavailable.



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Scanned Sales can be analysed by any combination of the followingdimensions:

Time

Store

Promotion

Product

The following diagram illustrates the path from store register to Data Warehouseand the approximate timings under the current legacy system. This will changeupon the implementation of MMDS.

ISP ISP ISPISP ISP

Comms

Machine

NSW

Head Office

DataWarehouse

Other

States

1. Cash Registers send data to In Store Processors (ISP) every 1/2 hour

2. Between 2am and7am Comms machine

receives data from

all states

3. 7am manual check

4. 9am sent to NSW head office

5. 10am sent toData Warehouse

6. Normally availableto Data Warehouse

Users by 2pm.

ISP

The information available for scanned sales is:

Scanned Sales Objects Description

Daily Sales Quantity The total quantity of units sold for a day for a

product

Daily Sales Value The total value of sales for a product for a day

Daily Product Cost The total cost of the products sold for the day

Daily Office Selling Value Daily units sold * office selling value

Daily Store Non Promo Value Daily units sold * Non-promotion price

Daily Competition Loss Daily Office selling value Daily Store Non-

promo value

Daily Promotional Markdown Daily Store Non-promo value - Daily Sales

Value

Daily Gross Potential Profit

Daily First GP



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Daily Non Promo GP

Last Price The last price at which a product was sold for

the day in each store

Avg Sales Value for last 28

days

Calculation of the average value sold for the last

28 days (by store & product)

Avg Sales Quantity for last 28days Calculation of the average quantity sold for thelast 28 days (by store & product)

The information shown in italics is calculated within Business Objects. The otherdata is directly sourced from the legacy system. The information displayed froma Business Objects request depends upon the dimensions selected.

For example, the sales data is kept by day. If you choose to examine sales bytime and select week, the sales will automatically be aggregated to the weeklevel. If you choose period, the sales will automatically be aggregated to theperiod level. If you choose nothing, data for each day will be aggregated up togive one total figure. Data will automatically be aggregated unless a specificdimension field is selected.

Data in the Sales table is held at the day level. This means that the datasourced from legacy is already aggregated. In the future there will a number ofchanges to this. Firstly, MMDS will capture price changes throughout the dayand therefore there will be an aggregation on sales values and quantities foreach price changes within the day. The value in the sales quantity field is notcumulative. This field is a combination of units sold and weight.

As mentioned on the previous page, the information available for scanned salesincludes a combination of raw and calculated data. The diagrams below show inbusiness terms how the data is calculated



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Office Selling Price (a)

Non Promotional Price (b)

Selling price (c)

Item Cost (d)

Competition Loss (a-b)

Promotional Markdown (b-c)

Store Profit (c-d)Increasing

price

->

Pricing Structure Formulae

First GP (a-d)

Non Promo GP (b-d)

Price Calculations

Competition loss- The difference between the recommended price and theprice charged when an item is not on promotion.

Promotional Markdown - If the selling price is less than the office sellingprice when a product is on promotion then this is regarded as the markdownfigure

First GP- The difference between the Office selling price and the Cost. Thisis the normal amount of profit based on the Head Office price.

Store GP- The difference between the Selling price and cost. This takes intoaccount the actual selling price that can be adjusted at the store level

Non-promo GP- The difference between the Non-promotional price and thecost

Diagrammatically, the calculated fields in the scanned sales can be viewed asbelow. The non-promotional price and selling price can be set anywherebetween the office selling price and the cost and these affect the markdown,competition loss and profit calculations. Of course if the selling price is set belowthe cost price, the company makes a loss on the product.



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Price and Profit

Office Selling Price (a)

$0

Cost (d)

Loss Loss

Sell Price

(c)

Store profit

(c-d)

Markdown

(a -c)Non-

Promo

Price(b)

Competition

Loss

(a-b)

Non - Promo

Profit

(c-d)

Settlement discounts

Promotions

Rebates

Summary tables

Within Business Objects, you will find several types of scanned sales figures:daily, weekly and monthly. The Data Warehouse receives the sales figures dailybut has also aggregated the figures into weekly and monthly figures to makeyour queries respond faster. The monthly table is actually held by finance month(period).

The purpose of having aggregation or summary tables is to assist in the

response time for queries. For example, if you want to see the dollar sales for aparticular product for a year, all 365 days of the year need to be located andaggregated if no appropriate summary table exists. If a monthly table exists,only 12 rows have to be located and aggregated and therefore the query will runa lot faster by using an aggregated table.

Aggregated tables provide efficiency. Detail tables provide flexibility.

Each dimension can be linked to the summary tables in the same way that theyare to the daily sales. Scanned sales should be thought of as one collection ofdata, from which a user picks the appropriate level of aggregation.

Currently, day, week and month (period) exist. Quarter, year and promotionalweek are possible future aggregations.

Weekly Sales

Weekly Sales information is aggregated by calendar week. The program doingthis is run on Tuesday night for the previous week. The weekly sales can bethought of as an aggregation of daily sales by week. There is however, onedifferencePrice. It would not make sense to add the price for each day of theweek. Therefore, the data warehouse contains an object called price fluctuation



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which is the difference between the highest and the lowest price for eachproduct charged during the week.

Scanned Sales Objects Description

Weekly Sales Quantity As for Daily Sales

Weekly Sales Value Ditto

Weekly Product Cost Ditto

Weekly Office Selling Value Ditto

Weekly Store Non Promo Value Ditto

Weekly Competition Loss Ditto

Weekly Promotional Markdown Ditto

Weekly Gross Potential Profit Ditto

Weekly First GP Ditto

Weekly Non Promo GP Ditto

Weekly Price Fluctuation Difference between the highest and lowestprices charged for the product during the

week

Sales information is designed to be analysed by the various dimensions: - store,product, time and promotion. The diagram below demonstrates how theinformation within scanned sales (shown inside the wheel) can be analysed bythe objects within the dimension classes (shown outside the wheel)

Dollars

Units

Profit

(potential) Promotional

MardownsCompetition

Loss

Averages

Cost

Products

Time

Departments Promotions

Districts

Sections

Stores

Counts

Price

Store formats

States

Any Dimension Any Measure

Store

Departments

Classes

(Outside the wheel) (Inside the wheel)



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1.6.2. Department Sales

Department Sales are theoretically the same information as scanned salesviewed in a different way. This is not information about product sales butinformation about sales aggregated to the store department level.

The following is a list of the store departments:

Grocery

Produce

Meat

Deli

Bakery

Seafood

Dairy

Frozen food

General merchandise

Bulk food

Liquor

Total Store

The information available is:

Department Sales objects Description

Number of customers The number of customers that purchased an item

from the department

Net Sales The value of sales for the department. Includes

non-scanned sales as well

Number of customers is not available for all departments. It is assumed thatevery customer through the store purchases an item from both grocery andgeneral merchandise departments and so the total store figure has beenallocated to both of these departments.

Net sales figures are complete.

As the total store figure is held along with the individual department figures. It is

essential that all queries from this table use a predefined restriction alreadycreated in business objects.

1.7. SupplyMuch more information than sales is required for category management. Information onWarehouse receipts and issues to the store have been grouped under the title ofsupply. The diagram below shows the flow of product from the vendor all the waythrough to the customer and the data available at each step.



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Managers will be able to track this flow and maintain much greater understanding andcontrol of the products within their category, where the stock is, the delays and thepossibilities.

Information flow in Data Warehouse

Vendor

Warehouse

Store

Customer

SupplyData availableCalculated information

Vendor Invoice

Warehouse Receipts

Warehouse Invoices

Warehouse Withdrawals

(Store Receipts)

Sales by Product, Store, DatePromotional Income

by Store/Product

Daily stock on hand

Sales Data Mart

Category Management Data Mart

1.8. InventoryThe stock on hand data available will initially be limited to Warehouse stock on a dailybasis. No information on Store level stock is available. Fresh stock will not be availableuntil MMDS release 1.

Data available includes the quantity of stock and the cost and office selling value of thatquantity.

1.9. PromotionsPromotional income information for stores and products is new information for thebusiness at CLIENT. The existing PPS system, the source for the information, holdsdata by individual promotion but no apportionment is included in the system.

The following diagram shows that Promotional income incorporates two distinctelements:

Cooperative income

Case Deal income (CDI)

Within PPS the Co-op is held at the promotional level and the Case deal is normallyheld by product. In the data warehouse we have further processed the figures to:

1. Apportion Co-op to the product level

2. Apportion both Co-op and CDI to the store level.



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3. The apportionment to the stores is done on the basis of sales. Sales information(already loaded to the data warehouse) is analysed for the relevant week of thepromotion and the income is apportioned to each store according the sales for thatperiod.

1.10. Core Records

Core records are known within business objects as dimensions. It is important whendesigning your queries to understand which dimensions apply to which measures.

The dimensions are:

Product

Category

Store

Store Department

Time

Promotion Warehouse

Supply Channel

Stock Type

Product and Store information is loaded from the core records in production on aweekly basis. Category information will initially be manually loaded whenever there arechanges. Other dimensions do not change.

1.11. State System

As yet the production systems have not been converted to have a single nationalproduct number. In many cases one number is associated with different products indifferent states providing much confusion. In order for category managers to see theperformance of like products for each state a separate universe has been developed,known as the state system. This universe contains products and vendors and holds 80weeks worth of data grouped together in four-week lots.

One standard report (see section 5.4) has been prepared to enable easy analysis ofproducts by state. This data is reloaded monthly from the product and vendor tablesfrom each state. They have been combined together for easy use by the users andshould be thought of as another business objects universe.

The fact that 80 weeks worth of data is available in this universe, means that there is

many more weeks information available here than will initially be available through thefull category management universe. No information on supply, stock on hand orpromotional information is available here, neither are sales for a day as sales hasalready been aggregated within the production source file.

Information available for each product includes:

Sell price

Promotional Sell price



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Cost

Average weekly sales

First GP

Total GP

Last 4 weeks sales

Last 20 months sales

5. Standard reports

1.12. Items Below Cost ReportThe Items Below Cost Report prompts for a date and category manager and lists allproducts that were neither on promotion or reduced to clear that still sold for less thancost. The question is why did these products sell at such a low price?

1.13. New Line Sales Exception ReportThe New Line Sales Exception Report prompts for a product and then checks to see ifsales have begun for that product. The report will list all stores that have not yetrecorded any sales for the product.

Why have these stores not begun to sell this product?

1.14. Inventory Review ReportThis report prompts for a date and takes the stock on hand figure for that day andcompares it with sales for the previous 28 days. Based on these sales, a cover figurein weeks is calculated, meaning that we have x weeks cover in the warehouse stockbased on the last 4 weeks sales. The inventory review report is run by category.

1.15. Item Review ReportThe Item Review Report is taken from the State universe in Business Objects. (Seesection 4.6 for a brief description of the data available in this universe.)

6. Data Warehouse Administration

1.16. MaintenanceThe data warehouse team is divided into two groups - a development team and a CPI(Continual Process Improvement) team. Upon completion of a development task, the

development team passes control over to the CPI team to maintain and further improvethe system. The CPI team undergoes training so that skills transfer is achieved to equipthem for maintaining the system.

1.17. Procedures and controlsA full explanation of the procedures and controls pertinent to the loading and checkingof data into the data warehouse can be found in:



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7. Future Directions

The future direction of the data warehouse has not been completely decided at thispoint; however, there are many possible future projects that have been discussed. Aswith all development projects, a business sponsor will need to commit to development,and cost/benefit analysis will be undergone to validate development.

The vision remains to have one central source of information capable of deliveringanswers to the business questions of CLIENT, and to provide tactical and strategicadvantage and derive competitive advantage from the data available within CLIENT.

2007 gantthead com 17

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