What is Data Warehousing All About? Peter Nolan

Agenda  What do you want, really?  What is the Data Warehouse all about?  Management Decision Making Process  Role of the Data Warehouse  Major issues of the Data Warehouse  What are people saying about Data Warehousing?  Typical applications of Data Warehousing  Case studies  Business benefits of Data Warehousing  What works?

What Do You Want, Really?  Improved profitability  Attention to both revenue and costs  Improved decision making capability  Make more effective decisions more often  Consistent measures of business performance  Others?

What is Data Warehousing All About?

What is the DW All About?  The Data Warehouse is all about “Supporting the management decision making process”  It’s that simple, and that complicated

Management Decision Making Process How’s Business? Why? What if? Invest $$$

What is the Data Warehouse?  Time Variant  Subject Oriented  Integrated  Contains non volatile snapshots  A Data Warehouse is a collection of data in support of the management decision making process.*  A Data Warehouse is a collection of data in support of the management decision making process.* *Source: Building the Data Warehouse by W.H. Inmon

What Does a DW Look Like? Highly Summarised Lightly Summarised Current Detail Older Detail (Tape/cdrom) MetaDataMetaDataMetaDataMetaData

Role of the Data Warehouse How’s Business? Why? What if? Invest $$$

Major Issues of Data Warehousing

Islands of Information

Hidden Cost of EIS/DSS Executive Custom Reports Spreadsheets Legacy Systems: $9/year $1

What are People Saying About Data Warehousing?

What are People Saying?  “The business case for warehouses is simple: they help turn data into a competitive tool” COMPUTERWORLD

What are People Saying?  Tom Peters  We are living through a shift from selling virtually everyone the same thing a generation ago to fulfilling individual needs and tastes... by supplying... customised products and services. The shift [is] from “get the sale now at any cost” to building and managing... databases that track the lifetime value of your relationship with each customer.

What are People Saying?  Rapp & Collins  it may almost be time to replace “location, location, location” with “database, database, database”.

What are People Saying?  Stanley Davis - Future Perfect  Mass Customisation  Standardise the Commodity and Customise the Service that Surrounds It  Example: Telephone calls

What are People Saying?  Philip Kotler - Marketing Management  Mass markets are fragmenting into micro- markets; multiple channels of distribution are replacing single channels... The winners are those who carefully analyse needs, identify opportunities and create value- laden offers for target customer groups that competitors can’t match.

IDC  Perhaps the single most important ongoing occurrence to affect data warehousing has been the information explosion. Organisations realise that, given the fundamental relationship between knowledge and power, utilisation of this information is key to their competitive positioning.

Meta Group  Bottom Line: Data warehouses are an increasingly critical component of the systems that support the ever-increasing tempo of business competition.

Typical Applications of Data Warehousing

A Way to Test New Ideas  How do you test new ideas for profitability?  Data Analysis/Mining “tests” ideas  Data Mining to find “diamonds”  There are “diamonds” in your data  Marketing Data Warehouse  Small investment, fast return  Likely source of “diamonds”

A Classic DW Application Targeted Marketing CUSTOMER SERVICE ADMIN CONTACT MGT DISTRIBUTION CAMPAIGN MGT ANALYSIS Marketing Cycle

Case Studies

 Many businesses have benefited  The following case studies are some examples

Product Rationalisation  Situation  Half the product line found to be unprofitable due to low number of clients and low premium payments  Solution  Launch “Product Rationalisation”. Cut the number of products by half. Leads to “Business Simplification”  Value  Largest business project ever undertaken by 100 year old company

Target Marketing  Situation  Legislation changes causes confusion for thousands over whether to retire. June 94.  Solution  Profile customer database, select all those people who would benefit from retiring before legislation change and target them for rollover products.  Value  $440M deposited into rollover fund. Some $300M up on product managers forecast.

Cross Selling  Situation  Customer wishes to cross-sell existing clients  Solution  Provide analysis capability to profile existing clients to determine who owned the product. Use DW to select targets who did not own the product.  Value  Response rate for new product purchase direct mail 18%. (As opposed to 2% for third party mailing list)

Up Selling  Situation  Customer wishes to up-sell existing clients  Solution  Provide ability to select existing customers to upgrade products  Value  Response rate for upgrade direct mail 33%

Variance Analysis  Situation  Senior management does not receive timely P&L report  Solution  Provide easy to use tools - access to revenue/expense database. Management conducts own variance analysis by dept, division, and bank  Value  $2M increase in net income from more timely management decisions

Cost Management  Situation  Cut corporate spending by 10%. Implement program within 3 months  Solution  Use relational databases. Create flexible applications for 285 departments to analyse expense data. Support senior management summary reports, consistent with department details  Value  Cut expenses by 10% - or $100M - from prior year

Resource Allocation  Situation  Misallocation of departmental expenses increases costs  Solution  Combine revenue, expense, headcount and asset/liability information into one database. Provide easy to use tools for access by all levels of management.  Value  $7 Million increase in net income through better resource allocation

Profitability  Situation  Unprofitable retail customers are causing drain on resources  Solution  Use CIS and product profitability to build customer profitability model  Value  Use model to reprice products and create household pricing. Increase net income by $20M

Segmentation  Situation  Marketing did not know what kind of customers were using services  Solution  Combine CIS with cluster-demographics to build customer profiles by product and market area  Value  Developed products to meet needs of customers. Increase net income by $3 million

Target Marketing  Situation  Direct Marketing budget substantially reduced  Solution  Develop Direct Mail Model, combining segmentation analysis and product usage research  Value  Target marketing reduced direct mail costs by $3M

Business Benefits

 More cost-effective decision making  Better business intelligence  Enhanced customer service  Enhanced asset/liability management  Aligned with corporate downsizing  Relationship to Business Process Reengineering

What Works

Likely High Payback Projects  High Volume, Low Cost products  Marketing Campaigns  Customer Value Index  Customer profit contribution  Tiered servicing of customers  Product launch, modify, termination, pricing  Customer/Product understanding

What Works  Senior Manager(s)  Making big decisions on scant data  Demanding information  Marketing Manager(s)  Demanding better sales targeting  Do something you can’t do now What works is generally not easy to do

What Doesn’t Work  IT technology driven project  Let’s try this new box, tool, toy...  Pie in the sky wishful thinking  There seems to be a lot of this about  Trying wide range of source systems first  DW as an extension of MIS/EIS

Places to Start  75% of DWs start in:  Marketing/Sales  Customer Information Systems  All benefit from integrating data from multiple source systems  All contribute to new revenue and profit  Most of the other 25% start in  Performance measurement projects  Financial reporting and analysis

Places not to Start  Financial Systems  eg. Ledger, Accounts Receivable, Product Catalogue  Not customer focused  These systems are already ‘good’  Provides ‘better’ numbers for accountants  Little opportunity for new revenue

Cost Justifications  These are hard to do in advance  Note that DW may be seen as “optional extra”  Near impossible to justify $1M, 2 year project  Much easier to justify  $100-$200K 3-4 Month Project  Aimed at profit project  Specific targeted audience  Even then it’s hard

Summary  What do you want, really?  What is the Data Warehouse all about?  Management Decision Making Process  Role of the Data Warehouse  Major issues of the Data Warehouse  What are people saying about Data Warehousing?  Typical applications of Data Warehousing  Case studies  Business benefits of Data Warehousing  What works?

Thank You for Your Time!