Turning data into profit

As business ever more competitive, so the ability to access analyse and understand business information becomes increasingly important

by Matthew Robinson, Microgen-Kaisha

Business has never been as fiercely competitive as it is today. Companies in all industries strive to gain new customers while maintaining their existing customer base. Government deregulation, globalisation, increased competition and the internet have all combined to change, almost beyond recognition, the way we do business. 


At the start of the 20th Century, economies were built on oil, coal and steel. Now, as we enter the 21st Century, the raw material that keeps organisations ahead, that drives top line growth and bottom line profit, is information: information about the organisation - its products, key markets and customers - and about its competitors and suppliers.

Organisations have invested billions in new systems, such as Enterprise Resource Planning (ERP), to integrate and automate business processes and maximise competitive advantage. In the process, they have built up huge volumes of data, in relational databases, data warehouses and legacy systems. However many organisations have been unable to deliver timely, detailed analysis of that data, which would empower them to react aggressively to changing business conditions.

Bridging the reality gap

In an ideal world, business decisions would be based on perfect knowledge of the organisation and its environment.

In practice, a manager’s understanding of the situation depends on the quantity, quality and nature of the information available. Consequently, critical business decisions are based on intuition without information, because the information needed is locked up in the business systems. No one knows where to look for it, and there are often no tools for taking the raw data and turning it into meaningful business information.

Business Intelligence (BI) provides the mechanism to ensure that decision-makers have access to relevant, reliable information, whenever, wherever and in whatever format they need it.

The challenge for businesses is no longer where to get data, but how to collect, organise, store it, and provide access for everyone that needs it, from the factory floor to the board room table.

Enterprise Data Warehousing

Business Intelligence is the key to transforming data into information effortlessly. The timeliness and quality of this transformation can make the difference between just surviving as a business, and thriving as a market leader.

An enterprise-wide Data Warehousing strategy brings data together across departments to provide a single, integrated and consistent view of the organisation for all users. Data from other systems - relational databases, legacy systems and other external data - can also be incorporated, enabling new decision making models such as activity based costing, product profitability analysis, and performance based management.

Users can analyse all the information in a Data Warehouse in depth, moving beyond simple viewing of the data to statistical analysis, forecasting, modelling, and what-if analysis.

Data Warehouses developed from the Decision Support Systems (DSS) and Executive Information Systems (EIS) of the 1980s and ‘90s, but differ from them in several crucial respects:

- Data Warehouses are mission critical. In today’s globalised, electronic markets, companies need to make decisions in real time, and need up to the minute information to support the decision making process. Traditional DSS is fed from transactional systems at the close of each financial period, so decisions are based on information up to a month old. Data Warehouse users can apply DSS type functionality to daily information, rather than historical period data.

  • Data Warehouses provide a single, integrated, enterprise-wide view of the company. Many DSSs and EISs are built around a single part of the business, such as a trading division, or a group of products.
  • Development of analytical tools was driven by users in finance, and sales and marketing. Data Warehouses extend analytical functions to a far broader audience in areas such as HR, customer service and the supply chain.
  • Decision-making is being pushed down the corporate organisation, and away from the centre. The typical warehouse user is a departmental or divisional manager, or even an employee in the field or shop floor.

Tools used for data warehouses also recognise that users are individuals, with their own unique information needs and levels of ability. Companies can choose between report writers of different levels of complexity and functionality; between professional OLAP tools and more intuitive multidimensional viewers; between powerful analysis tools, for users with an in-depth understanding of the data model, and query tools which allow the scope of analysis to be limited and simplified.

The internet changes everything

The web can deliver accurate, relevant and timely information directly to the desktop of the users who most need it, and who are best placed to act upon it.

Until recently, cost and technology barriers meant that analytical applications were seen as an executive level tool. The internet and intranet have reduced the cost and complexity of delivering this technology to the point where it no longer needs to be seen as the domain of power users and corporate executives.

Just as word processors, spreadsheets and even database management systems have become desktop tools available to every user, data warehouse software is increasingly seen as a basic tool of today’s information worker.

ORS training course

  • Introduction to Data Warehousing, data mining, OLAP and ETL tools
  • Business drivers for data warehouses including discussion of several case studies
  • Planning a Data Warehouse project
  • Ensuring success for a project
  • Latest thinking on data warehousing including federated warehouses
  • Links with other initiatives such as Customer Relationship Management, E-business and the internet.

The course will be interactive, including a demonstration of a data warehouse application and discussion sessions to ensure that delegates obtain maximum value from the course and have clear actionable steps to take back to their organisations.

The course leader, Matthew Robinson, has over 10 years’ business intelligence and data warehousing experience from both a business and IT perspective including practical knowledge of banking, having worked for a major UK banking group, as well as experience in utilities and manufacturing.

He has extensive knowledge of performance management, including tools such as the Balanced Scorecard, Customer Relationship Management and currently leads the Microgen-Kaisha Knowledge Management practice. His area of expertise is assisting organisations to exploit the value from information available to them.

The course is scheduled for 15th February, with a related course on Customer Relationship Management, also by Matthew Robinson, the following day.


Microgen-Kaisha is one of the UK’s largest independent Business Intelligence services companies, which has successfully delivered over 100 projects to blue chip clients, enabling them to realise their information management vision and support business objectives. Having no interest in products in the marketplace, the company is able to take an independent view.

First published to members of the Operational Research Society in Inside OR February 2000

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