GovernanceRegulationHow Data Warehousing Can Unite Your Company

How Data Warehousing Can Unite Your Company

You are about to face an investor firing squad. As an executive suit in global conglomerate ExCo, your major shareholders have called an urgent meeting to quiz you on the current state of business. How are your recent acquisitions in Guatemala performing? When will ExCo finally be compliant with the latest corporate governance code? And how on earth do you expect to derive any shareholder value from that merger in Central America?

If you had even half the answers at your fingertips, this might be survivable. But your data warehouse (the IT system which collects data for analysis and reporting) hasn’t taken into account your new acquisition. Oh, and you’re told that you can’t access any data from this acquisition until next quarter. It’s times like these when it seems that your IT and your business live in completely different worlds.

As scenarios go, this one is not so far-fetched. Big business is a fast-moving and constantly changing environment. Competition and innovation bring new opportunities and threats, while new regulations and legislation such as Sarbanes-Oxley and Basel II heighten demand for transparency and compliance.

Given these pressures, it is hardly surprising that IT is often out of sync with the needs of the organizations it serves. The lack of the right tools to enable constantly up-to-date reporting can become a stumbling block hampering a business’s ability to cope with demands put upon it; and investors are not known for their patience.

Is there a better way to harness the power of IT to bring it in closer alignment with your business? You bet. It’s called Data Warehouse Lifecycle Management (DWLM). This rather technical nomenclature may imply as much excitement to a busy company director as filling in a tax return on a wet Sunday afternoon, but in fact it is providing a truly ‘eureka’ moment for those executives now discovering its potential.

DWLM is a discipline for managing the data warehouse throughout its lifetime, and ensuring that it continuously provides business executives with fast, up-to-the-minute, consolidated management information. This approach is designed around automating the creation and modification of data warehouses, which in the past have traditionally been rigid in structure and thus inflexible to change.

This automation enables DWLM to empower IT to become more closely aligned to the changing needs of the business. In practice, this speeds up financial reporting and gives executives the information they need to enhance the performance management of key business elements, such as sales, marketing, supply, and logistics.

Even as the business changes, DWLM can be the means for obtaining reliable financial data – so allowing executives to better manage all aspects of their company. Should the company acquire and dispose of businesses, or reorganize product lines, its data warehouse as operated through DWLM can continue to evolve and adapt to the changes taking place.

DWLM can enable IT and the business to improve production of detailed market and customer segmentation, manage complex business models and product hierarchies, and manage products throughout their lifecycle. It gives both global and local views of business performance and profitability of key measures such as brands, customers, and channels.

In short, DWLM gives users a host of different views on their business – whether historical, current, or projected. And owing to the relative speed and simplicity of DWLM, it lowers the total cost of creating and managing the data warehouse.

To understand the leap forward that DWLM represents, some explanation of data warehouses is useful. As computing is so pervasive throughout a company’s operations, a huge mass of data is collected in various operational and IT systems. But it’s a tough task to obtain a coherent view of activity across these systems in order to see how the business is doing, because of the great variety involved.

Data warehouses were created to help overcome the constraints of single reporting from multiple operational systems. They work by copying data from these different systems, ironing out the inconsistencies, and creating an ‘information repository’ which can answer questions about the company – across the different processes, divisions, and even countries involved.

But data warehouses built on the traditional approach are difficult to get right. Beyond the tricky task involved in getting them to work at all in the first place, they may not have been built to cope with the complexity of change. However, large multinationals in particular are constantly evolving at all levels, in different markets, geographies, and jurisdictions.

They also have many different business models and different business cycles all operating at different speeds and phases. One part of the company may be at a planning stage, for example, while other parts might be at an evaluation stage. Traditional methods of constructing data warehouses often fail to take these different models and planning cycles into account. The fundamental problem is that traditional data warehousing is built around an enterprise business model at a specific point in time.

But businesses thrive on change – change that is much faster than custom-built data warehouses are able to keep pace with, and therefore building a new model for the data warehouse requires costly and time-consuming reprogramming. And even fairly modest updates put demands on scarce IT resources – which leads to backlogs of updates, which in turn lead to time-delayed, incomplete and inaccurate business reporting. The difficulty in reconciling this misalignment of IT with the business is a major factor in why four in ten traditional data warehouse implementations are expected to fail [source: Cutter Consortium, December 2002].

So how would a company go about implementing DWLM? It all starts with the business model – i.e. mapping the various business structures and then describing any relationships between these to identify if there are any overlapping versions of these structures (which there usually are)! Having then loaded master or reference data associated with this set of business definitions, the company is then in a position to load in any business transactions that are required from the source systems.

DWLM software can be integrated with existing warehouses without having to scrap all existing data warehouses i.e. it should be evolutionary rather than big bang. This is because DWLM can be introduced gradually into an organisation by using other data warehouses as feed systems or sources. The business model can be built as before, and then it can integrate these disparate source systems, which may include existing warehouses. Further value would be obtained by gradually replacing the legacy data warehouses, since then you can take advantage of additional functionality of the modern software, but you can do this at leisure.

So why would anyone want to bother? The answer is simple: tougher competition and compliance issues demand better business intelligence and performance management. For this reason, organisations may choose DWLM to provide data warehousing that is fast to implement and can cope when business change is on the uptake.

Since the practice of DWLM was developed in the mid 1990s, large companies have increasingly recognized its advantages. Some of the world’s leading companies are now confirmed users. Take for example Shell OP, the oil products businesses within the Royal Dutch / Shell Group. Shell OP needed to accommodate its various local, regional and global business models and data structures, while providing multiple, consolidated views of business performance. According to the traditional approach to data warehousing, the time to implement such a system would have taken years. But by using DWLM, Shell implemented a global deployment of more than 60 data warehouses covering 96 countries in just 18 months.

Global FMCG giant Unilever, meanwhile, needed a data warehouse capable of coping with the various business models involved in its frequent mergers and acquisitions. The company also needed to be able to view historical brand performance, in order to measure the effects of restructuring initiatives. By deploying DWLM, Unilever built a flexible and cost-effective solution that delivered rapid results, bringing together complex, time-variant data from numerous systems. It is using this data to deliver relevant and timely management information directly to business users.

And when Halifax and Bank of Scotland merged to form HBOS, the board wanted to integrate procurement data across the company in order to facilitate cost savings as quickly as possible as proof of the merger’s success. Using DWLM, HBOS was able to give business users a clear view of the merged procurement data within just three months.

Although DWLM is mostly used by Global 2000 companies, it is applicable to any large organisation that has to deal with multiple, incompatible business structures, each of which may change over time. Customers that have deployed DWLM have gone on to see excellent, and in some cases, remarkable, return on investment.

These examples show that DWLM is helping major companies achieve powerful new insight into their businesses in a fast and cost-effective way. Hopefully, this also means that investors will in future be putting fewer executives in front of firing squads. Rather, they should be handing out medals.

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