Re: DW: Turning Data into Lead

Martyn Richard Jones wrote: > > The following is an extract from 'Knowledge Asset Management and > Corporate Memory' a White Paper to be published on the WWW possibly via > the Hispacom site in the third week of August 1996...... > > Data Warehousing may well leverage the rising tide technologies that > everyone will want or need, however the current trend in Data > Warehousing marketing leaves a lot to be desired. > > In many organizations there still exists an enormous divide that > separates Information Technology and a managers need for Knowledge and > Information. It is common currency that there is a whole host of > available tools and techniques for locating, scrubbing, sorting, > storing, structuring, documenting, processing and presenting > information. Unfortunately, tools are tangible and business information > and knowledge are not, so they tend to get confused. > > So why do we still have this confusion? First let's consider how certain > companies market Data Warehousing. There are companies that sell > database technologies, other companies that sell the platforms > (ostensibly consisting of an MPP or SMP architecture), some sell > technical Consultancy services, others meta-data tools and services, > finally there are the business Consultancy services and the systems > integrators - each and everyone with their own particular focus on the > critical factors in the success of Data Warehousing projects. > > In the main, most RDBMS vendors seem to see Data Warehouse projects as a > challenge to provide greater performance, greater capacity and greater > divergence. With this excuse, most RDBMS products carry functionality > that make them about as truly 'open' as a UNIVAC 90/30, i.e. No > standards for View Partitioning, Bit Mapped Indexing, Histograms, Object > Partitioning, SQL query decomposition or SQL evaluation strategies etc. > This however is not really the important issue, the real issue is that > some vendors sell Data Warehousing as if it just provided a big dumping > ground for massive amounts of data with which users are allowed to do > anything they like (any this, that or the other - kind of reminds me a > little of the history of computing), whilst at the same time freeing up > Operational Systems from the need to support end-user informational > requirements. > > Some hardware vendors have a similar approach, i.e. a Data Warehouse > platform must inherently have a lot of disks, a lot of memory and a lot > of CPUs. However, one of the most successful Data Warehouse projects I > have worked on used COMPAQ hardware, which provides an excellent > cost/benefit ratio. > > Some Technical Consultancy Services providers tend to dwell on the > performance aspects of Data Warehousing. They see Data Warehousing as a > technical challenge, rather than a business opportunity, but the biggest > performance payoffs will be brought about when there is a full > understanding of how the user wishes to use the information, not before. > > To my surprise, most Meta-Data Tool vendors seem to have a handle on > what Data Warehousing is all about, so there is little to say on this > score, apart from the fact that these companies must participate with > other vendors in providing a Data Warehousing solution, and this implies > a degree of risk. > > So what is exactly wrong in just putting data into your Warehouse and > away you go? > > Firstly because there are various types of companies, and these > companies have various information needs brought about by marketing > initiatives that govern the applicability or not of historical data. > > For instance, a highly innovative company that introduces new but > dissimilar products onto the market on a irregular basis may not hope to > reap any benefit from analyzing their historical data before launching a > new product ... Ask Akio Morita of Sony if a Data Warehouse would have > resulted in the launch of the Sony Walkman. > > A relatively new business in what was once considered a traditional > market may not have the amounts of historical data to be even ready to > begin segmenting the market. > > A company that follows trends and uses the past to predict the future > may not be fully aware that eventually all markets succumb to the > eternal constant: change and furthermore, change that cannot be > predicted by solely examining the past. > > A company that trades in a few products may not have enough historical > data to be able to identify precisely the type of clients they have. For > example, a pet food manufacturer may discover by using a Data Warehouse > that most of their clients are furry, have whiskers and like to go out > at night. > > In diverse corporations there are various kinds of needs and wants, from > satisfying the monetary needs of the stakeholders to the psychological > needs of the CEO. However, most of these companies cannot readily > identify certain market need structures just by analyzing operational > data. So, don't go looking for the really important information and > knowledge in the operational systems, it will not be there. For example: > > No amount of legacy data will tell the telephone company that their > information service is not providing the service levels that the > customer requires. > > No amount of legacy data will serve to tell the telephone company that > their operators need a more customer oriented attitude. > > No amount of legacy data will tell a supplier that they are meeting a > need, but badly, and that this puts them in a potentially risky > situation with regard to market incursion from new competitors. > > No amount of legacy data will tell a company why people do or do not buy > from them based on the acceptance or not of the company style, culture, > personal traits etc. Maybe companies should hire external consulting > companies to tell them just what it feels like to deal with them on a > potential client basis. > > Legacy data that tells a company that it's employees work long hours on > various projects will not accurately show that a lot of productive time > is actually wasted due to informal or spontaneous business practices, > nor will it show the amount of quality time that is actually being > wasted. > > Legacy data that is used to support a Marketing organisation, when the > marketing organisation is just a glorified PR exercise can't really be > seen to be adding a lot of value to business processes. > > Legacy data may show that a company is performing well relative to the > competition, but will probably not show cases where that very same > company is performing badly relative to it's potential. > > Data Warehousing can handle structured data magnificently, but can it > really handle the kind of unstructured information that forms the basis > of many business processes and information networking and especially > strategic decision making processes? > > Data Mining will only really work if you have hidden information, that > is relevant and pertinent to the enterprise, if you don't have the basic > material then no amount of digging will reveal the gold that many aspire > to. It doesn't matter what you do with lead, you still can't turn it > into a precious