Sunday, January 25, 2009

Your Database

Everybody has a database. Your DNA is a database.

Every business and organization has databases - lists, spreadsheets, financial reports, et al. - but does your organization have its "DNA database"? That's a database that monitors and controls the processes that define the organization.

Every organization has one or more DNA databases. One might exist in the mind of an entrepreneur. One might be a cultural thing. One might be a business plan. One might be a ledger book.

Electronic Data

Electronic or computer storage of information is usually the best way to store business information, especially large amounts of it. Computers can automate data processing and communication, increasing the efficiency and reducing the cost of many everyday activities. So, while the time and money involved in planning, implementing and maintaining an electronic database can be daunting (hardware, software, business process reengineering, data entry/capture, data quality assurance, user training, et al.), putting your organization's DNA database on a computer is essential to the organization's success in the information age.

Not all databases are created equal. The worth of a database depends upon factors including:
  • The intrinsic value of the information stored.
  • The quality and cleanliness of the data.
  • The shelf-life of the data.
  • The accessibility of the information in the database.
  • The security of the database.
  • The relevance of the reports and queries designed and the ability to perform ad hoc queries.
  • The accuracy of the data model to the business processes of the organization.
  • The ability of the organization's executives and staff to use the database effectively.
For example, yesterday's lottery number is worthless. Tomorrow's lottery number is priceless, unless.
  • Everybody knows tomorrow's number so the pot is divided a million ways.
  • The lottery tickets are being sold by bodegas in Nicaragua but you are in Nebraska.
  • You got the numbers transposed.
  • This is not the Powerball lottery; it's a church charity lottery.
  • ...

Process Vs. Outcomes Data

There is a saying, "You can't manage what you can't measure." But it does not follow that you can manage what you can measure. Many systems are designed to measure the performance of business units; they measure outcomes or results from period to period. Since they do not track the key variables responsible for the outcomes, it is seldom clear why results are what they are or what changes need to be made (management).

The stock market is a good example. Everyone knows what it is doing from moment to moment; results are continuously updated. Why the market is doing what it is doing is anyone's guess.

In order to measure to manage, an organization must have a good understanding of how inputs that it can control are converted into results (i.e., a business process). Then it can model the process, collect data, establish goals and norms, monitor variances and make adjustments to improve results (manage).

To model a business process, it helps to articulate "use cases" or scenarios that describe the way various constituents (customers, employees, vendors, management, etc.) interact with the process. The use cases provide a perspective for analyzing the process, making it more efficient and building information systems to manage it better.

Stumbling Blocks

  • The "data model" is the foundation of a relational database, essential for monitoring a business process. The data model is the blueprint identifying what data will be collected, how the data will be stored and how different tables in the database are related to each other. Often, little or no work goes into the data model, limiting the effectiveness of the information system. For example, you can buy an off-the-shelf accounting package and implement it using one of the sample charts of accounts (i.e, data models). But chances are that a sample chart of accounts is not right for your operations.
  • Data quality is an issue that organizations sometimes ignore at their peril. "Garbage in, garbage out," as the saying goes. Depending upon the potential cost of data errors, it may be necessary to take heroic measures to identify, correct or cleanse bad data from the database.
  • Many organizations procure and implement systems but fail to invest in the education and training their people need to operate and maintain the system. Managers and executives may not realize that they do not have the background they need to properly use evidence-based, decision-support systems. Because people come and go in the organization, the need for education and training is an ongoing one, requiring time and money. But too often, the budget for such training is nil.


Computerizing your database is going to cost a lot, especially when you consider the hidden costs. Click here for more on this.


In this competitive world, your organization cannot afford to be without computerized DNA databases. The complexity and cost of developing and maintaining these databases should not be underestimated, however. Understanding and commitment is needed at the top of the organization to fund and nurture these databases.

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