When reality and the data in your system do not agree, you have contaminated data. The system says you have 10,000 cases but you actually have 9,850. A customer’s ship-to address is out of date. You have the same piece of information in two places in two applications or even two systems, but they do not agree. That means one or both are contaminated. Contamination can be caused by many things. Transactions causing a change in the data may have been inaccurately recorded. In the inventory example above, one of the many transactions that change the on-hand quantity could have been inaccurate. Maybe the physical act was flawed. A batch sheet calls for 1,000 pounds, the transaction is recorded as 1,000 but the picking resulted in more or less than 1,000 pounds. When material is placed in a location, the location is incorrectly reported, resulting in two pieces of contaminated data.

Time delays can cause temporary contamination. The recording of the transaction is delayed so that for a period of time, the data does not reflect reality. No harm, unless a decision will be based on the contaminated data. Contaminated data can have a negative impact on business. Catastrophic problems include a recall, losing a customer or a major financial write-off. Less of an impact is carrying too much or too little inventory or shorting a customer unnecessarily.

With the increased use of the Internet, suppliers, co-packers, brokers or customers will have access to your data. Trading partners will see the inside of your company. Internal data problems can quickly become external problems.

Contaminated data is often a sleeping problem. It may cause problems that are minor enough to remain hidden, but may be used in a way that causes problems. For example, if a lead-time is incorrect, order calculations will be incorrect, resulting in either over stocking or out of stocks. The contaminated data may lay dormant until something changes. A recipe may be wrong, but the first shift operator knows that and corrects it on the fly. Occasionally, you make it on the second shift and then the problems start.

Spot checks can detect some problems. Auditors send out verification letters to customers or suppliers. Cycle counts or physical inventory provide a precise picture of reality.

Business Intelligence systems can locate contaminated data by putting the information in front of people who can judge it best. These people can locate logical inconsistencies. In the most extreme examples, you must undertake a cleansing process. Proactively seek out the right information and take steps to correct it. This may mean a physical inventory or a campaign to get all customers to validate their name and address.

Contaminated data causes both large and small problems. If you rely on computer systems, your company can be negatively impacted. Now is the time to find contaminated data and fix the problems – before your customers or auditors find them.