The Dilemma of Bad Data

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"Bad data is no better than no data" - Mel Netzhammer.

Did you know that globally companies lose close to 10-25% 1 of their annual revenues just because of bad data?

All unformatted, non-classified, duplicated data or incomplete information that companies deal with on day to day basis is referred to as bad data.

It is said that corporate data grows 40% YoY 2. With this exponential rise, the percentage of bad data is bound to go up significantly, creating hurdles for data interpreters due to which company loses a lot on time and efforts in finding out the solution.

Let’s take it ahead with few examples to have a better idea on how bad data can be a lingering pain point for the organization, which is crucial for strategic decision-making.

1. Invalid Reporting

1)-Invalid-Reporting

Reports form an essential part of day to day decision-making process. Unavailability of required reports can then hamper crucial decisions which may translate into losses for the company in the longer run. For instance, in a processed cheese making company, they need X litres of fresh milk on regular basis for the production. During a festive week, the market demand of their products rises manifold. In such a situation, the production team prepares a chart on the basis of reports of current stock level of milk and sends it to the purchase manager. Any error in the report can lead to severe problems like stock-out-situation or wastage as milk is a perishable commodity.

It is rightly said, “Without Data you’re just another person with opinion.”

2. Lower Output

2)-Lower-Output

Until and unless the managers are equipped with correct, formatted and classified data, they are not going to achieve the desired levels of output for the company.

E.g. Inventory intensive (liquid/solid) companies must have near real-time information about their stock levels and should be able to work on demand-forecasting accordingly or they are going to incur huge losses due to delayed deliveries, which ultimately transforms into lower output for a company.

3. High Cost of Maintenance

3)-High-Cost-of-Maintenance

Data is widely used by businesses, to highlight areas of improvement in business operation. Now, in absence of Data Management tools, companies incur huge costs in hiring dedicated manpower to maintain the pile of unformatted data, which is not going to give you instant results when required.

So, what’s the purpose of maintaining such huge chunk of bad data which is not going to reap you any benefits? It is said that 50% of IT budgets are just spent on maintenance of data.

4. Incorrect Matrix

4)-Incorrect-Matrix

A typical inventory intensive company requires more than five different types of reports to keep a thorough check on unit economics of their business.

Collecting data into the system is one task and extracting formatted data out of it is another. Incorrect matrices could mislead and it may happen that you are turning a small portion of your inventory very quickly while a large portion of your inventory is remaining idle, getting old and is losing value.

5. Incorrect Decisions

5)-Incorrect-Decisions

It is said that data without any business context will only show us half the picture or even no picture at all. Evidently, in the absence of concrete data, middle-level management is going to take day-to-day decisions merely on assumptions, which is quite risky for an organization.

It is possible that every now and then due to incorrect decisions; companies may run into out-of-stock or overstock situations and may even have to face returns.

The very purpose of collecting data stands defeated if it is not helpful in taking swift actions on time. We are living in an Information Age, where dynamic reporting is required for inventory management that can drill down to SKU (stock keeping units) levels. Data validation softwares are put to use by top management to filter out bad data and data duplication.

Since late 80’s the digital transformation has continuously changed the landscape of data management by breaking the silos of incorrect, outdated and incomplete data. Companies now consider building data management infrastructure as a purely strategic move and invest in it handsomely.

At ecubix IMI, we help companies in managing their inventory data with our best-in-class analytical, resourceful and game-changing software.

For more information: ecubix IMI: http://www.ecubiximi.com/

You can also drop us a line at sales@ecubix.com

References

1-  http://bit.ly/1OEDshS

2- http://bit.ly/2cdPbdD

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