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An Effective Approach to Data Management: The Bottom-Up Approach

An Effective Approach to Data Management: The Bottom-Up Approach

We all know that data is one of the most valuable assets held within any organisation, but what is the cost to the business of inaccurate data? And is this cost increased when data resides in multiple systems?

shutterstock_243627415Organisations are often drawn to the beautiful user-friendly reporting applications that pervade the BI market. Whilst these tools are both necessary and ultimately useful, attempting to implement a data management program from a reporting perspective is akin to a top down approach. However, a more effective method, and what is required to deliver fit-for-purpose information to a business, is to deliver data management from the bottom up. Implementing a reporting, or dashboard solution should be viewed as the icing on the cake. Nevertheless, it still remains an important aspect, and in some instances can be a useful tool for highlighting data management issues and requirements.

 

The Bottom-Up Approach.

Over time, organisations create and consume a huge amount of data. Creation of data is carried out across the entire organisation and often there are few, if any, checks made to validate data at the point of entry. This creates a further challenge, which is laid bare when decisions are made based on this data. Accurate, reliable, good quality data is essential for producing reports and analytics, a key component of an organisations decision-making process. Without this the decisions made can be based on an inaccurate view of the business, potentially causing organisations to take the wrong path.

Experience tells us that a carefully laid down process for managing core data, identification of roles and responsibilities, having a defined set of standards and process all ensure good quality, well managed data which can be used in disseminating information within the organisation as well as the wider community.

There are 3 key components in delivering a robust data management strategy:-

People – The importance of people in data management can’t be over-emphasised. People devise the processes, and drive the technology required to achieve the aim. The right people should be put in charge of developing a methodology that turns data into accurate information. In addition it is people that define the data standards that underpin the delivery and maintenance of good quality data. Finally it is being realised that poor data management is not the responsibility of IT but in fact a business issue that can only be solved by the involvement of the business users.

Processes - Good Data Management means having well defined processes on how data should be used, and this includes setting out how your core data elements are created, altered, and used within the organisation.

Technology – This is the elegant bit of data management. All too often organisations are drawn to this part first. Choosing the right application which is used to implement the processes as defined by the people is very important, and should only be done after the processes have been defined, and accepted by all parties involved.

A very effective activity, only if the data that is pushed to the reporting engine is of good quality.

 

Is It Worth It?

The term ‘garbage in, garbage out’ is certainly a valid phrase

There is plenty of evidence to suggest that the long-term economic benefits of addressing data management from a bottom-up approach outweigh the initial cost.

For example, Gartner estimates that the average Data Management project can provide savings that are equal to the initial investment, year-on-year for 3-5 years.

Other research suggests that the cost of bad data is even greater than this and can in fact cost organisations many hundreds of thousands (or more) pounds. Some studies indicate that each individual “bad” piece of data can cost as much as £60 per record. A phenomenal amount when extrapolated.

So, in a nutshell, to make the most of ones investment in technology, organisations need to underpin their implementations with a robust Data Management Strategy. There is little doubt that doing so will improve ROI, increase adoption of the new system, and deliver greater business value.

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