We were told as children to eat our vegetables because they were good for us. More times than not, our parents said that to be healthy we had to eat the right foods. The truism of “you are what you eat,” however, has applicability far beyond the dinner table. For children it was about carrots; for business it is about data.

It is cliché to say that data is a company’s lifeblood. We may pay only lip service to data, but often that is all we pay. Data management in all its forms is too often underfunded, understaffed and misunderstood. It is important to be talking about this as we enter the season of strategic planning and budgeting.

Too many retailers, wholesalers and brands are predisposed to cut programs like data management for short-term budgeting imperatives, but fail to appreciate the long-term impact of their actions. Programs like Master Data Management can be viewed as expenses to be cut, rather than contributors to sales and profitability. Invariably over time, these choices have revealed to be a false economy.

Avoid the empty calories of poor data
Very often we fail to distinguish between data volume and data quality. Data quality requires ownership of the responsibility for data completeness that many companies overlook. CIOs routinely assure their organizations that they can deliver every piece of data that the company would ever need, but this is an assertion often made without context.

For example, take the assertion that the company has an email address for every customer in its transaction data. This may be true from the CIO’s perspective, as a data field exists within the transaction set. Though the data field for customer email may exist, it fails to account for the very low occurrence of customers providing their personal information at the point of sale; thus making the data at best incomplete and at worst deceptive.

A healthy business depends upon using fresh information
Data must be defined by how it is used. This is the responsibility of the entire organization, not just the technical team. Unfortunately, if the enterprise defaults on this, the IT organization is left with no alternative but to treat the data as though it were fixed, missing the critical aspect that data is dynamic, constantly evolving, and being shaped by competitive influences and customer expectations.

For many years, the retail business has struggled to adapt to the day’s complex and competitive landscape because its data model has been starved by a store-centric mentality. The rapid adoption of e-commerce by consumers has brought into stark relief the difference between retailers, separating those who could adapt their data model from those that could not. The fates of these short-sighted retailers that fail to improve their data practices should serve as a cautionary tale for all.