Many people understand that managing data as a strategic asset or resource is an important task. They know that, beyond simply being necessary to satisfy regulatory requirements, it is in fact beneficial to both top and bottom lines. They also know that when businesses need to squeeze every ounce of performance from their systems and processes, good quality data is a vital strategic asset.
Risk managers are a good example. They know and understand the importance of acting immediately to enact practical data management strategies.
They need to access the information behind investments to develop flexible risk measures, but they have to be absolutely sure the data is clean and reliable before they can use it.
They also need data management capabilities that are in line with operational capabilities. It's no good if their organisations can gather vast swathes of customer or market data without the ability to properly manage it thereafter. That scenario rapidly results in a cost exercise and nothing more. Putting that data to good use - in the market trenches - is crucial.
Another example may be a utility service provider's billing system. The inability to manage customer data will result in incorrect billing. The greater the customer volume and the greater potential for error, the greater the potential for lost earnings which, in hard times, is inexcusable at best and criminal - for a public services organisation - at worst.
Sum of all parts
But truly effective data strategies are not confined to points of operation or individual departments. Banks, for example, have related information scattered throughout divisions and departments and they're typically in different, often disparate, IT systems and silos, or locked in file cabinets.
Bringing all of those data reference points together into a single view through a cohesive strategy is important to an organisation that is trying to drive customer profitability, reduce churn, and generally grow its share of a customer's wallet in a saturated market.
Yet many companies are now ignoring data or have put data quality projects on the back-burner citing cash flow, rationalisation, budgets, and resources for readjusting their priorities to other projects.
Rethinking resources
Most organisations usually react to or accommodate resources other than data first. The problem they face is that there are many important projects or undertakings but only so many available resources and only so much cash to inject.
Neither party - business systems or data systems - is going to get everything it wants without the union breaking down.
Mervyn Mooi is director of Knowledge Integration Dynamics.
The problem is particularly acute during a financial crisis. The crisis itself highlights the need to use existing infrastructure to its utmost and strategically employ new resources and infrastructure that will generate the maximum return on investment, and yet, it is the same financial crisis that limits the organisation's ability to do so.
So although there may be organisational policies in place for clean, properly managed and consolidated data to meet the tenets of good business practice and regulatory requirements, it is often the more tangible assets and resources with more obvious - even if lesser - impact on the bottom line that take priority when budgets are handed out.
It's simply a horrible situation for IT chiefs to be in right now: they may well know a cancer is eroding their organisation from within but their budgets are bedridden; what must they do?
What they really need to do, as is the case in any good marriage, is compromise. Neither party - business systems or data systems - is going to get everything it wants without the union breaking down.
The trick is going to be balancing the needs of both with the available resources to supply them.
* Mervyn Mooi is director of Knowledge Integration Dynamics.
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