My previous blog post, that addressed finding a middle ground between data strategy investment and cost, highlighted three key areas that businesses tend to ‘waste’ spend on when it comes to their information management strategy. These included managing excess or duplicated data unnecessarily, trying to keep up with the latest in tech and not paying enough attention to the regulatory requirement linked to data management today. Dispelling the investment vs cost perception debate thoroughly, however, requires a business to dig a little deeper…
And by digging a little deeper, what I mean is over and above considering the more obvious data associated costs I previously addressed, a business must review aspects to data management that tend to play a ‘backseat’ role, yet steer the direction of the data strategy forward.
The same industry article I referred to last month shares great insights into what I perceive to be the ‘not so obvious’ cost factors. So, as a follow up to this, the below aims to address my take on these not so obvious areas, that support cost savings and a business approach to data and information management that can show true value.
Central business understanding
Given that the data landscape of a business is made up of data across various sources, it can be intricate and sometimes difficult to navigate. For data to add real value across the business, there needs to be a central business understanding around the data, how it is managed and how it can be accessed and used by everyone for the bigger business benefit. While this may be considered apparent it is often overlooked, especially if a business gets caught up in the hype around available data and the technology needed to derive meaning from it.
A business’s data strategy and management process must always map back to the business’s core objectives and be in line with the vision the business is driving towards growth and sustainability. A data strategy that does not align to this will only result in confusion across the business with everyone making their own assumptions about how data can and should be used. This can often present a high risk of unintentional poor business decisions being driven based on the data – and these decisions can be costly.
Senior management key to driving a foundational data approach
A business is only as strong as its leadership team and their ability to put in place structures that truly support the business to achieve its main objectives. This sentiment is no different when it comes to the formation of a data strategy. Senior management is critical to ensuring that the right strategy is developed and implemented throughout the business. Turning a blind eye to this need or hoping it will be achieved on its own or through the IT department solely can be a costly mistake – as there is no clear management channel guiding the process.
It is only when a business has a clearly defined approach to data management that unnecessary spend can be curbed.
Driving meaningful digital transformation
As digital continues to impact business operations and naturally grows the data landscape of a business, digital transformation is fast becoming a de facto standard of practice. Ensuring a solid data strategy, driven from the top down and that is understood by the full business will support a business in streamlining a smooth digital transformation progression – and this is the right position that any business focused on growth would want to be in.
These somewhat less obvious factors, coupled with those that make unnecessary associated data spend clearer, work hand in hand to not only manage data strategy spend better but to present a clear ROI for placing a focus on data strategy investment. Future successful businesses and those that transform with data considerations at their core will likely be the businesses that progress sustainably well into the future. The key is ensuring the implementation of an enterprise information management and data strategy that doesn’t cause more concern than value. This can be achieved with careful consideration and driving the right data approach.
