One of the most important things to understand about the types of legacy systems that you're likely dealing with is that you're talking about so much more than just a minor inconvenience. Legacy solutions may start out helpful, but they typically don't last that way for every long. Before you know it, your IT teams will be struggling to manage the growing number of disconnected applications and data sources across your enterprise. They'll be devoting more and more time to coming up with frustrating and time-consuming workarounds just to get everything to "talk together," simply because these solutions were never really designed for that in the first place.
But the worst part of all is that these outdated legacy systems aren't just slow — they still depend on the types of manual data entry and processes that can cost your business far more money than you realize.
According to one recent study, roughly 83% of all organizations said that they are not "fully satisfied" — either with the performance or with the output — of their current data management initiatives. A full 89% of decision makers from within these businesses say that the lack of integration among applications — and the data silos they create — are absolutely holding them back. But when you also consider that the same study revealed that businesses lose on average more than $1 million every year due to poor data management, it's easy to see why this is a problem that is so important to address.
Building a Better Data Management Strategy: Your Overview
At its core, data management is exactly what it sounds like — the processes you use to create, collect, store and secure data as efficiently and as cost-effectively as possible. It's something that has become particularly important over the last few years, as more and more businesses are turning towards intangible assets like data to generate value for their companies.
One of the reasons why an effective data management strategy is so important is because making key data available — both in terms of how it can be accessed and the ease at which it can be discovered — is a core component to your competitive advantage in your marketplace. If information is able to move freely across your enterprise, it means the people who need it to do their jobs have it — thus allowing them to make better decisions based on the types of insights contained within that data.
This has become especially important over the last year, given everything going on in the world right now with the COVID-19 pandemic. In March of 2020, most employees suddenly found themselves working from home for the foreseeable future. Without some type of data management strategy in place, simply getting that information to all of these disparate people would seem like an uphill battle. But with the right strategy (and the right technology at the heart of that strategy), your employees are free to be just as productive at home as they could be in the office.
Of course, data security and data governance are also hugely important to any effective data management strategy. The right approach to data governance can help improve a business' ability to classify information, for example — something that is hugely helpful from both a security and a risk management perspective. All relevant data can be cataloged with precise formats and access policies, again making sure that information can get into the hands of the people who need it without worrying about that information falling into the wrong hands.
These types of solutions are also critical in terms of enforcing the right level of protection based on the type of collected data. All of this puts organizations like yours in a better position to generate value from that data, with as few of the potential downsides as possible.
Overall, they key elements of your data management strategy include the ways in which you collect information, prepare information, store information, and distribute information across the board. It should be a responsibility shared across your enter enterprise by ANYONE who touches the data at any point. Obviously, the actual steps you take to identify data sources, analyze your data, store it in a structured manner and more will vary because your business is unique unto itself. But these are still hugely important steps to take — especially given the fact that the sheer volume of data you're dealing with is only going to increase as time goes on.
