From cradle to grave: Information life-cycle management strategy
Businesses these days can’t run without technology, and the systems and processes which make up this technology generate their own data.
If you want to improve these processes, you must analyze your data and then draw insights from it. But first of all, your data’s quality, consistency and comparability must be maintained. This is your information life-cycle management strategy.
The creation and implementation of a strategy performs a number of roles. It enables the collaboration between disparate parts of the organization because data is comparable and consistent.
Key Performance Indicators (KPIs) can be used to highlight what’s working well and what’s working not so well in the company. Your planning and forecasting will become more accurate which will benefit the entire organization.
All of this unlocked potential will arise from the strategy.
The netlogx information architect assigned to your project will have experience in the management of data in small and large organizations. We take time to get to know your business and then begin with the end in mind.
We don’t just look at where we can improve your processes. Instead, we focus on the key data which drives your business and target the areas from where your company will get the most value.
We’ll use a framework, such as the Method for Integrated Knowledge Environment (MIKE2.0), which leads to a systematic and comprehensive approach. We’ll then work with your management team to put in place appropriate governance which will control and guide new systems data and improve existing data.
The management strategy and complementary governance structure are then ready to be rolled out to all levels of the organization. And we’re there to guide your company through this, every step of the way.
Why is an information life-cycle management strategy important?
The less time it takes to gather and analyze data, the more productivity is increased. Insight can also be gained much more quickly once a strategy is in place, because data does not need to be manipulated nor its accuracy validated.
