At least 60 per cent of all new data an organization acquires or creates is analyzed and archived for future use. Given the powerful and fast-evolving data capture technologies out there, this means a mammoth data management challenge for companies of all sizes, but especially for small-to-midsized businesses (SMBs).
In this article, the third in our “Spotlight on Data Management” series, we look at the elements of any successful SMB data management solution, and the process of building one.
Data management is a question of architecture.
The word “architecture” refers not only to how the IT – hardware and software – is set up, but also to how the system integrates with and supports the goals, strategies and processes of the enterprise. What kinds of technologies are required? What role should business process requirements play so business users get what they need? How can the solution be future-proofed to cope with organizational growth, strategic changes and market changes? And what about the people side?
In the past, the IT part of the equation has tended to dominate not only the eventual implementation but also the design and planning that precedes it, often with the result that the solution doesn’t perform as expected. The technology has often forced business processes to accommodate its own data flows and categories, pulling the project away from its goals and resulting in a skewed, off-target implementation. In addition, vendor promises, the “quick fix” approach of na