I don’t like debt. Actually what I don’t like about debt is the interest I have to pay - the cost of borrowing. Interest is money that I could spend on some other goal I have, but it is instead given to someone else for the privilege of using their money. When choosing to use debt, I’m making a tradeoff: achieve one goal more quickly, but delay future goals until much later. Therefore, I use debt wisely, otherwise one risks bankruptcy.
The concept of debt can be applied to different areas of Information Technology. For example, when confronted with a technical problem in developing software, you have two choices.
You could quickly code a solution that solves the problem as quickly as possible. But this choice incurs debt - technical debt- because it typically leads to a fair amount of rework, or accrued interest, that must be done before a future problem can be solved. Technical debt results when a ‘quick and dirty’ approach is used instead of design best practices.
Like monetary debt, with technical debt, you end up achieving one goal more quickly but accrue interest (rework) that must be paid before you can achieve future goals. And the more technical debt you incur, the more inflexible your code becomes to any type of change.
The other choice, of course, is to choose a solution that takes longer to implement, but that uses design best practices that anticipate future problems, thus avoiding accrued interest. This is the preferred engineering minded solution because rework often takes more time and incurs more risk than implementing the optimal solution in the first place. And your code remains flexible to future changes.
Data debt is very similar. It is accrued when best practices for information governance are eschewed for short term fixes to data problems, thus accruing rework or interest that negatively impacts a business’ ability to solve future problems quickly with data.
But there is a higher cost of data debt. Data is a business asset, therefore its use should align with the goals of the business. Data debt accrues when the data landscape isn’t properly governed, resulting in less trusted data that limits the business’ ability to achieve its goals.
The Information Governance Cloud from BackOffice Associates helps minimize data debt by ensuring that your data, policies, and people are aligned with your business strategy. It also helps by providing clear understanding and visibility when making an investment decision so you can balance the right mix between risk and reward. With it, you define your business goals and directly connect them to supporting operational policies and business rules, and the data and business systems that enforce them. You can verify that your activities in data are aligned with the business strategy and that the operational policies you define are actually being carried out. Your entire governance environment is continuously monitored by Deep Guidance, embedded machine learning and natural language processing, that suggests changes to your data environment based on best practices for governance.
Debt stinks, so use it wisely. Minimize your data debt with Information Governance Cloud from BackOffice Associates.
About the Author
Kevin Larsen is the Senior Product Marketing Manager at BackOffice Associates. Over his 25+ year career, he has held positions in Software Development, Business Development, and Product Marketing. Kevin holds a B.A. in Mathematics, an M.S. in Software Engineering, and an M.B.A.More Content by Kevin Larsen