For many businesses, big data can seem ubiquitous and overwhelming. Even beyond the sheer numbers involved, knowing what data is and isn’t useful is not an easy task without the right systems and processes.
While this could be viewed as a mountain not worth climbing, effectively managing and valuing your big data can provide a substantial competitive advantage. Even if there’s not a potential wider business use, if you don’t know how much your data is worth then you don’t know how much you should be spending to keep it secure.
Infonomics a new paradigm
If you’ve never thought about this before, you’re not alone. The science of valuing data is so new that Gartner research VP Doug Laney coined a term for it: infonomics, or the economics of information.
While some organisations will prefer to just value their data in relative terms, like how accurate it is and how useful it is in relation to the business’s goals, others may opt to use the financial models Laney developed based on standard accounting practice for valuing assets.
Non-financial methods
The intrinsic value of an information model doesn’t consider the business value at all, instead putting the focus on data quality. How accurate, complete, timely and accessible is the data? How unique is the data to your organisation – do you have market data not available to your competitors?
Different companies will use a variety of characteristics, each weighted differently, to come up with an overall score.
Alternatively, an organisation may choose to value the information by measuring the data characteristics in relation to business processes. The performance value of information is more of an empirical metric as it measures what impact data has on KPIs over time.
For example, would your salespeople be able to close deals more quickly if they had accurate, real-time stock data? If you can’t answer this question now, Laney suggests an experiment – where one of your sales teams has access to this data and another doesn’t – to see if the performance of the teams is different.
Financial methods
In recent years, whether through online or offline attacks, many organisations have had to recover from a complete loss of data. As part of that process, they’ve needed to answer the question: “How much is our data worth?”
Based on standard accounting principles, a method was developed to quantify the information’s value based on its replacement cost. How much revenue was lost from the destruction of the data and how much would it cost to reacquire it from scratch?
The economic value of the information model refines the performance value model by using revenue instead of a given KPI. Again, using the sales example, an experimental group has access to real-time stock data and a control group doesn’t. Then, instead of looking at how quickly sales are closed, you’re looking at how much revenue the salespeople in each group generate minus the cost to acquire and administer the data.
The final model is based on the market value of your data. How much revenue would your data generate if it was sold, rented or bartered? While open markets for data aren’t very common – legal ones, that is – what your data would fetch on the open market can be estimated by comparing it to similar data from syndicated providers.
Insight as valuable as data
Valuing your data using any of these methods will be a painstaking process, but the insights gained may be almost as valuable as your data. You may find that your data is more valuable than you thought it was and you’re not spending enough to protect it as a result. Alternatively, you may have some expensively protected data that is not really worth that much.
Whatever the result, you won’t know without going through the process of determining how much your data is worth.
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