Business today is a numbers game. Everything can be quantified - from obvious areas like inventory, on-time deliveries, or sales performance, to less tangible concepts like risk or customer satisfaction. Today's need to give a numerical value to everything is driven by the fact that once you can measure something, you can manage it and gauge performance improvements.

The trouble is, most people who work with data on a daily basis are not trained statisticians: analysis is typically a bolt-on activity to some other responsibility or skill-set. Crunching the numbers is a time-consuming, laborious exercise that requires a consistent, disciplined approach and a fastidious eye for accuracy.

To this day, the only tool provided by many businesses for ad hoc analysis is spreadsheets. They afford users a huge amount of freedom and autonomy in how they work. However, the blank canvas they offer can also be their inherent weakness.

There is an enormous amount of variability in the methodologies people use to work with data. The information is usually consolidated from a variety of sources, then manipulated to produce results which offer nothing more than a static account of what was or may have been true based on a snapshot of old data. There's no 'audit trail' with spreadsheets either. Conflicting versions may be stored in various folders, intranet and any one of multiple contributors to a spreadsheet can introduce an error that may not be detected until it's too late, if at all.

It's often more convenient to blame mistakes on data (a faceless, intangible object) than spreadsheet-based business processes (executed by people). But the truth is, data can be an immense power for good - it just needs to be properly organised and structured, analysed using a repeatable and traceable methodology, and presented in a meaningful way.

That's the thinking behind SAP Crystal Solutions. It gives everyday business users who aren't analysts by trade the tools to explore, report and visualise information without fear or limitation, or risking the integrity of the underlying data. Put simply, once you move away from the limitations of spreadsheets, you may find data isn't so unpalatable after all.

Is it really data you hate, or just the task of crunching the numbers? Follow the debate by connecting with Mr Data Lover and Mr Data Hater on Facebook.