We've spent the last two decades working with data. Most of it was locked up in spreadsheets, documents and web pages. And far too much of our time was spent getting it into a form that we could use - transcribing, reviewing, and double checking information - before we could even begin to analyze it.
We remember those analyses and reports that got updated monthly, weekly, or even daily to incorporate the latest data. We still cringe at how many of them had to be updated by hand. That wanton inefficiency always bothered us.
Not to mention that no matter how careful people are, errors get introduced by these manual updates. According to one study
, 94% of spreadsheets contain errors while another
highlights the significant financial impact these errors can have on an organization.
What about those analyses and reports that get created to look for infrequent events - like a pricing anomaly or inventory shortage? It's critical to know when these events occur, but often, no action is required. However, this kind of monitoring is expensive - both in direct costs and management time. Wouldn't it be nice to have automatically maintained datasets that are watched continuously for these critical events, and alert you when they occur?
These are just some of the limitations with the tools that are available today (including those that cost thousands of dollars a month).
There had to be a better way. We think we've found one. And it won't cost a fortune or require any specialized IT skills.
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at any time.