Not to be the bearer of bad news, but I recently found out just how many analytics, IOT, big data, and BI projects fail. And the numbers are staggering. Here's a list of articles and primary sources. What's interesting to me about many of these is the common issue around "technology solutions in search of a problem." Companies cannot define precisely what the analysis or data or IOT is supposed to do for the end users, or for the business.
And, it hasn't changed in almost a decade according to Gartner:
- Nov. 2017: Gartner says 60% of #bigdata projects fail to move past preliminary stages. Oops, they meant 85% actually.
- Nov. 2017: CIO.com lists 7 sure-fire ways to fail at analytics. “The biggest problem in the analysis process is having no idea what you are looking for in the data,” says Tom Davenport, a senior advisor at Deloitte Analytics (source)
- May 2017: Cisco reports only 26% of survey respondents are successful with IOT initiatives (74% failure rate) (source)
- Mar 2015: Analytics expert Bernard Marr on Where Big Data Projects Fail (source)
- Oct 2008: A DECADE AGO - Gartner's #1 flaw for BI services: "Believing 'If you build it, they will come...'" (source)
There are more failure-rate articles out there.
Couple these stats with failure rates for startup companies and...well, isn't it amazing how much time and money is spent building solutions that are underdelivering so significantly? It doesn't have to be like this.
Go out and talk to your customers 1 on 1. Find a REAL problem to solve for them. Get leadership agreement on what success means before you start coding and designing. There's no reason to start writing code and deploying "product" when there is no idea of what success looks like for both the customers and the business.
Skip the design strategy part, and you'll just become another one of the statistics above.
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