We analysed all the big data and discovered that the biggest reason for IT project failure is people – Big Data Informs…
We had failed at Data Warehousing, Business Intelligence, Core Competence, and quite a few other things, so some bright spark decided to give Big Data a shot.
The first task was to identify the reasons for IT project failure, globally.
According to the techies, Big Data was helping to move things on quite a bit, especially considering a previous attempt to analyse IT project ended tragically when the Data Warehouse coal-face caved in.
Before we gathered together all of the data in the Good Big Data project, we didn’t have a clue as to what was causing so many frequent, costly and dramatic failures.
We have an idea of where the biggest problems may be, but the Big Data team are afraid to pony up.
So, instead of boiling the ocean of data again, we decide to narrow the scope to Data Warehousing and Business Intelligence projects.
We were three months into this project and we’d still not achieved anything to brag about. So I put on my Project Manager’s hat and diplomatically engage up with the Big Data team.
“What the feck are you guys playing at?” I ask “You’ve had three months to come up with findings, and you have found nothing”
So, one by one, out come all the perfectly reasonable excuses and justifications.
“We didn’t know”, “this is very complicated”, “you don’t understand”, “I have the flu”. It all came out. We dance around the issues for a while, and then I set some tasks.
“I want you to find out what the prime motivators are for working on Data Warehouse and Business Intelligence projects”
“Is it for the cache of working on such projects?”
“Is it to bring real technical knowledge and experience to the party?”
“Is it to learn a technology, new product or technique?”
“Is it solely for the money?”
“Is it to ensure that the project lasts for as long as it can?”
“Is it to milk the budget for all its worth’”
“Is it to achieve the business objectives?”
“Is it to create inertia?”
“Is it to be on the inside, to ensure that the project fails?”
“Go and find out just what motivates people to work on these projects”
“Do it now and report back to me this time next week”.
So, I set and assign the tasks, clarify and address every current doubt, and leave.
Next week I go back. The team has a delegated spokesperson.
He says “we have addressed the questions you posed, and the answer is yes”
“Go on” I reply.
“It seems that to a greater of lesser extent, the questions you posed last week are all relevant”
“Fine, now tell me more”
“Well, there is not much to say, apart from the fact that what motivate many people isn’t exactly in the best interests of the projects in question”.
What am I listening to? No shit Sherlock!
“Can you expand on that?” I ask “Let’s open this up to everyone”.
So we have another three hours of discussion.
In the end what emerges is a classic set of metaphors and analogies that clearly identify why so many Data Warehouse and Business Intelligence projects go wrong, and indeed why this particular project cannot really deliver.
So, I wind things up.
“This is how I see it”
“3rd party suppliers and vendors want to see these projects last for as long as possible”
“The more licences, consulting days and bodies they can bill for, the better for them”
“The longer they take our money, and the more of it they take, the better it is for them”
“The more that innocent glitches, hiccups, procrastination and prevarication can be fabricated, forced and imposed, the longer everything takes, and the more that is billed for”
“So, better to over-promise, over-reach and under-deliver, than do things on time and to spec”
“What’s more, many people working on such projects will take the sides of the supplier, to the detriment of the client’s interests”
“Money is being leeched from healthy corporations to pay for bullshit death-march projects that deliver no value, bring no insight and can actually be a risk to corporate health”
“Projects are being financed by us, and used by others, as training”
“Corporations are being used as reference sites, even though the fundamental premise is nonsense”
“We are paying to teach people, bad-practice, worst-practice and no-practice”
“We are creating private armies of artful mediocrity, banality and imbecility”
“And we are proclaiming it as the way that business should be done in the future”
“Well, feck that! I don’t need big data to inform me that we are being taken for a ride”.
So, after ten days of contemplation, I formally close the project.
It had become a meta-example of what we were ostensibly investigating, analysing.and reporting on.
Yours strategically, Martyn