Martyn Richard Jones
New York City, 18th January 2017
I’ll make this short, sweetish and to the point.
These are the arguments that CEOs need to know about Big Data.
It was written for CEOs and those who provide independent advice to CEOs.
If you are someone who wants to be prepared for CEOs who are armed with the realities of Big Data, then maybe this is for you too.
Point One: Big Data is bullshit
What you have heard about Big Data is wrong. Most Big Data talk is cultivated babble, bluster and bullshit designed to get you and your organisation to part with your cash, time and effort.
Point Two: Heads up. Big Data bullshitters don’t do tangibles
For all the adjectives like amazing, awesome and incredible that Big Data gurus and bullshitter use in the surfeit of Big Data bullshit articles they they publish, you will be lucky to get one significant example of a tangible, coherent and verifiable Big Data business success story.
Don’t be suckered by the Big Data bullshit. If Big Data pundits are so sure of their ability to generate value for you, make sure the projects that you commission provide risk and reward for all parties. Tie your vendors’ rewards to your own ROI from Big Data. No tangible outcome from Big Data, no tangible benefits for the vendor. Simples. Make sure your Big Data contract is heavily weighted to outcome based payments.
This will ensure that solution providers only get paid if a Big Data project actually provides tangible benefits to your organisation.
So, don’t believe the Big Data bullshit that Big Data pundits are pushing. Take particular caution of the opinions expressed by those who represent vendors, whether what they are selling is offshored services, management consulting, hardware, software or vapourware.
Point Three: Beware. The IT industry has vested interests
The IT industry is geared up to maximise the advantages accruable from selling you and the people working for you the illusion that Big Data is the next big thing in revolutionising how we do business. It’s no coincidence that the hard-sell on Big Data is like a modern day equivalent of a digitalised mass marketing campaign for today’s snake-oil medicine. The IT industry is running short on margin, Big Data is one means being used to try and make up for increasing shortfalls.
Of course there is nothing wrong with people trying to make a buck, just make sure they don’t take you for a ride whilst they are doing so.
Point Four: FYI Big Data is technology, not business process
Big Data is a set of simple technologies designed to run on low-cost commodity technology products. It is technology to ingest and search unstructured data that will come from computer systems that are typically not central to your business operations. Unless of course you run your business via Facebook, twitter or LinkedIn.
It is a technical configuration not a business solution nor a silver-bullet.
Remember this, no matter what the IT people tell you, cheap hardware and open-source software does not equal cheap and beneficial and valuable project outcomes. A lot of disruption and damage can be inflicted by a rogue Big Data project that sap your enterprise of time, effort and money, and dislocate and frustrate day-to-day business operations and objectives in the process.
Point Five: Vital. Make sure the eyes are on the important data
By far your most valuable data is stored in your businesses operational systems. The bread and butter systems of all business.
In order to add tangible business value, data is sourced, packaged and provided to the business users as part of the Data Warehousing process. It delivers appropriate, adequate and timely data to where it is needed in the organisation. Not by magic, but my deliberate design that can be changed as rapidly as business change demands.
This data is provided in order to support decisions and to help determine actions. At best, Big Data can augment data provided by the Data Warehouse.
However, to pretend that Big Data will replace Data Warehousing, or modernise Data Warehousing or revolutionise Data Warehousing, is the biggest and most misleading bullshit line in the field of IT.
Point Six: Good sense. If there is no tangible business benefit, it’s bullshit
Whatever it is, if there is no tangible business benefit, then it’s bullshit – in business terms, technical terms and good sense terms.
Which leads me to a key question that I invariably ask people when I am brought in to create a new strategy, architect a new solution, build a new business platform or validate business process reengineering (or whatever else), and that question is simply “to what ends?”
In my experience, Big Data initiatives generally fail to provide any coherent, cohesive or realistic response to the challenge implicit in that question – to what ends?
Also, remember that when it comes to Big Data we don’t stop being totally and mutually inclusive and exclusively exhaustive in questioning the raison d’être. Or, to put it more succinctly, there are no limits to the use of the question “why?” when it comes to Big Data.
Over the years I have had little problem in providing answers to the questions about business benefit, but sometimes it requires some effort to unearth and identify potential benefits. If that isn’t possible for a Big Data initiative, no matter how attractive the attendant marketing guff appears to be, then it’s probably not something that’s worth giving the time of day.
Point Seven: Business ideas. If there is no business benefit stepping forward, then it’s bullshit
Trust and verify.
I have told you what I think. However, don’t take a word of this on face value. But don’t ignore it either. I suggest getting someone you trust (or maybe it will require more than one person who you trust as a subject matter expert) to verify the factual elements of this brief article, and then you make up your own mind.
Of course, not everything we do needs to drive cash value. But, Big Data is definitely a case where lack of a tangible business benefits should be a definite sign that it isn’t worth contemplating. If the Big Data business case cannot satisfactorily the question “to what ends?” then the Big Data business case sucks and should be dumped.
I am personally convinced that what I state here is actual, relevant and verifiable. So my advice is to trust, but, to verify for yourself.
And so it came to pass
There you have it. All you need to know about how to be on the side of the business angels when it comes to Big Data.
Treat all Big Data as bullshit and you won’t go far wrong, even if your business eventually finds a way to make money from Big Data. You’ll thank me for it.
Before I conclude. Two final pieces of counsel.
Never allow anyone in your organisation to augment their pension fund by initiating any kind of Big Data, MIS, Business Intelligence, Enterprise Data Warehousing, Artificial Intelligence, Machine Learning or Data Science project or programme. You don’t want that sort of conflict of interest to be inflicted upon your business.
Try not to outsource any aspect of your business IT that has anything substantial to do with core business processes, and never ever offshore anything that is inextricably linked to the value propositions and intellectual capital of the business, and this includes Data Warehousing, Business Intelligence, Analytics and Big Data.
All things being equal, if you need any additional advice when it comes to Big Data, Data Warehousing or any aspect of Data Architecture and Management in business, then give me a call. I look forward to doing business.
Many thanks for reading.
I can be contacted on this and other subjects via my email address: firstname.lastname@example.org
You may also be interested in joining The Big Data Contrarians group on LinkedIn
Bill Inmon has written a great piece on Big Data value which can be found here: https://www.linkedin.com/pulse/fishing-where-fish-simone-molenaar
Wow. I came here expecting an intelligent, clear critic of the downsides of Big Data – as a computer engineer and startup founder, sounds like you don’t even understand it my friend.
I’ll say one thing (in major contrast with this poorly thought-out and arrogant article) – do some research on Big Data and its actual uses and projections by people who understand it. Then, attempt to understand how its implemented and when and why each implementation could be useful.
Maybe you’ll look back on this article one day and wonder if this is bullshit!
Martyn Jones said:
“Maybe you’ll look back on this article one day and wonder if this is bullshit!”