25 Thursday Nov 2021
I am quite a fan of many aspects that sit under the Data Mesh umbrella. However, when it comes to a proper fact-based understanding and analysis of the history, place and architecture (business, data and technical) of Data Warehousing, the leading exponents of data mesh have it woefully wrong.
Therefore, the purpose of this blog article is to set the record straight.
23 Sunday Dec 2018
Posted in Assets, awareness, behaviour, Best principles, Brexit, ethics, goodstrat, Martyn Jones, Martyn Richard Jones, Offshoring, Outsourcing, Politics, Remain, statistics, The Guardian
Photo by Pixabay on Pexels.com
Martyn Richard Jones
Madrid, Sunday 23rd December 2018
What’s all this fuss about Jeremy Corbyn and Labour’s Brexit strategy?
Despite Liberal Democrats, Blairites and most of the national media ramping up the righteous outrage about Corbyn stating the bleeding, bloody obvious (see e.g. http://www.theguardian.com/commentisfree/2018/dec/23/labour-remain-jeremy-corbyn-brexit ) nothing has changed.
So, what are the facts?
03 Monday Nov 2014
Posted in Ask Martyn, Best principles, Data governance
Tags
Big Data, Business, business intelligence, data governance, data management, Data protection, Data Warehouse, privacy, Strategy
There was a time, when absolute discretion was an important maxim in the relationship between a liberal professional (doctor, banker, solicitor, architect etc.) and their clients, but times have changed, and are continuing to transform at an ever increasing pace. Continue reading
03 Monday Nov 2014
Posted in accountability, Ask Martyn, Best principles, deceit, pain
Tags
accountability, aspiring tendencies in IM, ethics, good job, information management, Information Technology, IT business, Organisational Autism, organisational awareness, professionalism
“Anger is the enemy of nonviolence and pride is a monster that swallows it up.”
Mohandas Gandhi
The predominance of strength and innocence, better known as ignorance and arrogance, is undermining Information Management, and in turn is ensuring that many Data Warehousing and Decision Support initiatives are disappointments.
2015 will again give IM professionals the opportunity to regain some dignity and professional integrity.
First, by recognizing that there are grave problems within IM; then slowing down and halting the toxic trends, carelessness and bad practices; and then in subsequently, reversing, through intelligence, perseverance and integrity, the ingenuous and decrepit habits that still trouble the profession.
In the rush to the bottom we throw excellence in analysis, architecture, engineering and business understanding, under the bus. In IM as well as in many other branches of IT (Information Technology), mediocrity has become the new excellent, regular the new exceptional, and shoddiness the new normal.
Whether it is in Data Warehousing, Big Data, Business Intelligence, Analytics, Decision Support or Data Integration, we see that professional integrity and ethical behaviour – already enough of a rarity in IT – is being repeatedly trumped by short-term expediency, wilful witlessness, and the cultivation and perpetuation of dogmas, dysfunctional behaviour and dubious doings.
The Information Management sector is rife with elaborate charlatanry, partisan expediency and wilful self-deception. There is not a day that goes by in which we are not submitted to an avalanche of contemptible claims from rogue IM evangelists, DW neophytes and unsophisticated opportunists, who chose to simply make things up as they go along.
It is in the best interests of IM to raise the profession out of the ditch; to reform the profession from the inside; to drive sea-change improvements in knowledge, quality and professional integrity; to ensure a drastic reduction in destructive hype, deception and dogma, and, to show the artless charlatans, chancers and snake-oil merchants the door.
Data Warehousing and Decision Support – if done right, and for the right reasons – can deliver tangible benefits to many organisations. Simply stated, if business information has a value in the realm of business and strategy then it should be treated as an asset, if it is an asset then it should be managed and nurtured as such, which means aiming to do the right thing right, first time, every time, whilst focusing on maximising confidence, availability and agility.
File under: Good Strat, Good Strategy, Martyn Richard Jones, Martyn Jones, Cambriano Energy, Iniciativa Consulting, Iniciativa para Data Warehouse, Tiki Taka Pro
13 Monday Oct 2014
Posted in accountability, Ask Martyn, awareness, Best principles, governance, leadership, public, technology
My sister Liz was part of a group that offered support to the striking miners of Wales, Scotland and England.
They organized a public fund raiser and invited the politician Tony Benn to speak.
The trouble was that none of the support group were Labour people, and they weren’t the greatest admirers of British parliamentary democracy and the Labour party.
So they sort of moved the problem up-stream.
They asked me if I would be Tony’s minder for the night.
They didn’t actually use the word minder, but that what it was mainly about.
Because they probably reckoned that as a long time Labour member myself with an unquestioning belief in Westminster democracy, we might actually be able to talk the same language.
I had dinner with Tony that day, just before he was due to speak.
The conversation came around to Tony’s book, Arguments for Democracy.
Well, actually I had pushed the conversation in that direction.
I mentioned that I had read it at least three times, and that I used some of the examples from the book in my work.
In particular the part dealing with the questions that an elected politician and Minister of State must ask any technologist who is proposing a new projects or programme.
I told him that I had applied these principles in a large US multi-national corporation called Sperry, notorious for its Republican hue, its affinity to the Department of Defense, intelligence agencies and Federal Government, and its alleged hire and fire culture – which somehow I managed to evade for almost thirteen years.
He found that quite funny, in a surreal way.
I said “over the last eighteen years I have often used the following questions, which you designed to indicate that the role of the elected representative and minister is not to seek to reproduce the expertise, which he or she could not do, but to see that the expert is subjected to rigorous cross-examination on behalf of the people”.
Anyway, to cut a long story short, I shall now move on to the crux of the matter.
But before then, a final comment.
Because I have been using these lines of enquiry primarily in business I have replaced the role of the government minister with that of the Project Board and project stakeholders, and the role of the “people” with the role of the organisational stakeholders and the business community.
So here you have it. The leader must ask the technologist:
First, would your project, if carried through, promise benefits to the organisation, and if so, what are the benefits, how will they be distributed and to whom and when will they accrue?
Second, what disadvantages would you expect might flow from your work? Who would experience them? What, if any, remedies would correct them? Is the technology for correcting them sufficiently advanced for the remedies to be available when the disadvantages begin to accrue?
Third, what demands would the development of your project make upon our resources of skilled manpower [I would include demands on all organizational resources in this context, and would also ensure to enquire about the availability of those resources]
Fourth, is there a cheaper, a simpler, and a less sophisticated way of achieving at least part of your objective and if so, what would it be, and what proportion of your total objective would have to be sacrificed if we adopted it?
Fifth, what new skills would have to be acquired by people who would be called upon to use the product or project which you are recommending, and how could these skills be created?
Sixth, what skills would be rendered obsolete by the development that your propose, and how serious a problem would the obsolescence of these skills create for the people who have them?
Seventh, is the work upon which you are engaged being done, or has it been done, or has it been started and stopped in other parts of the world, and what experience is available from abroad [elsewhere] that might help us to assess your own proposal?
Eighth, if what you propose is not done, what disadvantages or penalties do you believe will accrue to the organisation, and what alternative projects might be considered
Ninth, if your proposition is accepted, what other work in the form of supporting systems should be set in hand simultaneously, either to cope with the consequences or to prepare for the next stage and what would the next stage be?
Tenth, a final and very important question. If an initial decision to proceed is made, how long will the option to stop remain open, and how reversible will this decision be at progressive stages beyond there?
Later that evening I had to drive Tony to the station to catch his train to Oxford.
We were late, it looked like we would miss the train.
In the car I asked Tony if he would care to sign my copy of Arguments for Democracy.
He did.
Trouble was, in the rush he didn’t pick up anything to read on the train and he hadn’t brought anything with him.
So I gave him The Chomsky Reader. Which just happened to be on the back seat of the car.
As one would.
Anyway, off we rushed. Hell for leather through the empty streets of Worcester.
We arrived at the station in time to catch the train.
Job done.
12 Sunday Oct 2014
Posted in Architecture, Ask Martyn, Banking, Best principles, Big Data, Business Intelligence, Creativity, Data Warehouse, Dogma, Knowledge, Peeves
Tags
Banking, Behavioural Economics, Big Data, Bill Inmon, business intelligence, data integration, Data Marts, Demagogism, Dogma, enterprise data warehousing, hadoop, Information and Technology, information management
This weekend I read a piece on the Information Management website by Steve Miller with the title of Big Data vs. the Data Warehouse. It’s an old piece, from March 2014.
It was in response to a piece penned by Bill Inmon, titled Big Data or Data Warehouse? Turbocharge Your Porsche – Buy an Elephant, in which he singled out for criticism the ad campaign of a big-data and Hadoop promoter.
10 Friday Oct 2014
Posted in Ask Martyn, awareness, Best principles, Big Data, business, Business Intelligence, Data Warehouse
Tags
Big Data, business intelligence, Commercial IT, Corporate IT, Data Warehouse, IT business, IT Strategy, Pimps, Pundits
The IT business suffers a malaise, it also affects other businesses. In IT, like in other lines of business, much of what has been made is eventually side-lined and forgotten. If it was ever on the radar in the first place. Continue reading
09 Thursday Oct 2014
Posted in Analytics, Best principles, Business Intelligence, Executive, Extract, Knowledge, Offshoring, Outsourcing
Tags
Behavioural Economics, Big Data, Business Enablement, business intelligence, Business Management, business strategy, Challenges, Creativity, Data Warehouse, Organisational Autism
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
09 Thursday Oct 2014
Posted in Ask Martyn, Best principles, Creativity, Excellence, Methodology
Tags
Behavioural Economics, Business Enablement, Business Management, Information Technology, Strategy
I came into IT at the tail end of the seventies when I joined one of the original computing pioneers.
It was a conservative company lead by veterans, engineers, accountants and sales, with many ties to the US administration, the Department of Defense and intelligence agencies.
My interests at the time were in philosophy, politics and economics. I liked to meet people and talk, and also liked to help people solve real-life business problems, so I was always engaged with the corporate staff and executive management rather than with the real hard-core technicians and engineers.
The thing is, I had no idea what constrained IT, so I never had that baggage when thinking about solutions.
08 Wednesday Oct 2014
Posted in Ask Martyn, Best principles, Business Intelligence, Strategy, tactics
What triggers a review of organisational strategy?
Well, typically organisations usually shy away from major strategy reviews when things are just ticking over quite nicely. The old axiom of “if it isn’t broke don’t fix it”, has a lot of power of persuasion, even in cases where the logical and coherent thing to do would be to continually review strategy.
Many companies reach for a new strategy when one fine day they are rudely awoken to the fact that they are not doing as well as they once did.
Basically, organisations will seriously think about strategy at times when stakeholders and shareholders start to kick up an almighty ruckus.
With this incentive behind them, organisations embark on the tortuous journey to a new organisational vision and strategy. Or do they?
For the sake of brevity I will exclude all of those organisations who look at the strategy process as a great big exercise to produce an organisational wish list, for as warm and fuzzy and socially responsible it might be. For as laudable these initiatives might be, they just don’t count as strategy in this paper.
So, in the process of arriving at a strategy, we need to address the vision, the challenges to the vision and coherence of the executable strategy. In order to address these core elements effectively we need to be able to access as much relevant and actual information and data we can in order to generate, test and categorise our hypotheses.
So, where is this information and data and how can we get it?
I will take a brief look at three major areas of information and data, which roughly correspond to:
Now it must be made clear, upfront and clear, that data in an organisation is subject to the vagaries of data quality assurance. Therefore, in a far from perfect world, we will usually be looking at the following issues and will have to work with them, no matter:
GOOD STRATEGY 