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The data diet: A healthy balance is just as important to data as it is to people

It is encouraging to see the level of emerging focus on the data-centric enterprise, putting data, at least, near the forefront on the business mindset. But how do we keep such a step change true to itself? If we continue with the same behaviors, will we not just keep getting the same results?

The data management industry and its collection of practitioners can be a fickle beast, constantly pursuing the next "Great Thing," inventing ways of doing pretty much the same as before with a new name, a slight technological twist with a new set of jargon which needs a new set of skills to deliver... Selling the "New You" message and then blaming you for doing it all wrong when things don't quite work as expected.

This is not a new situation, it has been going on for decades. Each iteration attempts to supersede as much as possible, with a new set of evangelists and detractors locked in a bitter generational rivalry.

Each wave, in theory, should make the overall situation better for business. The "old is bad, new is good" paradigm is applied to convince businesses of reaching those greener pastures. But nothing seems to have time to settle and produce results.

There is another industry area that behaves in similar ways. The dieting industry itself and its related beauty and body image partners... and some of the behavioral parallels make interesting food for thought (excuse the pun). Businesses struggle with data in the same ways that people often struggle with achieving a balance of healthy living, stress and well being. So here are some lessons we might learn from our everyday personal experiences of lifestyle behaviors.

Lesson 1 - Focus on the long game for long term results

A fundamental change of personal lifestyle is a huge forward commitment, requiring continual focus, unwavering determination and that inner fire that drives you forwards every day to reach your goals. This does not mean that short term achievements are not important. They are the constant and frequent reminders of progress made that help to keep you on track. However, they must be seen as stepping stones to the end game, a measure of progress to success, but not success itself.

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An employee passes banks of computer hardware connected by colored cabling inside the Barcelona Supercomputing Center (BSC) in Barcelona, Spain, on Thursday, Feb. 20, 2014. A smart city initiative, which also involves rolling out electric vehicles and bikes and making neighborhood blocks' energy output self-sufficient, widescale deployment of sensors and quick-response codes to 8,000 points around the city by the end of the year to provide location-based information to anyone with a smartphone, could save Barcelona 3 billion euros ($ conv) in the next decade. Photographer: David Ramos/Bloomberg

The dieting industry is a master of the "quick wins" message. We are constantly bombarded with rapid weight loss pills and potions, 10 minute exercise videos accompanied with the usual "use this device at home when you have time and you could look like me" mantra, expensive body shaping procedures and scientifically "proven" rapid weight loss diets... all designed to tempt us to buy into the quick result.

But as we all know, most of these have some initial impact but fail in the longer term. The videos and devices find their way into the garage; the pills, potions and diets get overrun by the hubbub of day to day life; the procedures and science get proven to be not as able as first thought. Then we give up... until the next time... but very often, never achieve what we wanted.

This is a personal lesson that we should take note of more often within our data management endeavour. Quick wins that fail demotivate us and, in the end, make long term goals harder to justify value against cost. How can we possibly know which is which? Well, this is where some foundational data management thinking needs to be applied to bring us all back to our senses.

A healthy balance in both industries is based on a similar set of life long and enduring fundamental premises and equations... generally consuming no more calories in a balanced diet than your body burns, exercising regularly, reducing harmful lifestyle choices and creating a long term work/life/stress balance leads to a positive long term health result.

We must, therefore, find the similar long term paradigm for data management based on fundamentals of enduring data governance, business collaboration, principle and method... and deliver all these as a continuous service to the entire business, not a program or project. We should be more wary and analytical about new waves, fads and data technologies promising the earth now, always seeking in them... a clear and true long term path to business value.

So the lesson is : be consistent, enduring and end value driven.

Lesson 2 : Face the whole problem

To achieve a long term balanced and healthy lifestyle, one must face the fact that you must take a coordinated approach, addressing all aspects simultaneously. Eating less fatty foods on its own does not guarantee significant long term weight loss, exercise on its own may not give you that "six pack" you so desire.

The dieting industry is just as fragmented as data management in this area, with hundreds of methods and approaches all competing for your attention. It is small wonder that people can find it difficult so see and choose what works and what does not with so many claims of magic bullets out there, especially because very few are holistic in nature. They tackle a specific problem area only, like your abdominal body shape, and not the interconnected whole, your lifestyle that led to the "beer belly" in the first place.

When you take a coordinated approach across all aspects, you get more than just accelerated results, you get better and more sustainable results... you get synergy. This is where data management can start to really show its true enterprise value, if it wishes to, and make the whole enterprise fitter, leaner and agile.

A coordinated full scope data diet approach will make data management be:

Seamlessly Interconnected, Collaborative and Federated

When governance, quality, modeling, architecture, security and risk, change and knowledge management (and all other aspects and disciplines!) work together and reach out into all corners of the business, data management not only becomes more fit for purpose... able to react faster and achieve more... but an integral, value creating line of business in its own right.

With less Data, Resource and Technology creating more Value

This is a key part of the data diet approach. The goal is to actually put your data on a diet... have less of it, copied to less places, with less technology footprint, less dedicated people needed to manage it and reused as much as possible. This can be achieved only when full understanding and coverage is gained, allowing areas of "fat," "excess" and "poor choice" to be identified and eliminated over time.

Accepted, Understood and Utilised

A coordinated data management discipline projects a more professional outlook to the business. This is rewarded with acceptance, engagement and increased mandate over time. Any business function that clearly has got its act together will command a greater level of respect and influence. When you can demonstrate that you understand the data landscape of a business better than the business themselves, they will come to you for the answers every time.

Standardised, Repeatable and Assured

When the different areas of data management work as a single unit, its operating model becomes more standardized and repeatable. The business knows how to engage and what to expect from those interactions. Repeatable processes are then able assure a quality service that can be relied on to deliver.

So the lesson is : always tackle the whole problem from all perspectives.

Lesson 3 : Treat the causes and not the symptoms

Of course, making progress in all areas takes time and commitment, but it is the only way to ensure ongoing results that can be measure from all perspectives. More exercise may initially lead to increased body weight through muscle growth, but at the same time lower blood pressure and resting heartbeat. There is cause and effect always in play here.

The UK healthcare industry spends billions of £ every year treating the symptoms of poor lifestyle choices. It also makes great efforts to proactively educate us to live healthier lives... and still, despite also the dieting industry spending vast resources to get us to use their products, services and approaches... the western world, especially, still has a huge problem in this area.

So, you might come to the conclusion as me, then, that all this effort is actually not solving the right problem, the causes, but mostly the symptoms. Why do we live such unhealthy lives? This is because the root causes are deep seated, complex, interrelated and systemic in human nature.

I will not get into the nature vs nurture debate here, but I will say it all plays a part in the development of a system of behaviors not necessarily best suited to optimal lifestyles. Sometimes, we are our own worst enemies.

Root causes for poor lifestyle can be easily identified but are hard to treat... especially when external factors, past trauma or socio-economic factors are in play and cannot be easily eliminated. But then, not all people exposed to the same set of factors end up with the same lifestyle. There must be a differentiator altering the result... an even more deep-seated root cause? Establishing the root causes of data management failure is not that hard either, but even these may be just symptoms.

There is a more fundamental cause... CHOICE

So when we look at the systemic social and cultural behaviours of the average business to data management, we should not be surprised that similar patterns emerge in what is, primarily, a people oriented discipline that, sometimes, does not act in its own best interests or the common good of the enterprise as a whole.

The data diet approach must therefore confront the "agony of choice" head on and direct attention to applying it to alter long term and systemic data behaviors. Just as a person flips that mental switch and decides to embark on their fundamental and enduring lifestyle change, so must a business struggling with data management do the same. Cause and effect must be permanently realigned and then constantly refined.

Here are some aspects to consider:

Lack of Belief

There must be belief that the full scope end goal can be achieved, through a clear path from right now to a measurable result that represents a desired level of success in all areas. Both the dieting and data industries struggle in this area, unable to agree both what the journey should be and what the result would look like in real terms. It is imperative that this must be addressed first, belief is a powerful ally when cultivated and continuously maintained.

Lack of Motivation

Where there is no belief, there is also little enduring motivation for action. Activities are sporadic and prone to falling away in focus. The dieting industry is somewhat better at this, well at least, the more successful methods have inbuilt group participation and motivational elements to make success more likely. Also, it has many people who have clearly gone through the process and can be a great motivational boost when their story of success is told. The data industry needs to get much better at this.

Smoke and Mirrors

But we must also be very aware of false success, or success built on a false premise where the root causes have not been addressed. Somebody who takes a dramatic approach of physically removing all excess fat from their body may well be able to show significant visual improvement. But this can all be swept away by a lack of a continuing foundational healthy lifestyle. The data industry also suffers from this in many ways, for example, implementing an MDM solution at great cost, only to then continue to buy silos that can't communicate with it or continuing to store master data locally. So the root cause has not been removed.

Fear of Failure

This can be both a motivator and a barrier, leading sometimes to some very self destructive behaviors to compensate from a lack of root cause solutions. Fear of not reaching a weight loss weekly target at a group show and tell session may lead to both a renewed sense of purpose for next week... or a crumbling of will and collapse of motivation.

This must be addressed by remembering that it is only the small daily steps and long term continuous activity that produces sustainable results. Failure must not be seen as an absolute, a point in time event that can not be reversed. The cure for this will always be to keep taking those small steps in the right direction, there is no other way.

Resistance to Change

Change can be painful... and sometimes literally in the dieting industry. The status quo is a very powerful animal and it bites hard when challenged. Even with belief and motivation that the data problems can be solved in place, there still needs to be a compelling reason to solve it. And whatever that reason is, it will require change of both behavior and activities. The dieting industry has spent significant effort cultivating the concept and visualizing the idea of the perfect body, mind and soul, and this results in a tipping point where, in the mind of the individual, change becomes an essential thing to do right now.

Such tipping points, however, seem to get missed in the data industry. GDPR in the EU being a huge one that should have been the compelling reason for change across all EU enterprises. But for some reason, even this legal requirement has been met with much inactivity and, at best, a fragmented and least available response mindset. This is a huge problem for the data industry.

Lack of Resources

So maybe such resistance to change is due to not having the resources to do anything about it. Individuals may also wish to do things differently, but cannot see how they can achieve such changes without resources they do not possess. Enterprises, however, should be able to re-prioritise their people and money much more easily if they can see that it is both not a huge additional long term cost or they actually have most of the resources already... but are just not using them as effectively as they could.

The argument must be made that you do not have to create an enormous data department and hire hundreds of specialists, because the business already does most of this (managing data) already...just not very well, and this can be fixed within the business itself. Data people can only assist the business to fix their own data problems, they cannot do it all themselves.

Bad Advice

Then comes the inevitable fly in the soup, so to say. The usual suspects are then asked to assist in the process. We all know who they are. They bring their magic (spot the reference) friends with them and everybody makes a pile of cash doing what they've always done, dividing the problem up in to disparate "projects," dissolving the holistic mission into thin air and perpetuating the problem for the next time the enterprise feels it is ready for another bite at the cherry. The best intentions lost to commercial contracts, delayed timescales and disconnect solutions. There is much bad advice also in the Dieting Industry, born from the same conflicts in commercial interests.

Bring these aspects together unchallenged and unsolved, and you will stay in a state of data management paralysis, treading water frantically but getting nowhere fast.

So the lesson is : solve root data behaviours and start making better choices

Lesson 4 : Get the right sort of help

Getting the help you need from the data industry can be more difficult than you might think, this is why so many businesses opt for the well known generalist systems integrators and consultancies to assist them more often than not... at least they can "talk" business and give you some feeling that, initially anyway, all will be well. They are very good at cultivating that feel good factor, they've had year of practice at it, and they win most of the time.

But this is like somebody going to a sports shop to get holistic lifestyle advice. You won't get it; only advice on possibly using the sports equipment they have in store. Then they'll sell you a full jogging kit, expensive treadmill and protein pills, and send you on your way to sort it all yourself.

So you then go to a data conference and you listen to the technical seminars and see the demonstrations and walk around the exhibition stands... all of them... trying to find how to solve your data problem. You get lots of enthusiastic engagements from the sales teams at each stand... smelling fresh blood in the marketplace... but everybody seems to be suggesting a different solution for a small aspect of your total problem. You can't see a total solution, just lots of disconnected ones.

The data industry does loads of great stuff, but as a holistic industry we have a long way to go. Advice needs to match the end game, otherwise it will never happen.

So the lesson is: Get advice from people who desire the end game you do.

The data diet is a tough regime, not for the faint-hearted and not a fleet of fancy. Learn these 4 lessons and you may stand a chance of creating a more healthy data enterprise.

The choice is up to you.

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