What To Do When Your Client Wants Sizzle Not Sausage

I love a good dashboard- really I do. So, you'd think I'd be pleased that a trend seems to be emerging that has more business folks becoming aware of dashboards and, by extension wanting to make use of them. But I'm not. Sure, I'm all for the opportunity to provide insight and a better means of managing business operations with an effective dashboard, but the trouble is far too many of the dashboards I've seen built don't do that. Sure, they're flashy, with widgets and gauges galore and often even visually appealing at first glance, but they're simply not designed to give the right sort of insight, or provide that insight in a way that allows them to be used effectively and efficiently. Now that's often not the fault of the person charged with designing the dashboard it may stem all the way back to the client - the person requesting the dashboard.

Unless you have a long standing relationship with your client, excellent rapport and tremendous trust it's unlikely that you'll have carte blanche to determine how they dashboard should look. In the majority of cases they will have come to you with a design already in mind. Chances are that that design will have been influenced by what they've seen elsewhere - be it in other dashboards, or in advertising from dashboard vendors or implementation consulting firms, many of whom seem to promote [just] the eye-catching nature of dashboards, showing off the latest and greatest controls and visual capabilities. And here's the hard pill to swallow, no matter how many of Few's books you've read, no matter how many industry awards you may have won for your prior dashboards, no matter if you have a PhD with a thesis written on visual cues and how people respond to them, your client is still likely to look at your with a mixture of confusion and disappointment if you suggest alternative design and layout options which are too far apart from their own ideas. If you just build and present him or her with what you believe is the better option then 8 or 9 times out of 10 he'll say it's not what he asked for or wants. Push the issue, spouting all of the theory you like, and you'll do little more than back him into a corner. He'll still want the same design, you'll still need to build it, and the company will have an ineffective dashboard - no-one wins in this situation.

So, what's the answer? Why not build prototypes for both - build him his, but also build what you think will work. Give your client what he wants and you may in turn get what you want, either through the chance to explain why you believe you dashboard layout is more effective, or he may just see it for himself and have a eureka moment. At the very least you will have opened the door for a discussion and now be better placed to have a conversation about the things you really need to know - what's the core aim of the dashboard, who will its audience be and what behaviour is it trying to produce, etc.  And, who knows, the same may happen in reverse, having seen your client's option made real you might have a similar moment and realise that it does in fact work more effectively than your own concept. That's not a bad thing, the company will have a usable and useful dashboard and you'll have discovered another design pattern that you can store away to be leveraged later.

Data Governance and the Not So Thirsty Horse

What's that old joke? The one about the deeply religious man caught in his house as flood waters rise around him.  Early in the piece as the waters are only a few feet deep a dingy arrives to take him to safety and he refuses, saying "I'll be fine, the Lord will look after me". Later, as the water rises and forces him to the house's upper story, a bigger boat arrives and those on board implore him to leave his house and come with them. Once again he answers "I'll be fine the Lord will look after me". Some hours later as he is perched dangerously on his roof with water lapping at his feet a helicopter descends and those on board urge him to leave before it is too late. But the man is insistent - "The Lord will look after me, I don't need you to save me". Not long later the waters rise again and the man is swept away to his death. Arriving in Heaven he is confused and, on being granted an audience with God, asks Him "Lord, I put my faith in you. I trusted you. Why didn't you save me?". God looks at him somewhat incredulously and asks "what more did you want? I sent you a dingy, a boat and a helicopter!"

On more than one occasion in my career I've marvelled at how much that joke paralleled what was going on around me. You may have even experienced this yourself at some time - demands coming from all sides, requests for clarity around data meanings, master data rulings, demanding to know why you don't know the ins and outs and business rules of obscure pieces of data that is about to be touched by some project or rather, and complaining because there's not enough documentation and other collateral in place - forcing them to have to spend more effort and dollars inside their project.  If this was indeed all missing then I could understand the consternation, but when a data governance framework exists and the business users understand and acknowledge that they (and not the IT group) steward the data and are the ones with the true knowledge of that data, then I start to bristle a bit. Maybe not the first time, or even the second or third time you walk people through what's available and how to make best use of, and leverage it, but sometime thereafter it's sure to come. I've noticed similar behaviour in other industries across my career, but it does seem to be remarkably pronounced amongst those working in IT.

Often I've put this down to some form of Not Invented Here Syndrome and accepted that some individuals will just not use what is put before them, be it through lack of acceptance, understanding or whatever. I'm sure that the phrase "you can lead a horse to water, but you can't make him drink" has passed my lips on numerous occasions. But lately I've started to think that perhaps this is not the answer. The horse really needs a drink, he just doesn't know the water is good yet! I've written before  about the need for persistence and tenacity when implementing data governance programs. Perhaps this situation offers an opportunity to create greater acceptance of data governance, data stewardship and the like. Meeting those IT folks placing demands on you half way may well work - give them a little of what they are asking for, do a bit of "their" work for them.  Sure, it's re-inventing the wheel to some degree, but nudge them toward what's already in place, shepherd them into the data governance framework and show them (via a few small wins) how they can leverage the data stewards working within it. My initial findings suggest that where those people begin to see that it can make their jobs easier they start to be more accepting of it and begin to use it to augment their other activity and in some cases make it first port of call. Given enough time I'm convinced we can make data governance advocates and champions of at least  some of these people.

I'm keen to hear from you if you've experienced (and leveraged) similar issues as I'm sure I'll encounter many stables full of horses who don't know they're thirsty across the rest of my working life!

Data Ownership and Data Responsibility Should Go Hand in Hand

Chances are that all of us who have tried to advance a Data Governance initiative will have had the data ownership discussion and socialized the idea that IT shouldn't own the data. In the earlier years of my data governance efforts getting acceptance of this concept was most often the first stumbling block. Common remarks from both the business and IT fronts reflected long established culture and practices in which data was seen as an IT focus - they managed it, wrangled it, invested and got to the root cause of data problems, and they held the responsibility of fixing data problems. This resistance, although frustrating, at least had a common theme which allowed me (and I suspect others like me) to build up a toolkit of arguments, presentations, stories and case studies to help move stakeholders toward an understanding that data is best owned by the business and not the IT function.

I've written about the need to keep working away toward implementing data governance before in my post on Thinking Like a Vogon. Having a bag of tricks built up and finessed over time is, in my opinion, key to successfully importing data governance at an organization. It allows those of us charged with championing data governance to keep working toward advancing stakeholder understanding and buy-in over weeks, months and years. Recently I've noticed a trend which has the potential to poke a hole in this bag of tricks, reducing its effectiveness and necessitating a rethink of how I engage with stakeholders. These days I encounter less push back when I propose the idea that IT doesn't own the data. The concept that the business owns the data now often seems to be easily accepted, with some business users going as far as saying "of course we own the data!"

Acceptance! It's all easy from here, right? Maybe not. While there seems to be a lot more widespread agreement that business users own the data this doesn't always translate into the best outcomes for data governance and improved data quality. Statements from stakeholders along the lines of "we own the data, but IT let us down because they can't get the data quality right and they don't understand our data" ring alarm bells for me. That one step forward may just have been followed by two quick steps back. What's missing here is responsibility. Ownership without responsibility is hollow and reflects an understanding which still has quite some way to go to reach maturity. I liken this sort of statement to a father boasting about the achievements of his children before reaching for the phone to arrange a nanny to look after them whilst they are home from boarding school. Just like we can't expect school teachers and others to take sole responsibility for shaping our childrens' lives and helping them through their problem times, business users can not claim to be data owners and then take a passive role only getting involved in data issues long enough to point the finger of blame at IT.

So how can we this new phenomenon be dealt with? Sure, a part of what needs to be done is updating the message and tailoring the tools and communication methods we use to address this new position. But, it's more than that, as data governance professionals we need to look for ways of showing those in the business with this view "what's in it for them". We should look to find success stories - show where there was demonstrable benefit gained when another business user started to take an active interest in the health and well being of their data. Even better, we should spend time with those business users who have already embraced not just data ownership but data responsibility as well, helping to make them into champions for the cause and assisting them to sell the benefits to their colleagues. The broader IT function also has a role to play here. We need to ensure that IT doesn't reinforce the existing culture, and as such there needs to be a little gentle push back when the business shows signs of pushing all data responsibility to IT. This need not mean a flat out "no", nor an abdication of any and all responsibility, but rather taking these opportunities to engage with business users, working with them as enablers rather just than in isolation as technical troubleshooters blindly trying to solve problems often without enough context or knowledge. By working together - making changes on both sides - IT will boost data context familiarity and those on the business side will get involved more often and earlier. From a management perspective, look to change IT policies if they talk about IT owning and managing the data, and think about establishing data reference groups.

No matter what approaches we take, there is one very important thing that can not be forgotten. We must help business people in their new roles as data stewards. We can not leave them to feel their way along. Build documentation and tools to help and guide them, recognise new responsibilities by modifying Position Descriptions and the way these people are measured and rewarded for performance. Not only will this signal that the organisation is serious about data governance and data quality, but it will also guide and encourage the stewards to perform better.

Why IT Can't See 2 Plus 2 Doesn't Equal 5 (And Why It's Not Their Fault)

How do a loaf of bread and a small bottle of orange juice lead to a blog post about data? Here's how. Last week I bought (or at least tried to buy) a $4 loaf of bread and a $2 orange juice. The young lady (a trainee, according to her badge) behind the counter cheerfully informed me that it would be $27.60 and seemed a little taken aback when I asked if she was sure about the price. She assured me it was right and even went so far as to turn her monitor around to show me - "See, there it is!". Risking the chance of becoming the customer from hell, I pushed my claim that the price was wrong. Another staff member (herself probably not old enough to have left school) was called to assist and tried her best to educate the problem customer - "Look, the computer says that's what it is, so that's what it costs". It took me leaving the goods on the counter and turning to walk out to have the duty manager come over and straight away see the problem and charge me the correct price.

I bet we've all had at least one similar experience and laughed about it, putting it down to "kids today" or asking "what are the schools teaching now?". But step back for a second and think - should we really be so quick to judge? Take a less critical view and ask what is really happening. The shop assistants are most likely casual employees, which means they spend only a few hours each week in that environment, they don't live and breathe the goods they sell and couldn't tell you the price of a loaf of bread without referring to a price list. While they can do their job and function largely without mistakes if enough boundaries are set and systems provided, when something goes wrong or when the pressure is on they lack the familiarity and deeper understanding which lets them sense when something (e.g. my price) is wrong. Chances are that the math skills of the two casual shop assistants were just fine, it was the lack of context of the individual prices and not yet having a confidence gained from situational familiarity which prevented them from recognizing a problem and speaking out with a different answer than that given by the system.

Is there a parallel between this example and how we work with data in our organizations? I think so! I've certainly heard (on more than one occasion) people from the business bemoaning that IT just don't get it, they don't understand the data. If the IT folks don't work with that data much, only a few hours per week, or in blocks of time many months or years apart, then that's not surprising. Even if they do work on the data more frequently they don't have the context gained from working with the data in the same way the business users do. What's apparent (at least to me) is that this gap in understanding is not the fault of the IT staff. If people don't work with a dataset closely and regularly enough to gain familiarity and understanding then even what are [to others] glaringly obvious mistakes may well go unnoticed. In the same way as the shop manager needs to find a way to better equip her staff to deal with situations like mine, we (as Business and IT Managers) need to find ways to better deal with data centric issues in our organizations. This may happen in a number of ways, for example

• embedding IT staff in the business to have them work with the data and alongside the business users 
• having business people take an active and accountable role in data migration projects and not leaving IT staff to make snap judgement calls about the data at the pointy end of a project to hit a go-live date, or 
• bringing the idea of data governance into the organisation and getting the business people involved with decisions around the data.

No matter which of these approaches you adopt I think two things should always be present. Firstly don't blame the folks at the coal face, and secondly introduce and promote the idea that data ownership belongs with the business not the IT department. Miss these opportunities and chances are that, just like me with my bread and OJ,  at some stage your company will be asked to pay a much higher price than seems reasonable.

Data Migration: Don't Ask What Should I Take, Ask What Can I Leave Behind?

I've written before about the importance of Selling the Data Migration Strategy and getting senior management buy-in. Recently I've been engaged in that sales job within my own organisation and just the other day met some resistance. On past projects disagreements around my strategic intent often took the form of objecting to my position that migration is an activity that should be front and centre for the business with them, rather than the IT or IS function, having accountability for its success. However, that wasn't the case this time, instead the contentious issue was that the strategy I'd written didn't explicitly call out the we should only migrate the minimum amount of data.

From my point of view this isn't something that belongs in an Enterprise Data Migration Strategy. It's not that I don't think that keeping the volume of data to be migrated down has merit. I don't need convincing that involving more data increases the cost and heightens the risks of overruns or impacts outside of the organisation's walls but, even more importantly, I don't think it's my place to be mandating a minimum data approach in a blanket fashion. For me, each of our data migrations will have different needs, different profiles and different levels of data to be migrated. And let's not forget that it's the business, not the technical staff, who should be making the calls about how much data to migrate!

This discussion got me thinking. There is value in keeping migration data volumes low so how could I, through the strategy, encourage this behaviour without presupposing it was the right course of action for each migration project? After some thinking I've landed on updating the data migration strategy to include a new principle:

Migrate the appropriate level of data. 

Expanding this a little, I see two key points that should be considered in finding this appropriate level of data.

• Firstly, a default position of migrating all available data is not where we should start. 
• Secondly, and following on from this, don't just ask the question "how much data do we need to migrate", but instead try the question "how much data can we afford not to migrate - what data can we leave behind?" 

With this question as the starting point I think there is a way of ticking all the boxes: the appropriate amount of data is migrated, the data migration volume is kept as low as possible, and IT doesn't drive how much data is migrated - the business still gets to make this decision.

The unanswered question here is how does the business decide on the appropriate level of data? I've used various techniques to help in the past and I've some new ideas as well, but that's a discussion I'll leave for another blog post.