Tag: data

A Thought On An Afterthought

I was thinking about what my third post was going to be about when I noticed what I had done on my earlier posts. I had neglected and rushed my metadata! Feeling a sense of shame, I then proceeded to clean up the elements I had rushed and scratch my head over the ones I had left blank. If you are wondering why I decided to obsess over this, it was because I broke one of my professional cardinal rules around data. I treated data as an afterthought.

What is the big deal then? Over the years I have been reading and researching around why data related projects fail, as well as being involved in a few myself. Depending on the source, somewhere between 60 to 85% of data-driven projects ended in failure. When I first came across this, my first question was how could this have even happened, especially on projects that were specifically about data.

I then proceeded to try and find a common answer across the web and in journals and came across many things. Some of the most common things I saw included:

  • Poor executive knowledge of data and lack of strategy: Here I basically saw that they underestimated the task in front of them and failed to treat data as an asset. Also, they had no strategy on how data would work within their organisation. Lack of a centralised data function also played a factor.
  • Lack of appropriate tools: It was deeply disheartening to see companies use Microsoft Excel as the backbone of their Data Quality/ Management strategy instead of the appropriate industry tools.
  • No data team: Leave it the Developers and the business experts. As talented as they may be, they were not data specialists and the people that were assigned to these projects had to be the jack of all trades from a data perspective. Meet the Data Architect Governor Engineer Steward Analyst.
  • Not enough business buy-in: This one may sound a little familiar, but it often sounded like there was no attempt to build a Data Community or grow the idea of Citizenship

There were a lot of other reasons why these projects failed, but in the end, it all came down to the same reason. Data was treated as an afterthought every single time. The emphasis on having a solid strategy, an educated executive, the right team and tools was not a priority and for many companies, they ended up paying it back in lost time and productivity. Going back to my earlier conundrum, I ended paying in time because I had forgotten what some of the values should have been as they were not in my mind anymore. While my problem was quite simplistic compared to the real world, these issues can cause companies serious costs when data is not considered properly.

This is why my professional rule is to never treat data as an afterthought. Over the years, I have been involved in projects in and outside of my work life and in the initial conversations, it is amazing to see how quickly data is overlooked. When brought up, it becomes one of those things that is dismissed as “we’ll get to that later” or “not the focus right now” only to end up in a series of crisis meetings and lose on the most precious commodity – time. In my career, I have worked out a ratio of 1:3. For every one hour spent in pre-planning, three hours of crisis or emergency remediation work is avoided. When getting people to understand the importance of why we need to think about data upfront, I use this ratio to sell the value of getting this done right at the start.

Some people will even ask me “why bring it up?”. Data can be something of a beautiful beast – majestic when it is accurate and providing you with the insight you need to grow, but it can be ugly and painful when ignored. Similar to Beauty And The Beast, data can often incorrectly viewed as a beast and as something that is too complex to understand. Over the years, I have learnt that people that ask that question view data purely as a beast, becoming overwhelmed by the complexity and not wanting to talk about it. The irony is that it ends up turning into the beast they were trying to avoid. To get around this problem, I sell the beauty of data alongside the time and resource savings that I mentioned earlier. It is easier to sell beauty as this is what drives value in your organisation and gets your team to treat data as an asset.

If you have gotten this far and you have wondered about the relevance of the picture above, think about this. Would you jump off a cliff without thinking about it prior? It is great to say “oh, I should have had a parachute” once you are descending at 100km/hr, but you are already heading for a crisis and failure. The lesson that I’m taking away from today’s post is to never treat data as an afterthought. This does not need to be hard or take a lot of effort. The next time you sit in a meeting and no one is bringing up the data requirements, stand up like the Data Citizen you are and bring it to everyone’s attention.

Meanwhile, I’m going to clean up the rest of my metadata.

Everyone Needs A Voice

In my last post, I talked about Data Citizenship and why you and I should be making this a goal for 2020. You may have gotten to the end of my post and thought that you could cross this off your list. Rightly, you may have recognised that your organisation is full of excellent Data Citizens. But, are they all speaking equally? Are some of your citizens out in the spotlight and others are in the dark? Do you or any of your citizens act as the office lone wolf when it comes to the way data is handled? If you said maybe or yes to any of those points, it is more likely that you are running a Data Dictatorship than a successful Data Community.

Like all other things in the workplace, there is no I in “team”. I can easily think of numerous projects of a professional and a social nature that collapsed because of one person who wouldn’t let go of the microphone. Back in 2006, I started a project called PHLAB which was a WordPress plugin that allowed templates to be built in Flash. I had a few other people helping me who in reflection had a much stronger vision and structure for the project. In the end, I decided my structure was right and the only way to proceed. The project failed in the end. Years later, I heard about the term “Benevolent dictator for life” and later realised that in acting this way, I destroyed the project through not taking a communal approach.

As I have gotten older and a little bit wiser in my present field, I have realised that dictators can be present in the data industry. For clarity, I’m not talking about those who are passionate- we need more of those people. These are the people who within their specific business or subject matter area who believe that their approach and understanding of the data that matters to them is the only way forward. These type of people are dangerous because the needs and requirements of those out outside of their subject matter area can be ignored. From experience, these people are even more dangerous when they have been given a poor data experience in the past as their passion and enthusiasm for better data will make them even more oblivious to the rest of the Data Community.

To establish a well-working Data Community, we first have to recognise that although Data Dictators exist, they are not wrong. As I mentioned in my previous post, everyone wants good quality data. And just like I mentioned in my previous paragraph, it is generally the data environment that they have been exposed to which creates these dictators. In the last couple of years, I have found that educating people on the importance of the Data Community has helped to turn potentially destructive Data Dictators into the most engaged and productive members of the Data Community. For me in this situation, I end up with the best of both worlds. I get some of the strongest ideas for the Data Community to build up a complete strategy and I end up with supporters and endorsers for the community as well.

Removing the presence or feeling of Data Dictators will then help to grow the confidence of those around them that are not currently bringing anything to the community. We know that all workplaces are filled with Extroverts and Introverts, all with equally good ideas. I have found that providing them with the same education as the dictators, but also educating them on the power of doing nothing is the winning ticket. The danger with Introverts is that if they don’t feel that they can contribute to the community, they will also internalise their hatred for the data they have to work with. Potentially in this situation, you could also lose your best people.

When it comes to bringing your Dictators and your Introverts together, I educate them with one simple message- we are all Data Citizens and we are all members of the Data Community. I know I’m repeating myself when it comes to this point, but I feel it is a point that needs to be made continuously so that it sticks in your head. It is a simple message that communicates to all that you got to be mindful of those around you and that if you don’t speak out about what you need, you will never get it. This is what I love about data, it is the sense of a community coming together to build something great. For that community to work, everyone needs to have a voice.