Data strategy ain’t easy
As a data expert, I find it an intriguing observation to see how well-formed our opinions are about data. While, in fact, our knowledge about the topic is rather limited. This discrepancy means we are missing out on opportunities to improve, to delight, to understand or to empower. It means we are leaving money on the table.
A good article starts by shattering a reader’s assumption or belief.
So, here’s my swing for it: you think you know what “data” is about, while in fact, you don’t.
Let me illustrate that point by asking you a few simple questions:
How is a logistic regression different from a linear regression?
How exactly is big data different from small data? (please don’t tell me it’s the size)
What’s the difference between a data scientist and a data engineer?
How would you measure data quality?
When do data become privacy sensitive?
To me, a data expert, it’s an intriguing observation how well-formed our opinions are about data, while our knowledge about the topic is limited. I mean, do we really believe we can assess the value of data for our companies, governments, society or even our personal lives when we:
lack the basic methodological knowledge (question 1)
can’t detect the paradigm shifts behind the hypes (question 2),
don’t know the different professional roles (question 3),
cannot assess the usefulness of our resources (question 4)
are unsure about the ethical and legal side of things (question 5)?
An intriguing observation, like I said, but there’s a silver lining to it. The inspiring part is that mediatisation, self learning and rapid information exchange all have led to us being very aware of the potential of data. Even without a deep knowledge of the techniques and technologies that support this potential. Chances are that you, without being able to answer any of the above questions, do have a good sense how machine learning can improve your business or even life.
Business leaders have a good view on the potential but struggle in assessing the capabilities of their organizations when it comes to data.
In business we are equally observing this duality, most notably when discussing data strategies with c-level executives. This should not come as a surprise. After all, strategy in its essence is about understanding the potential (of what could be possible) and assessing the reality (of what we can and cannot yet do today). Business leaders have a good view on the potential but struggle in assessing the capabilities of their organizations when it comes to data. As a consequence, formulating good data strategies becomes rather difficult.
Is this a bad thing? Not necessarily. I’d rather live in a world where thought and business leaders can envision the potential of data (technologies) than in a world where they cannot.
The fact that there is a huge discrepancy between knowing what to use data for and not knowing how exactly to do so is cumbersome. It means we are missing out on opportunities to improve, to delight, to understand or to empower.
Still the fact that there is a huge discrepancy between knowing what to use data for and not knowing how exactly to do so is cumbersome. It means we are missing out on opportunities to improve, to delight, to understand or to empower. It means we are leaving money on the table.
This is exactly why we have recently founded Craftzing Data, our expertise center on data. You see, as delighted as we have been to hear our clients (and the general market) express their aspirations for data, we couldn’t but realize that we, and perhaps the whole of Belgium, need an expertise center on data. A place that gets in touch with the data reality and helps us define our data strategies. A place where the technical possibilities and limitations are being experienced daily by data engineers and data architects, where data scientists actively explore methodological developments, where data visualisers innovate in congruence with clients, where data protection officers follow up on legislation and offer pragmatic advice, where data analysts thinker about business requirements and solutions, where data strategists put the pieces of the puzzle together and where product owners ensure that puzzle will come to life.
We are actively building this place. To support our clients in a similar way as we have supported them through their digital transformations. By combining clear strategic guidance with top-level execution.
Now we are using these experiences to face this imminent wave of data challenges or, better, opportunities. We are actively developing a wide offering of data services from data protection officers to creative data visualizations, from advanced data analytics to masterclasses. To be fairly blunt, it’s extremely exciting to see all these expertises coming together.
No matter your situation, next time you ponder about your projects, read an article on AI or witness your competitors declare a big data victory, why don’t you ask yourself the questions: “What would my data strategy be?”
What’s even more exciting is that we know you are keen on building expertise in this area too. Perhaps you are about to start a small data use case such as financial reporting or a data stewardship program. Or maybe you are already investing heavily in business needs such as point-of-sale data, IoT integrations, or advanced data analytics. No matter your situation, next time you ponder about your projects, read an article on AI or witness your competitors declare a big data victory, why don’t you ask yourself the questions: “What would my data strategy be?” What knowledge am I lacking to clearly see the next steps I should take? If ever you find yourself in need of a partner: give us a shout. We’re here, working towards the same direction as you.
By Dr. Maarten Vanhoof
I’m a spatial (big) data expert with a strong motivation to use data for the common good.
I strive to make an impact via my organisation Craftzing Data, academic work, education, and advisory services.