Following on from my previous article focusing on how the data industry needs a data revolution, as part of truly making the data industry great, I would like to propose a series of changes to how the data industry operates, which should be incapsulated in a professional body and associated methodology.
At the outset, I will be very clear; this is a challenging proposition, and one that not all corporates will commit to. To begin, in this article – the second of a three-part series − I am going to focus on the business aspect first.
There are many professional bodies in existence that specialise in data management, data warehousing and related methodologies. The importance of close collaboration with business and aligning with business objectives are certainly highlighted in these professional bodies.
The concern that I have, however, is that the business stakeholders are often only included as part of the broader community, and not as direct stakeholders.
This is where I believe the challenges start. Data professionals enter the corporate environment wanting to deliver according to their methodology. However, in many cases business is often not aligned with this and doesn’t understand the importance of adherence to the methodology. Neither strategically, nor in their day-to-day, business as usual world.
Conversely, full academic adherence to the methodologies often don’t speak to the inherent needs, time frames and costs of the business stakeholders, which causes frustration on their part. Of course, agile methodologies can assist with this. However, simply inserting an agile delivery team into an otherwise broader, non-agile working environment, also does not lead to success.
I believe we need to start with a professional body that both business and data professionals can join and contribute to.
To address this, I believe we need to start with a professional body that both business and data professionals can join and contribute to. This must make provision for the business layer. It must define a clear framework on how, from a business standpoint, to implement a data-driven organisation.
So often, business and data professionals wax lyrical on how they will become a data-driven organisation, but these initiatives mostly fail. Most commonly, due to an improper understanding of what this means, lack of business buy-in and support, lack of funding and a lack of vision for how to transform the business to enable this.
To solve these problems, we need a set of best practices that guides business stakeholders on a strategy and implementation roadmap for how to effectively, and practically, put data at the centre of their organisation.
It must deal with the practicalities of what it means to be a data-driven organisation. It must describe and educate the business on the meaning of a data-first mindset, data-driven decision-making and data democratisation. It must highlight what this implies to how a business must operate.
Furthermore, it must stress the importance of closer collaboration with IT and how to achieve this. It must teach not just the importance of data governance, but how to implement this as an integrated component within all business operations. It must emphasise the importance of flexibility and agility, both to the business operations, and how this must carry over into IT and data.
It should be clear by now, that besides the heavy focus on guidelines on how to transform the business, there will also need to be a heavy reliance on education of the business community.
One of the challenges to getting true business buy-in and support is a lack of understanding of what data professionals do. More importantly, a lack of understanding of how important it is to do it right. Too often, due to time and cost constraints, there is a downward pressure to do the most with the least.
This is when junior or inexperienced teams cut corners, and this becomes a death by a thousand cuts scenario, resulting in a formerly well-designed system becoming inoperable.
To address this, a strong focus is needed on significantly improving data literacy in business. We need to implement data literacy programmes, where we can teach the importance of data management, data governance, data warehousing, business intelligence and data science to the business.
Not just what it is, but how we effectively do it. We need to teach the theory, but also the pitfalls, the consequences of doing it wrong. More than that, we must also show them the benefits of doing it right the first time.
Data literacy training should be aimed at the traditional feeders of business resources, people studying qualifications such as marketing, business administration, finance, etc.
We need to incorporate this as early in the education of these stakeholders as possible, and across as many institutions as possible. In addition, we need to target people who rise through the ranks.
The corporates that commit to this should commit to ensuring anyone that assumes a management or SME-level position should attend this training, so they can understand the importance of the principles we want to propose in the profession.
In this way, we can make the key business stakeholders a part of the professional body, that can in turn contribute to the professional body and its methodologies. We also want to ensure it is business stakeholders that drive the formulation of the business framework component of the methodology. This will ensure the framework is relevant, speaks the business language and stays true to the key business drivers.
If we can define a common business framework for delivering data initiatives, that takes the business requirements and challenges into account, all while ensuring business understands the importance of the key data management principles, then we have taken our first, positive step towards improving the data industry.
Do keep a look out for the last article in this series, where I will share my final thoughts on this topic.
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