Data democratisation and Domo

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Although it has never been the most talked-about topic, the concept of democratisation has been a consistent theme in data for some time. The concept, at its core, is simple: data is valuable, but that value is only realised by a relative handful of people in most organisations. This, the argument runs, severely limits the amount of value that can be extracted from that data. Hence, if you could leverage your data across a larger portion of your userbase – if it was democratised – you would see significantly greater returns and generate even greater value from it.

None of this is particularly controversial; indeed, it is obvious to me that most, if not all, organisations do not fully utilise their data, and the isolation of data to only a small number of experts is entirely plausible as a contributing factor. The key question is – how do you achieve the aforementioned democratisation? The first step, I think, is to understand why data is ending up exclusively in the hands of a few experts. It seems to me that there are three possible explanations here, all of which are going to be present in varying amounts in the vast majority of businesses.

First, there is the possibility that some of your users simply don’t have a good use for your data – sometimes there is simply no relevant value to extract. There is of course nothing you can do about this, but then there is also nothing to be done about it. However, it is worth being aware of as a potential factor when assessing why data is being used exclusively by one group: sometimes it’s because it’s not relevant to anyone else.

Second, there is lack of access – if some of your users do not have a way to leverage your data, of course they won’t get any value out of it! More commonly, if there is access in the literal sense, but it is too difficult to do, takes too long, or is otherwise too user-unfriendly to actually get used by anyone without a technical role, the results are much the same. This is the area that many democratisation-centric products play in, as it is the only issue that can really be addressed directly by a vendor product.

Third, and to my mind this is by far the trickiest of the three, there is your organisation’s culture concerning data. You can lead a horse to water, but you can’t make it drink – likewise, it doesn’t matter how much data you provide to someone, if they do not have any desire or reason to leverage that data, they most probably will not. Many users are used to thinking of data as something highly technical and complex, something difficult to get a hold of and do anything with: a chore, basically. If you want to actually democratise data in your organisation, you need to actively work to show your users how easily it can be accessed and how it can make their own work-lives easier (and of course there must be truth to this). You must make data both non-threatening and obviously beneficial, creating fertile ground for a data-friendly culture to take hold. This means that as a bare minimum you need to make data access fast and easy for users of any technical ability (addressing the point above) before you can start meaningfully addressing your data culture.

And now that we understand what we need to do, we can start thinking about how to do it. For instance, vendor products in this area often provide dashboards, BI tooling, and so on. That’s all well and good, but a vendor I talked to recently put it better. Domo, the vendor in question, bills itself as crafting (and allowing you to craft) unified, centralised, tailored data experiences designed to make data accessible for everyone. There are various features on offer here – various integrations, an app store for user experiences with a monetisation path, low-code experience development, support for AI services, and so on – but I think Domo’s core insight is that it is not enough to make data access easy: you also have to make it look and feel like something your users are comfortable interacting with. In particular, this means creating a universal interface for data that persists throughout the vast majority of your organisation in terms of both how it looks and how it functions (which is something Domo very much accomplishes, in part by bringing data from disparate systems and even random excel files under its platform umbrella). It seems to me that this consistency will be incredibly useful for bringing non-technical users onboard and creating a culture of widespread data usage – and from there, democratisation.