What Are The Pros And Cons Of Data Democratisation?
Data democratisation is the process of taking the overall control of data out of the hands of the few who have previously acted as its ‘gatekeepers’, and making it accessible to a much wider group (or groups) of people across an organisation.
One of the reasons why democratisation is beneficial is because it allows the recipients and users of the data to derive insights from it and make informed decisions that will ultimately help the business.
But what are the other advantages of taking this approach to managing your organisation’s data? And are there any drawbacks to such an approach?
We’ll take a look at the major pros and cons of data democratisation below, as well as the steps involved in instilling a democratisation mindset within your organisation.
What are the advantages of data democratisation?
The main reason why you may want to democratise your data and processes in the first place is to increase your ability to use that information to generate ‘actionable’ (excuse the jargon) insights that can ultimately help your department, and the organisation as a whole, to achieve its goals.
By democratising your data, you’re empowering your colleagues by making it easier for them to use data in their decision making, the idea being that they will be able to make better, more informed decisions as a result.
It also gives people more accountability and ownership over the decisions they reach, which should in turn make them more invested in the final outcome.
Additionally, by giving people the chance to use data in an independent and self-driven manner, you’re giving employees the chance to discover new business opportunities while also creating a more agile and flexible working environment.
By democratising data, you are empowering and encouraging members of your organisation to use data more, giving them the chance to experiment and potentially achieve great results that could otherwise have been missed.
What are the drawbacks of data democratisation?
Unfortunately, as liberating as data democratisation is, there are inherent downsides to this approach. When you open up data and make it accessible to a much wider group of people, you are increasing the likelihood that some of those people who are less data-savvy or experienced working with large amounts of information are going to misinterpret it, and make bad decisions as a result.
There’s also the risk that the democratisation of information can lead to the creation of data silos. This is despite the fact that the very act of democratisation is largely carried out to prevent data from being continually siloed within the IT department, and to do away with gatekeepers. However, simply removing it from one silo does not erase the possibility of it being siloed elsewhere if the proper processes aren’t put in place to prevent that from happening.
In fact, pretty much all of the drawbacks of data democratisation are along the same lines – they stem from the fact that simply opening up the data to more users does not suddenly turn them all into data experts, and that errors can occur without governance measures and policies in place.
For example, there’s an increased risk of creating duplicate data, as well as misusing it and exposing your organisation to legal concerns regarding regulations and privacy laws.
How do you democratise data effectively?
Effective data democratisation is not just a case of giving access to all of the information you have to everyone and expecting them to turn it into gold. You need to take a structured approach to the process of democratisation, and it should include the following steps:
- Focus on data that is relevant
- Put data governance measures in place
- Don’t be afraid to use the right tools
- Increase data literacy
- Use the data to make decisions
Focus on data that is relevant to your organisation
The first step towards democratising your data is to work out what kind of information is actually relevant to your business. As such, when you’re presented with a big pile of information, you need to separate the data you want or need from all of the other noise.
Apply data governance rules to the information
Again, data democratisation does not mean giving everything to everyone. Different roles and varying levels of seniority will determine who should be given access to what information, depending on relevance and confidentiality.
Data governance – and a data governance framework – includes the overall management of the availability, usability and security of your organisation’s data assets.
For a governance framework to be truly effective, it’s a good idea to create a dedicated data governance body to oversee it. This body will then be able to focus on defining policies, rules and plans that make it clear who should have access to what data. To read more about how to create a data governance framework, check out this blog.
Give people access to the right visualisation tools
People will have varying amounts of experience and confidence when it comes to working with data. Not everyone is a data scientist. Even for those people in your organisation who are more comfortable working with large amounts of raw or complex data, simply giving them a spreadsheet with thousands or tens of thousands of bits of information to examine is unlikely to be an efficient process, especially when there are ways to get the same results but much more quickly.
This is why it’s a good idea to give your colleagues the tools required to take the information and turn it into visualised results that are easier to understand. Another benefit of giving people access to tools is that, especially from this point on, a lot of software is going to incorporate aspects of AI – such as machine learning – to reduce the burden of manual, time-consuming tasks and to allow increased automation.
One thing can be said with certainty – the amount of data swimming around is only going to increase, and as it does, the need for tools will as well.
Improve your organisation’s data literacy
Once you’ve democratised the data, established a governance framework and applied tools in order to simplify the information, you then need people who can make sense of those results – in other words, people who are ‘data literate’. As part of this, you need to make sure that you are offering regular training to people within your organisation, especially as and when you implement new tools.
As information becomes more accessible – which, after all, is the aim of data democratisation – the number of roles that have key requirements that involve data in some way (and require good data literacy) will only increase.
Make decisions that are influenced by the data
The whole point of this process is not just to democratise data for data’s sake, as a ‘soft’ exercise. It is to use the data effectively to make critical business decisions that are backed up by analysis and evidence.
For example, when it comes to taking measures that are designed to improve efficiency, reduce costs, improve supplier relationships and so on, these are more achievable and justifiable when backed up by solid data and clear results.
Here at HICX we support many leading global organisations in improving and transforming their supplier management and procurement processes by utilising the power of great supplier data.
You can see plenty of example case studies of projects we’ve worked on with market-leading organisations here.