What data does your organisation really need?
When was the last time you sat down and questioned what data your organisation is collecting and why? Here we look at reasons to review what data you are collecting, how you collect it and how you might go about updating your approach.
Why review your data collection?
Whether intentional or not, your business is collecting and generating a lot of data. If there isn’t a centralised data capability within the organisation, then it is unlikely there is an awareness of what data is available. Even with a centralised data capability and good governance practices like data catalogues, often there is a dual problem of data being collected that isn’t included in the central view and legacy data being collected that is no longer used. Regular reviews of what is being collected and why are useful for the following reasons:
If there isn’t a good awareness of what data is being collected then the business won’t be able to use it. It’s a very frequent scenario for us to be engaged by a business team to collect some data that it turns out, they already had elsewhere in the business! Data is only useful when it is known about and leveraged to help improve experiences, make decisions and automate processes.
Are you sure that what is being collected is relevant to your business needs? Is anyone looking at what suburb customers are visiting your website from? Are the 3 different identifiers for each product sent by the manufacturer necessary to store if you only use one? Making sure the data being collected is relevant to business operations and the level of insight means that there is less noise for people to cut through when they need to find information. There is a theory of ‘collect everything and we will find out how to use it’ but if it hasn’t been used within a reasonable time, why continue to collect it?
Maintaining a data store, flows and the processing of data to keep it up to date, compliant and accurate requires time and money. The more data you store, the more maintenance overhead and costs are incurred. By ensuring that the data being collected, processed and stored is still relevant and being used, there is comfort that the investment in the data capability is well spent.
Data requires space to store. That space, even if rented on a server is taking up physical space and resources somewhere in a data center. The less data you need to process and store, the more environmentally friendly you can be.
What should be considered when reviewing data collection practices?
Now we know why we should review our data collection practices, and what should we be considering when reviewing them:
Having a data strategy that is clearly stated and considered as part of a review is important. A data strategy sets out what is being collected and why. It’s important to consider if the strategy is still aligned with the business’s goals. A good exercise is to take the executive strategy and map out how the data strategy supports each objective. .
The next area of consideration is the accessibility of the data – how easy is it for business teams to find what data is available and surface it into reports, products and experiences where it is needed most? If the data is sitting in software and just backed up to a centralised repository for reporting, can the business teams use it from within the software? If not, how can it be exposed?
Alongside considering what data is being collected, how that data is being collected should be considered. If there is an uncovering of new data being collected, then the assumption is that explicit consent isn’t being asked to collect that data. Marrying up the consent tooling, data privacy policies and actual collected data should always be a part of this process.
Data doesn’t need to live forever. When considering what is being collected and how it is used, working out how long the data is useful for and setting appropriate retention policies is an important exercise. Especially when considering the future costs of the data store as it grows. At some point the data will give diminishing returns in value vs cost of storage and that calculation should be part of the cost of ownership.
Lastly, asking about the security of the data is important. Most organisations consider how secure their data stores are and monitor access and requests to that data store, which is critically important, but what about access to that data? If the data is being collected by a third party and the business relies on that data as key strategic information – what happens if the third party changes its collection method, or the collection method becomes redundant? How will the business continue to get access to that information?
How to do a data review?
Data feeds three parts of our organisation: insight, decision making and automation.
To review what data is needed for insight there needs to be two questions asked: what do we currently know and what do we need to know in the future? The former part of that question is answered by looking at reports that are currently generated (automatically and manually) and working out what data is needed for these reports. Remember to be just as critical about the purpose of the report as the data point. The latter is to go back to the business objectives and understand what success would look like and how this will be measured.
Decision-making often gets lumped in with insight but they can be quite separate – while insight is usually to help measure trends and change and contribute to decision-making, decision-making points are often more action orientated ‘If this does X, then do Y’. It can be something as simple as sending an order to the warehouse for packing with the delivery date on it (so they can decide what order to pack in). It can also be about helping customers make decisions – such as presenting product recommendations or letting them know the current average call time when they call in so they can decide whether to wait or not. The best way to understand what data is necessary for decision-making is firstly to have clear processes mapped for the business to see where decision points are being made. The second is to do the same for any customer experiences and map where the customer needs information to move on to the next stage of their journey.
Automation is taking decision-making a step further and informing another machine to take action based on the state of the data. This is built upon the work done for decision-making. One of the best ways to work out how data can be used for automation is to see where the current process requires a person to move patterned information from point A to point B to continue with the process. This can help understand where data might be best used or better collected to drive efficiencies.
- Regularly review your data collection habits for improved relevancy, usability, efficiency and ecological purposes
- Review the data collection in the context of the wider business strategy, ensuring it is accessible, collected in a transparent way, retained for the right period of time and secure.
- Ensure that data is reviewed in the context of what drives insight, decision making and automation to improve collection
Need help reviewing your data collection habits? Our data team is available for a conversation