There is a famous saying in the data world which is “garbage in, garbage out” but how do you know what isn’t garbage? This final article in our three-part series on building a healthy data culture provides three steps to ensure your organisation is measuring what matters.
The first step in gathering meaningful data is determining what is important to your organisation. What are your organisation’s goals? What needs to be done to reach these goals? What things can you impact to reach these goals? The answers to these questions relate to the three categories of meaningful data – indicators, metrics, and dimensions.
Indicators reveal if an organisation has met their goals. In other words, indicators have a target determined by your organisation’s strategy and will change as your strategy changes. Indicators reflect key aspects of your organisation’s performance, such as financial goals, customer satisfaction, employee wellbeing or operational efficiency. They should be kept to a minimum, ideally under eight so they are easily remembered and achievable.
Metrics track progress in reaching these indicators. Everyone working for an organisation should have a metric which they are responsible for and can influence. Empowering metrics enable people to understand how their work fits into an organisation’s strategy and the importance of their role.
Dimensions categorise indicators and metrics providing context. Dimensions should enable action. For example, consider a financial indicator such as profitability. The metrics driving profitability will relate to costs and sales. When considering how you impact sales, you need to know what is being sold, where is it being sold, and who is buying the product. These are dimensions which can be acted upon, i.e., increasing production of popular products, increasing distribution to types of outlets which are being more successful, or creating targeted marketing campaigns against a high potential customer group.
Documenting how your metrics and indicators relate to one another, who is responsible for each metric, and how dimensions will be used to drive action ensures you are aiming to collect meaningful data.
Once you know what data is valuable to your organisation, you can start to think about how to source it. Most meaningful data can be found within the software, sensors and surveys used within your organisation:
Beyond the obvious, data vendors like Equifax and Experian sell data. For instance, customer information (i.e., their social-economic status, age, gender, etc.) can be purchased to assist targeted marketing. Likewise, open data sources provide free access to data collected elsewhere. Doing a quick online search for “open data APIs” and your area of interest will show if meaningful data for your organisation has been shared. The programmable web has collated a list of open data APIs. Likewise, the UK Government has shared a catalogue of their public sector APIs, some of which you can utilise free of charge providing you meet their licensing and access requirements.
So how do you know if the data you’ve gathered is good enough? The data must be of a high enough quality to be acted upon, but it does not have to be perfect. Unhealthy data cultures can form aiming for perfect data. Either they are stuck trying to collect this data, unwilling to act on anything else; or are spending more money creating perfect data than the insights from this data can generate. Consider the cost, effort and time required to gather data and balance this against its value.
According to the Data Management Association (DAMA), data quality is defined by its completeness, uniqueness, consistency, timeliness, validity, and accuracy. We can make do with incomplete data, remove duplication and enforce rules to ensure data is consistent and valid. However, in addition to accuracy and timeliness it must be relevant, unbiased, and legal.
We hope these tips help you gather meaningful data to propel your organisation towards its goals. If you have more tips or would like to share some more links to open data sources, please comment below. And if you’d like our help building a healthy data culture in your organisation, get in touch today.
