What are data metrics?

There is a wealth of data available for any organisation, but what is it that matters and how do you put it to correct use?

In 1954, famed management consultant Peter Drucker said, ‘What gets measured gets managed.’ The thing is, in today’s world, everything gets measured. In fact, organisations are drowning in data. It has now become more pertinent to curate which of the measured materials get managed.

A data-driven business culture is one where decision making is undertaken and communicated by using the information or data the business captures. Employees in such organisations can be shown why they are doing what they are doing, backed-up with evidence. When communicated properly, data brings credibility to management strategy; metrics are the particular parameters of data that a business chooses to measure its performance using. Good metrics are easy to source, free or cheap to collect, and consistent.

Examples of these metrics include; customer lifetime value, customer satisfaction, or adoption rate. Examining these metrics across a business’s lifespan can show who your customer is, when they seek out your services or when they abandon them. However, having these metrics is not enough on its own. Understanding the relationship between two metrics’ data-points can cover where they can be applied, to the strategy that can be built from them. 

Metrics vs KPIs

KPIs or Key Performance Indicators are sometimes used interchangeably with metrics, however despite all KPIs being metrics, the same cannot be said the other way around. KPIs are the most important measurable information that is going to affect your business. A great strategic plan will identify 5-7 KPIs to monitor across a project. Metrics are your ‘business as usual’ measures that still add value to your organization but aren’t the critical measure you need to achieve.”

Organizations can’t control their data, but they do control what they care about.”

 Jeff Bladt is Director of Data Products & Analytics at DoSomething.org, Harvard Business Review

Data, metrics and analytics are all different elements that work together – an organisation can’t build their metrics and KPIs without capturing data – and without then identifying the ‘business as usual’ metrics and strategic KPIs, organisations cannot establish trends and analyse business patterns.

Data vs metrics

Data is the hard 0s and 1s gathered which are then identified for a specific metric. Before deciding which data is important to track, it is important to consider three things:

  1. Is the data agnostic?

What this means is whether the data holds any specific bias that could unfairly advantage or disadvantage end users.

  1. How is the data captured?

The necessary data needs to be collected consistently otherwise it will be hard to establish accurate insights.

  1. How is the data stored?

In the UK all data needs to be stored safely and in line with GDPR to ensure the security of the company and customers. 

Analytics vs metrics

Analytics are the decision-making actions that a company takes off the back of analysing its metrics.

“I just want to point out the fact that if you don’t have data and metrics locked down, analytics are a moot point. You don’t just leap all the way to analytics. It’s a hop (data), skip (metrics) and a jump (analytics) to truly better understanding. Every step in the understanding process is as crucial as every other.”

Data, Metrics, Analytics: The Hierarchy of Knowledge – SmashFly Blog

Quantitative vs. Qualitative Metrics

Tracking your numbers is the basis of being a data-driven organisation, however it’s important sometimes to engage the human touch, to reach out to key stakeholders and gain insights beyond the numbers.

To use data metrics as part of business strategy, different team members need to be faced with what is important for them to manage. For front-line staff it’s unlikely that complex loads of financial data and revenue are going to resonate with them. Giving data points which measure an action against its impact on real humans and the community will often be easier to digest for most people. That’s not to say that these metrics do not feed in positively to the revenue stream up the chain; if the metric is not good for the health of the organisation there is little point in measuring it.

There is not just a business case for harnessing data; by establishing continuous metrics in relationship with one another, the progress or decline of vulnerable people can be tracked. In America the Federal Department of Housing and Urban Development (HUD) conduct an annual large-scale attempt to quantify homelessness in the US. The “Point-in-time” homeless count enables federal and state government, charities and organisations to target their outreach. Astonishingly, in 2017 they found that 23% of all homelessness in the US was concentrated in New York City and Los Angeles. By collating separate data points “one of the most important outcomes of building a CES for homelessness is the ability to prioritize clients based on their vulnerability.”

“A good metric is comparative. Being able to compare a metric to other time periods, group of users, or competitors helps you understand which way things are moving. “Increase conversion from last week” is better than “2% conversion”. A good metric is understandable. If people can’t remember it and discuss it, it’s much harder to turn a change in the data into a change in the culture.”

Towards Data Science

Being presented with a good metric changes organisational strategy and stakeholder behaviours. For example, The Health Foundation found that “investing in housing support for vulnerable people helps keep them healthy. Every £1 invested delivers nearly £2 of benefit through costs avoided to public services including care, health and crime costs.” A business given this metric can justify social care and purpose-driven strategy as a route to revenue and return.

“Businesses have transformed their operational models to building continuous relationships with customers. Priorities have shifted from getting new clients to keeping existing customers satisfied and growing “share of wallet” – a way of measuring how much a customer will spend in a business category and the percentage of that spend that a business is capturing.”

The 3 most important data metrics for retaining customers, Information management