Blog - 25 Nov 2021
3 minute read
Business Intelligence
Data Driven Decision Making
Data Strategy


Ascent blog: Jon Stafford, Principal Data Consultant at Ascent explores what makes data meaningful, and how businesses can ensure they don’t fall into the trap of ‘all data is good data’.

data, informed business, business intelligence, data culture, data analytics




Is your organisation truly informed, or does it just think it is?

Not all data is created equal. Jon Stafford, Principal Data Consultant at Ascent, challenges business to constrain their consumption to only ‘meaningful’ data - and realise massive efficiency gains.


Business Intelligence


Are we informed or overloaded?

Nowadays, data and information are easy to come by. On a personal level, anything we want to know is available instantly, thanks to smartphones and ubiquitous internet connectivity. We don’t even need to go looking for information – it’s pushed out to us constantly by social media companies and other organisations (provided we give up our data in return, of course). At work, we’re increasingly likely to have access to a sprawling array of reports, analyses and dashboards.

It wasn’t always like this. It’s easy to forget that until relatively recently, access to information involved time, cost and effort. You had to find someone who knew what you needed to know. You had to buy or borrow a book. You had to put together a business case to offset the cost of developing a new report against the value you would get from it.

Thanks to increasingly capable and less costly technology, the pendulum has swung the other way – but has it gone too far? It’s relatively easy now for organisations to provide people with self-serve data and tools allowing them to create as many reports and dashboards as they desire. However, this often has an undesirable side effect: lowering the time and cost of producing data in this way is often offset by an increase in the time and cost of consuming that data. People receive more and more information that may (or may not) be relevant to them, and so spend more and more time consuming it. This causes a problem if it diverts time and energy away from achieving what they need to. It also becomes more difficult for people to work out which of a dozen reports and dashboards they should focus their attention on.

Just tell me what I need to know!

Organisations need to strike the right balance here, and only produce the information that people actually need to consume. Practically, they can achieve this by applying the following three tests to any new data or information they are considering adding to their data estate:

  • Does it pass the ‘so-what?’ test? Does it help someone achieve their goals and objectives? Is it required for legal or regulatory reasons, or is it needed to respond to a competitor’s activity?

  • Will there be a process to use the data/information, and will someone have the responsibility of making sure this process is followed?

  • Will the insight that the data provides be used to inform a decision, and will this decision result in someone taking the necessary action to enable a positive result or change?

As an illustrative example, consider the following two items of weather forecast data: likelihood of rain and atmospheric pressure. For me, the first passes all three tests, the second does not:

  • The forecast of likelihood of rain passes the ‘so what?’ test – it helps me achieve my goal of not getting wet when I go out. There is a process to use the data – I check the weather forecast before I go outside – and (trivially) the responsibility to do this lies with me. The insight I get from the forecast results in a decision – if it’s likely to rain I decide to carry an umbrella – followed by an action with a positive result – I take an umbrella with me, and as a result I don’t get wet.

  • In contrast, the forecast of atmospheric pressure as, say, 1019 mb, does not pass the ‘so what?’ test. Knowing this does not help me achieve any of my goals and objectives, because I don’t know what effect a particular reading of pressure in mb has on the weather.

Becoming an Informed organisation.

The above example is, of course, a simple one, but it’s useful to keep it in mind when considering data more relevant to an organisation’s performance. Becoming an informed organisation means making sure that everyone in the organisation has the data and information they need to be able to achieve their objectives, helping the organisation as a whole, realise its goals. Every piece of data needs to have some tangible value and a positive return on investment – the cost to consume it needs to outweigh the cost to produce it. Applying the above three tests provides an organisation with a practical means of consistently achieving this.

The tests also have another major benefit. They ensure that the data and information an organisation decides to use are always driven by business objectives, rather than by answering questions like ‘We have lots of data, what can it tell us?’, or ‘Let’s do some AI!’. This, in turn, ensures that every piece of data and information earns its keep, and no time, cost or effort is wasted on needless information production or consumption. The result? An organisation that is truly informed, instead of labouring under the illusion that it is.

Jon Stafford

Principal Data Consultant


Jon helps businesses drive more value from their data by ensuring they use the right information, in the right way, for the right reasons.

With over 16 years' experience in data strategy and business intelligence, Jon has worked with organisations of all sizes to better align their data approach and capabilities with business goals and objectives.

Jon believes that data and technology should always makes peoples' lives easier, and that this philosophy should be at the heart of every organisation’s data vision.


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