How NumberWorks and NumberCloud can help you track your growth

Chris Conway
Chief Architect, Quantiv

If there’s been a theme to a few of my recent blog articles, it’s ‘anniversaries’. So, continuing that thread, it won’t have escaped your notice it’s now about five years since the start of the Covid-19 pandemic.

‘Build Back Better’ was one of the slogans coined by the UK Government during that period. If that phrase meant anything beyond an alliterative soundbite, it was probably intended to conjure up an idea of learning the lessons of the pandemic and recovering as a nation.

And now that ‘better’ phrase is resonating again as our new Government looks to tackle the lack of economic growth.

Cheaper or bigger?

It’s a gross generalisation, but economic developments come in two broad flavours:

Cheaper: providing existing services and products for a lower cost
Bigger: providing new services and products for the same or higher cost

The ‘cheaper’ route allows the services and products that already exist to be accessed more easily. This is admirable because it’s more inclusive, but while it might lead to more consumption, it doesn’t really increase the sum of what’s available. In short, growth here is in activities. In other words, the same sized pie divided differently or more often.

In contrast, the ‘bigger’ route finds different uses for resources or even new ones. Initially, these uses are often expensive to produce and deliver, so may not be all that accessible. Yet, while this restricted accessibility may imply limited initial consumption, the value of what’s available increases. In short, growth here is in the assets. So, a bigger pie, albeit with some getting bigger pieces.

The importance of putting data into context

Both the ‘cheaper’ and ‘bigger’ options have their benefits. And if we leave aside the ambiguity of which is preferable (and to avoid straying too far into politics), perhaps the more significant question is: has ‘cheaper’ or ‘bigger’ been achieved.

To answer that question, starting positions must be established because how do you know something’s grown if you don’t know what you had in the first place? You need to know what and where to measure. In effect, not just collecting data but putting it into context.

And that doesn’t simply mean collecting as much data as possible and then trying to make sense of it – even with the help of AI. Instead, context implies incorporating the concepts of comparability, precision, accuracy and timeliness, i.e.

Identifying growth depends on being able to compare your information across time and circumstances.
Those comparisons also need to be precise. Knowing something is approximately the same as it was might still be useful but if measures move slowly, precision is important to identify whether changes are working.
Likewise, accuracy – or targeting – is important to ensure changes have been made in the right areas. Again, knowing that everything is a bit different might be useful, but knowing which areas have changed significantly can help optimise your resources.
This all needs to be delivered in time for it to be useful. You’ll miss out on opportunities if you receive perfect information too late to make the necessary changes.

By using these concepts to ensure information is collected, managed and exposed in a standardised format, accurate operational metrics can be provided in a timely and specific way to make sure growth – however its defined – can be measured.

And those concepts aren’t specific to any specific business or organisational domain. Classifying, qualifying and quantifying data to produce good operational information applies regardless of how the data is collected or the ensuing information is used. Only the details (the vocabulary) changes, while the concepts (the grammar) remain the same.