The hidden Data tax you pay on your business growth – The Growth Tax Newsletter #6
growth tax, noun
A hidden cost or inefficiency that slows down a company’s growth rate, reducing its potential to expand and succeed in the market.
Sherlock Holmes once said “It is a capital mistake to theorise before one has data.”
And it’s just as relevant 140 years later.
As we will explore in this month’s Growth Tax newsletter, failing to prioritise data accuracy and building up the right data-led culture costs more than just inefficiency, it can derail strategic decision making altogether.
Just last month, TNT, the media company that merged with Eurosport, and which streams a variety of pay to view sports including cycling, hiked the price of their plans 343% from £6.99 / month to £30.99 / month.
In a move that seems detached from the data, or customer insight, a recent survey suggested that just 2.5% of the original £6.99 / month paying audience were willing to pay the new monthly subscription. Some basic maths suggests TNT is set to lose money from this move rather than benefit from it.
Data Tax, noun
The costs incurred when your brand makes sub-optimal decisions, or mistakes, through the use of inaccurate data, mismanagement of data or the wilful act of ignoring its insights.
Data; the basics matter
It’s a difficult time to be evaluating how a business might best use data. This includes but isn’t limited to the proliferation of so many new data sources (exacerbated by media fragmentation), new legislation governing the handling of data (GDPR), Google’s flip flopping over killing off the 3rd party cookie, and now the arm’s race of using AI to drive greater efficiency and effectiveness in all aspects of operations and data management. And that’s before businesses tackle how to best access, store and use the data within its own (often legacy) systems. However, just like the marketing challenges faced by businesses evolve over time (see image below), the sophistication of data management practices should evolve over time too.
Most importantly, scaling businesses need to focus on getting the basics right when it comes to accuracy and reliability of their data.
A recent (client) example
We recently worked with a fast-growing and scaling B2B business which had a high level of data fluency but the data itself was found to be highly unreliable. This was leading to lots of false insights and poor decisions as a result, demonstrating the importance of accuracy and consistency in the data upon which vital business decisions (like marketing spend or resource allocation) are being made. Fortunately we caught this as part of a routine check during our Marketing Competency Audit but many businesses will be operating on the assumption that the data they’re seeing is accurate.
The challenge of ensuring accuracy and validity of data is easy to overlook and can affect all businesses. Public Health England is a famous example where an outdated version of excel files were being used to compile the reported number of covid cases. The result? At a crucial (early) stage in the handling of the pandemic, 50,000 potentially infectious people were missed from the data; a huge number of people that may have changed the conclusions and/or responses to the pandemic at the time.
Data as a culture
The second consideration is using data as a cultural norm to aid decision making. It’s more difficult, requires time to embed and can be uncomfortable to adjust to. First it can de-centralise decision making, empowering people or teams to challenge decisions. Businesses need to lean into this and embrace the fact good decisions can come from anywhere in a business, not just the boardroom. It also establishes cultural norms around how and why decisions are made and brings transparency and accountability over decisions.
Boeing is a good example to draw upon here. Faced with two horrendous crashes of their new 737 MAX airplanes, they decided to blame the pilots rather than accept what the data was telling them. Only later did they accept the truth; that the crashes were the result of technical errors. These decisions about transparency and accountability through its culture are still affecting the company nearly a decade later.
TELL-TALE SIGNS 💡
If your business is struggling to embed the use of accurate data into day-to-day decision making, there are a number of things to look out for:
- Are key decisions driven by gut feel or opinion, causing conflict, instead of using data to guide discussions?
- Are different teams providing different insights, highlighting a need to centralise reporting, review what really matters or check data accuracy?
- Do you have plenty of data but lack actionable insights, which can erode confidence and cause hesitation in decision-making?
- Is data used in the business, but decisions sometimes contradict what the data suggests?
A final word
One of the biggest challenges for fast growing and scaling businesses is to balance the strategic use of data so it can scale and support the key decisions the business will face, not just now but in the future. Whilst at the same time recognising the risks (and costs) of overcomplicating things or not getting the basics accurately in place. Ultimately, the data fluency of an organisation lives as much in its people as it does its structural and governance processes.
When a business ignores these tell-tale signs, and acts in conflict with what the data is telling them, it risks acting out of step with its customer or audience. And this is often how new competitive threats emerge and/or marketplace dynamics change. Time will tell if this happens to TNT Eurosport in the same way Airbus has benefited from Boeing’s downfall.
If you missed our last growth tax newsletter, you can read it here. And if you want to talk to us about any of the topics in our growth tax newsletter series and how they relate to your business, drop us an email.
Next month we’ll be looking at Knowledge Tax. Sign-up to the series to make sure you get the next instalment and if you like what you read, share it with your colleagues.
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