This is the first article in a 5-part series, providing insight, advice, and guidance to small and medium-sized businesses, on how to become more data-driven in an increasingly digitalised economy. Complete our live benchmarking tool to compare your approach to data and analytics with small and medium businesses from across the UK.
During what continues to be the most unprecedented period of uncertainty for the global economy in more than a century, the power of data is proving transformational for many organisations across the UK. From accurate forecasting and scenario modelling, to understanding changes in consumer-behaviour and shifts in employee working habits, the way organisations manage their data has become a key differentiator between those who have remained operational during the pandemic, and those who have unfortunately succumbed to it.
The harsh reality of this has hit few harder than small and medium-sized businesses (SMBs), many of whom have been forced to accelerate their digital transformation initiatives as a means of survival. As a result, many business leaders have had to rethink their approach to decision-making, in a more contextual, connected and continuous manner, driven by data.
In fact, a recent Gartner report1 found that 65 per cent of business decisions being made today are significantly more complex than they were two years ago, with expert analysts warning that the current state of decision-making is unsustainable.
Why is this?
Historically, decision-making among many business leaders has been based on gut feeling, with two-thirds of organisations stating their decision-making process is rarely data-driven2. This has stemmed from multiple factors, ranging from a lack of data literacy and in-house expertise to limited investment into new technologies which effectively manage the proliferation of data – with the C-level preferring to allocate resources elsewhere.
The pandemic, however, has raised the expectation for decision-makers to be able to explain or justify their decisions. This has exposed the vital need for business decisions to be re-engineered, if significant improvements in critical, contemporary measures of performance, such as business value, cost, quality, service and speed, are to be achieved.
More importantly, it has amplified the critical role data plays in rethinking the way decisions are made, whether this be human-led, or machine-led.
An advanced level of data maturity, for example, can generate greater actionable insights which, when used correctly, can help businesses become nimble and responsive. Businesses with lower maturity will lack the foresight to make faster and smarter decisions in an increasingly digitalised economy, which demands more inclusive, transparent, personalised, flexible and trustworthy business outcomes.
Many business leaders of small and medium-sized organisations could be forgiven for thinking that an advanced level of data maturity is only achievable for larger enterprises, i.e. those with deep pockets and plentiful technical resource. However, with the advent of modern analytical technology, that is most certainly not the case. As we enter a new era, powered by cloud, AI and automation, there is no better time than now for small and medium-sized businesses to pivot their priorities, and become a “data-driven SMB”.
Addressing the data and analytics maturity issue
A report conducted before the pandemic began found that, while SMBs have invested significantly more time and money into their data and analytics initiatives over the last five years, many of these organisations are still falling short of achieving measurable business outcomes for their investments.3
In fact, according to Gartner’s IT Score for Data & Analytics, 73 per cent of midsize enterprises were still classified as having low data and analytics maturity in 2020. Only 9 per cent of midsize organisations from the same report stated that they were “very effective” at managing information assets strategically, and a further 21 per cent stated that they were “very ineffective”.4
What is hindering their maturity?
An organisation’s data and analytics initiatives are meaningless unless there is a clear understanding of who will be using the information, what decisions are being made, what business outcomes will result, and how those outcomes will advance organisational goals.
Despite the demonstrable need for a much more strategic approach to data and analytics, only 30 per cent of organisations align their data strategy with their broader corporate strategy, with many not even having a data and analytics strategy at all.
Furthermore, on average, every week a resounding 44 per cent of analysts’ time is being wasted manually searching, preparing and integrating data, primarily using spreadsheets5. This is invaluable time which a smaller organisation simply cannot afford to waste, and which would be much better spent on value-add analysis.
To make matters worse, despite all their efforts, analysts are only analysing about a third of their organisation’s data, with between 60 and 73 per cent of an organisation’s data never analysed6. This presents a serious problem, with organisations that rely on opportunistic, ad hoc practices unlikely to ever emerge from their low data maturity rut and be able to make truly informed decisions.
How can SMBs accelerate their maturity to become more data-driven?
To address this issue, SMBs must align their approach to data and analytics alongside their broader corporate strategy, while nurturing a culture of data literacy throughout the entire organisation. This can be achieved by engaging the right senior stakeholders, implementing the right infrastructure, processes and governance, adopting the right tools, and effectively training employees.
It is imperative, particularly with growing concerns for our economic future, that business leaders recognise that becoming data-driven is much more than simply procuring technology, merging spreadsheets and creating pretty dashboards.
With this in mind, TrueCue has designed a data and analytics maturity framework for SMBs. It is comprised of six pillars (strategy, process, data, platforms, analysis and culture and skills), and is designed to guide organisations through the necessary competencies to become data-driven.
We will explore the framework further in the next article in this series.
Data and analytics maturity benchmarking
As part of our ongoing efforts to empower business leaders with truth and certainty from their data, we’ve designed an interactive benchmarking tool that will allow organisations to compare their level of data and analytics maturity with industry peers.
Everyone who completes the assessment will receive a free personalised report, which provides insight into their organisation’s current level of maturity and how this aligns and compares with the wider SMB market. TrueCue will then provide actionable next steps on how they can improve their data and analytics maturity.
The rationale for this initiative is simple. In the current climate, the importance of having complete visibility and truth around your data has never been more critical. TrueCue is here to provide businesses with the technical know-how, framework and support required to navigate that journey with truth and certainty.
For more information please click here.
| This is the first part of a five-part series: To discover more follow the links below: Part 2: An Introduction to the Data and Analytics Maturity Framework Part 3: Data and Analytics Maturity Framework: Focus on Strategy and Process Part 4: Data and Analytics Maturity Framework: Focus on Data and Platforms Part 5: Data and Analytics Maturity Framework: Focus on Analysis and Culture & Skills Release Date – 16/02/21 |
1. Gartner Research Circle, “Reengineering the Decision”, 2020
2. PwC’s Global Data and Analytics Survey 2016
3. Midsize Enterprises Need to Get More Value From Data and Analytics Investments
4. 3 Questions That Midsize Enterprises Should Ask About Data and Analytics. Gartner, 2020
5. State of Data Science and Analytics Report. IDC, 2019
6. Closing the Data-Value Gap – How to become data-driven and pivot to the new. Accenture, 2019