The Data-Driven SMB

1. The critical role of data in decision-making

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.

A 2020 Gartner report found that 65% 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.

Source:  Gartner Research Circle, “Reengineering the Decision”, 2020​

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.

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-driven¹. 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.

2. What does it mean to be a data-driven organisation?

In a data-driven enterprise, data and analytics are no longer afterthoughts — they are fundamental to driving business value and digital business transformation. Yet the ability to “think in data” is difficult for most organisations, especially SMBs.

Why? Well, building a data-driven enterprise is not just about encouraging the use of data in decision-making. Organisations must develop the appropriate competencies and align these with the business’ ambitions for generating information value.

Rest-assured, organisations who treat their data and analytics as supportive and secondary to their business initiatives, will never become data-driven.

In fact, an organisation’s data and analytics initiatives are essentially 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.

So, if what we just said isn’t how you’re approaching your own initiatives, then you should probably reassess your approach.

Unfortunately, this is the case for most small and medium sized businesses across the UK, with the vast majority of SMBs operating without a data and analytics strategy, and for those organisations who do have a strategy, only 30% align this with their broader corporate strategy.

Source: Global AI Survey: AI proves its worth, but few scale impact. McKinsey, 2019

Furthermore, on average, organisations are only analysing about a third of their data, with between 60 and 73 per cent of an organisation’s data never analysed.² 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.

In contrast, those organistions who can define themselves as having greater data and analytics maturity, recognise and value the potential of being data-driven in an increasingly digitalised economy, which thrives on data and the analysis of data.

For these organsations, data and analytics have become a primary driver of their business strategy. It has become the fabric of everything they do.

How do they differ?

They create a vision of a data-driven enterprise, which captures the aspirations of every senior stakeholder in the business.

They ensure that authority and accountability for data and analytics are in balance with the organisation’s data-driven ambitions.

They change and adapt their data and analytics operating model to account for data and analytics competency gaps.

They diffuse these competencies throughout the organisation to develop the data-driven culture which is so fundamental for achieving the success of their vision.

Furthermore, these organisations will be asking themselves thought provoking questions, such as:

• “How can we treat data as an asset?”
• “With this data, or this type of insight, how could we fundamentally change the value propositions for our customers?”
• “How can we create new information products and services?”

Conceiving and answering these types of questions requires an expanded set of data and analytics competencies, as well as an organisational culture that embraces data literacy.

The success of any organisation’s data and analytics initiatives, is therefore very much dependant on having a much more expansive and open-minded approach to their role in business value generation. It requires business leaders to embed data and analytics into everything their organisation thinks, says and does.

This is not a simple exercise, and to achieve success, business leaders will need to address the depths of the challenges as much as they realise the heights of the opportunities, appreciating the myriad of work required to truly become a data-driven organisation.

What are the benefits of becoming a more data-driven organisation?

There is no denying that data-driven organisations are more competitive, more resilient to external threats and better positioned to achieve their strategic objectives.

In fact, a recent YouGov survey found that 80% of data-driven businesses claim they have had a critical advantage as the impact of the pandemic continues to disrupt the global economy.⁶

When asked how being data-driven during the pandemic helped, business leaders acknowledged multiple benefits, including:

Furthermore, business leaders are increasingly reliant on their data and analytics resources and expertise, within the lines of business, in order to help them make more informed decisions supported by data.

Whether this be marketing using cross-channel customer analytics to understand and improve the customer experience, HR using people analytics to address key talent risks while improving recruiting and retention, or the revenue department leveraging sales analytics to provide insights into which leads are the most likely to convert, the use cases for maximising your data assets to drive business value, are endless.

How do I know whether my organisation is data-driven?

Despite the obvious benefits of becoming data-driven, according to a 2019 report by Accenture, only 32% of companies are realising tangible and measurable value from their data ⁷, whilst research from Gartner last year, found that an overwhelming 73% of midsize organisations are classified as having low data and analytics maturity.⁸

So, for business leaders who are committed to becoming more data-driven, the starting point must be to first understand what the necessary competencies are for achieving greater data and analytics maturity, and to then understand how to advance these.

With this in mind, TrueCue has designed a data and analytics maturity framework for small and medium-sized businesses. Comprised of six pillars (Strategy, Process, Platforms, Data, Analysis and Culture and Skills), our framework has been engineered to guide organisations through the necessary competencies to become more data-driven.

Our framework evaluates the current level of data and analytics maturity across each of these six competencies, based on four dimensions that are unique to each competency and scored between 1 (low) to 5 (high), based on the current level of maturity. 

For example, an organisation may score highly for analysis in the dimension of ‘sophistication’, but also score on the low-end of the scale in relation to its analytics automation capabilities.

As the competencies are interdependent on each other, to improve an organisations data and analytics maturity, a holistic approach should be taken whereby all key areas need to be improved relative to one another. By doing so, businesses can ensure there is a seamless alignment between data and analytics initiatives, and the objectives of a corporate strategy. 
 
Once an organisation has a clearer understanding of its maturity level within each of these key competencies, it will be able to start prioritising the areas that require immediate improvement. 

Our framework offers small and medium sized businesses a simple way to achieve this, enabling them to logically navigate to the next-stage on their journey to becoming more data-driven.

How can I accelerate my organisation’s data & analytics maturity?