In today's data-driven world, the potential for small and medium businesses to thrive and innovate through the effective use of data is immense.
A recent survey of 500 UK companies found that those using data were 13% more productive than those that didn't [1].
[1] source K. Lepenioti, A. Bousdekis, D. Apostolou, G. Mentzas, Prescriptive analytics: Literature review and research challenges, International Journal of Information Management 50 (2020) 57–70.
With SMEs estimated to generate 60% of employment and 40% GDP[2], there is a big win for business owners to improve in this area to improve overall innovation and growth.
However, when it comes to data strategy and data management a lot of focus is often on large enterprises rather than SME’s. That is particularly evident in the approximate level of adoption where it is estimated that less than 1% [3][4] of SME’s are adopting data analytics to drive their business in comparison to approx 25% of large enterprises.
[2] S. K. Lam, S. Sleep, T. Hennig-Thurau, S. Sridhar, A. R. Saboo, Leveraging frontline employees’ small data and firm-level big data in frontline management: An absorptive capacity perspective, Journal of Service Research 20 (1) (2017) 12–28.
[3]M. Willetts, A. S. Atkins, C. Stanier, Barriers to smes adoption of big data analytics for competitive advantage, in: 2020 Fourth International Conference On Intelligent Computing in Data Sciences (ICDS), IEEE, 2020, pp. 1–8.
[4] S. Coleman, R. Göb, G. Manco, A. Pievatolo, X. Tort-Martorell, M. S. Reis, How can smes benefit from big data? challenges and a path forward, Quality and Reliability Engineering International 32 (6) (2016) 2151–2164.
So why is the adoption so low? Are there too many barriers for SME’s?
Encouragingly a recent survey we conducted with Senior Leaders of 100 UK SME’s, found that 69% believed that being data-driven was very important. The majority were also using data in some way, with 20% saying that becoming data-driven was of very high priority.
In this blog, we'll delve into the common challenges faced and explore actionable strategies to overcome them.
Lack of Resources:
37% of our responders stated they had insufficient resources to develop a data strategy
Small businesses often operate with limited budgets, with the focus often being on short-term initiatives to drive sales within an acceptable return on investment. This makes investing in an unproven sophisticated data infrastructure and tools that will require a longer-term strategy more difficult.
Overcoming this barrier requires a creative approach and shorter-term ‘proof of concept’ approach before investing in an unproven approach.
Focus on one area of the business that could use more insight - often marketing could do with more customer insight.
Don’t try to get to the perfect automated solution on day one - look at what data is available and conduct some top-line analysis. Consider the current tools you already have, Excel is still one of the most powerful tools for data analytics, or explore open-source data tools, cloud-based solutions, and cost-effective analytics platforms.
Lack of Skills:
36% of our responses said they had insufficient skills or expertise in data.
The technical skills required to gather, analyse, and interpret data effectively can be daunting. However, small business owners and employees can upskill through a huge range of online courses, workshops, and tutorials. Collaborating with local universities, and community colleges, or hiring interns with data-related skills can also help bridge the knowledge gap.
Leveraging external resources like freelancers or consulting services can also provide specialist expertise without the commitment of a full-time hire. They have done it before and will get you to the solution quicker than starting from scratch. Work with them to upskill your existing team.
Interestingly, 94% said they have data analysis skills in the business with only half dedicated purely to data analysis.
With 45% saying they have dedicated data management and governance resources.
Being data-driven isn’t purely about the analysis its important to have the right skills across the data landscape.
Lack of Data Integration:
Often, data in small businesses is stored in disparate systems, making it challenging to gain a holistic view.
Investing in integration solutions or employing a data consultant for a short period of time, to bring together data from various sources can provide a comprehensive perspective, enabling more informed decisions.
But this can often be the holy grail that is so rarely achieved - don’t get caught up with everything contacting to each other, it can get expensive. You can make some great wins by starting to use the data you have to do specific tasks i.e. using Google Analytics for website optimisation, or creating a data-driven culture where your teams are learning from each and demonstrating how data have helped them make decisions.
When you are looking to implement new systems do include in the requirements that it needs to be able to ‘talk’ to the existing system and needs to be part of the implementation process and this will make it easier than doing it retrospectively.
30% of our respondents stated that they had poor communication across their teams. With only 19% stating they had inadequate data management and governance.
Lack of Trust in Data:
22% of our respondents stated that they have a lack of trust in their data.
Misaligned or inconsistent data often leads to mistrust and skewed decision-making. Building trust in data involves those who are using it to know and understand the imperfections of the data.
Even with rigorous data quality control processes, things go wrong, and spotting when something does and the impact it might make is really important.
Trust comes from explaining why one report says something different to another. By always ensuring that data analysis is checked before presenting it, checking with other sources to see whether ‘it makes sense’ and being upfront about the definitions. The reason the reports are different is often because they are comparing very different data.
Build consistency in the definitions of data across the business and if things change keep them documented. Teach users how to validate data and how to use data to identify trends and patterns.
Data insight is only as good as the data collected.
47% of our respondents stated that they have difficulties in collecting accurate data.
Ensuring good data collection methods is essential, no matter how good your data analysis team are, if the data is poorly collected the output is going to be incorrect.
Fear of Change:
Generally people aren’t great with change and embracing data-driven strategies might disrupt established routines, leading to resistance.
Becoming more data-driven as a business will take time and will not happen overnight, take time to understand where resistance is coming from. Some people have a legitimate fear of numbers, some may feel demotivated as they think their experience is being replaced or fear of not knowing what is going on.
Take your time to understand this to take your people with you, they are important. Data is here to help, supporting and enabling businesses to be more productive. Demonstrate the positives it can bring and how team members can be even more brilliant at their job by using it.
As previously discussed a gradual approach through developing ‘proof of concept’ or pilot projects can help demonstrate the positive impact of data-driven decisions without overwhelming the business.
Overcoming Barriers: Strategies for Success
There are many strategies available for SME’s to explore to ensure they can reap the benefits that data can provide:
Start Small: Begin with manageable data projects that have clear objectives. Gradual successes can build confidence and momentum for more extensive data initiatives. Provide incentives for using data to make decisions and highlight the benefits of data-driven decision-making.
External Support: Engaging with data consultants, freelancers, or agencies can provide specialised knowledge and guidance without the need for full-time, on-going in-house expertise.
Data-Driven Culture: Cultivating a culture that values data and rewards evidence-based decision-making can drive positive change. This starts at the top, with leaders setting an example. Encourage the management team to demonstrate how they use it to support decision-making and setting the expectations throughout the business.
On-going skills development: Support ongoing training and workshops for employees, as this can empower them to use data effectively. This could include basic data literacy training or more advanced courses on data analysis.
Collaboration: Forming partnerships with other small businesses, industry associations or government initiatives, there is a strong focus on SME’s in the UK Data Strategy. These can provide access to funding, shared resources, expertise, and collective data insights.
While small businesses face numerous barriers to practical data usage, these challenges are not insurmountable.
With a combination of planning, education, and a willingness to adapt, small businesses can harness the power of data to drive growth, innovation, and lasting success in today's competitive landscape.
Embracing change and viewing data as an opportunity rather than a challenge, can pave the way to using data as well as their larger competitors.