Understanding the Value of Data Analysis

Every time you look at your P&L and review your income and expenditure, you are doing data analysis. However, far too many of us small business owners aren’t good at seeing the value in extending this exercise to other areas of the business such as sales, marketing and operations.  If we think about it, we collect data in all these areas - sometimes loads of it!  However, we are less good at being able to conceptualise what that data could tell us about how we are performing.  Data analysis takes that data, turns it into information we can use and presents it in ways which can really begin to tell a useful story that can have a meaningful impact, driving decision making towards a more evidence based approach that can lead to significant, measurable performance improvement.

Key stages in data analytics

Integrating data: pulling data together from a range of possible sources so that you can see relationships and trends across data sets

Analysing data: creating tables that provide useful information from the data.  For example, seasonal trends in sales of products

Presenting data: creating visual presentations of data.  This is important because for the vast majority of us, when we look at data tables, we can’t see the wood for the trees.  Graphical representation of the data is much easier for most minds to see patterns and trends that we can use for decision making.

Key Benefits of Data Analysis for UK Small Firms

Improved Decision-Making: Small business owners and senior managers often like to think they have a really good understanding of performance strengths and weaknesses.  However, it is too easy for this to result in us making assumptions. It is remarkable how often some well presented data analysis can prove our assumptions to be wrong and help us to improve our decisions.

Enhanced Efficiency: Simple time tracking can reveal really significant inefficiencies in our use of human resources.  How much time is wasted with duplicate data entry or manual tasks activity that could be automated?  Where are the production bottlenecks which could unlock additional capacity if solved?

Increased Customer Satisfaction: Analysing sales data helps us to understand customer preferences and behaviour which enable us to look at those key marketing attributes of product (design), price, place (distribution channels) and promotion (how we communicate with them) in ways which improve customer experiences and satisfaction (and so, loyalty)

Competitive Advantage: Our larger competitors are already well established in data analytics and the sophistication of their analysis is increasing rapidly (and exponentially so with AI).  The longer we delay our own use of data analytics, the more we disadvantage ourselves in the marketplace.  Data Analytics is no longer a ‘nice to have’ - it’s a ‘must have’ in order to remain competitive.  However, this is not just about defence.  Data Analysis will invariably help a small business to identify USPs it wasn’t even aware of and market opportunities that others haven’t spotted or are of no interest to them.  It’s a hugely powerful tool to help drive strategy.

Risk Mitigation: visibility of performance data can help to identify potential risks before they materialise.  In this sense, data analytics also provides a very powerful safety net.

Every time you look at your P&L and review your income and expenditure, you are doing data analysis. However, far too many of us small business owners aren’t good at seeing the value in extending this exercise to other areas of the business such as sales, marketing and operations.

Getting Started with Data Analysis

This can often be the biggest and most challenging barrier.  Where do you start?

Some tips:

Start small. Identify a discrete and (reasonably) self-contained area of the business.  Try to avoid starting with something that is going to set hares running to all corners of the business!

Look at the data you have.  Everyone has at least some data - use this as the basis for your case study.  Very often, a great place to start is the accounts.  There is lots of data there and if you can’t get to grips with it yourself you will have someone on hand who can (your accountant).

Identify issues in the data.  Dig into the causes of the issues.  If you don’t have data relating to these, set up mechanisms to start capturing the data you need so you can start to understand what is happening.

Identify the tools you need to capture the data and create reports.  More often than not, this will be a spreadsheet.

Identify the skills you need to create the data capture tools (e.g. a spreadsheet template) and create reports that analyse the data.  In the vast majority of cases, this will also mean spreadsheet skills.  

There are many epithets about how all business runs on spreadsheets.  It’s pretty much true.  And a huge amount of data analysis can be achieved through spreadsheets - especially when you start to use add-on modules like PowerBI and AppSheet. And spreadsheets cost almost nothing, I find it almost impossible to imagine an organisation that doesn’t have spreadsheets available on almost every device.  The far bigger challenge is the skills.  People with advanced spreadsheet skills are expensive - and data analysts even more so.  However, there is now a solution to this in the UK which is growing rapidly in popularity: data analysis apprenticeships.

There are two relevant apprenticeship programmes:

Data Technician (Level 3)

Data Analyst (Level 4)

These are two of the fastest growing apprenticeships in the UK in 2023-24 and for good reason - they open up two interesting options for small business owners wishing to make better use of data analytics in their business:

Develop the skills of existing staff - this could be the business owner themselves or a relevant member of the senior management team  - possibly even more than one.  With government founding 95% of the cost of the training, this can be an incredibly cost effective option

Employ an apprentice - which would normally mean a younger adult who is already fairly IT literate who could add huge value to the business through their apprenticeship programme and the knowledge and skills it will help them to develop.  There is a salary cost here but again the training is 95% funded by the government (or 100% if they are under 22 years old when they start).

Conclusion

In today's data-driven world, small firms can no longer afford to ignore the power of data analysis. By leveraging data, even small organisations can improve efficiency, identify new markets and enhance customer satisfaction and loyalty and so enable them to compete more effectively both against their peers and larger competitors.  At least some of the data will already be in place, as will the tools to analyse it.  The significant challenge is the skills, however, there is now a powerful and incredibly cost effective solution for this through the apprenticeship scheme.  Large organisations are already using it to great effect - we need to get the message out to small firms so that they can as well.

Head to Boom Training to find out more about us and our data programmes.