In the sometimes confusing and opaque world of data management, in can be difficult for businesses to get useful insight from the valuable data they have collected. Data analytics represents a powerful medium to extract meaningful information from raw data that can in turn be used to drive value through trends and patterns. These metrics provide businesses with a transparent view of their organisational capabilities and answer key questions to assist with effective decision making.

The key issues middle market businesses are facing.

There is increasing pressure on most companies, not just middle market businesses, to grow revenue whilst maintaining the same cost base. This pressure can be mitigated by companies having a stronger understanding of what their data means and how they can apply the findings. Data analytics can provide in-depth insight into customers, specifically the types of products or services they are purchasing, what price points they occupy, and how frequently they are made. This information outlines an entire customer journey and presents valuable metrics on how to best market products or services. It is in understanding which products or services are the strongest performers, not just in terms of revenue but also profitability, that underperforming companies can take a stronger stance and therefore focus their efforts. This approach also bridges marketing and sales, allowing for customer sales to be directly compared with the efforts of sales and marketing teams to help measure the effectiveness of campaigns and highlight areas that require training.

How data analytics can improve efficiencies and reduce costs

Another common pain point is the pressure to reduce costs and improve efficiency. The data analytics approach required in this instance is an exercise in streamlining through calculating the total cost to serve and report the findings. This is an effective way to improve profitability through focusing on brand objectives and profitable products, whilst identifying and removing non-core products.

The sales cycle is another critical element that requires focus. Analysing sales transactions that require intervention, correction or return credit is important in measuring the sales cycles’ efficiency. Using data analytics to measure this provides companies with a complete picture when combined with the revenue findings. From here, a business struggling with these pressures can find a strong basis to develop a strategic platform.

What should a business consider when adopting data analytics strategies?

It is important when starting to set a clear business objective. Data analytics initiatives are at their most successful when aligned closely with the strategic objectives of an organisation. Time must be spent in understand the sources of data and the processes that create it. It is also important to select the correct technology for the given task. Simplicity is key, as whilst the technology being applied can be complex, the application of the results is human and therefore best kept straightforward. To ensure a regular return on investment, it is worth considering introducing data and analytics in incremental packages. With each package delivering a specific business value, delivery teams can remain aligned with the business requirements.

COVID-19: how has this impacted the use of data analytics?

Data analytics has been on the radar for many organisations before the COVID-19 pandemic, but certainly this period of increased remote working and transition to e-commerce has led to an increased awareness at senior management levels. Pushback that has previously plagued digital initiatives such as data analytics has largely disappeared as the importance of such platforms has been proved. Organisations are learning that such initiative do not carry inherently high price tags and can be implemented in a controlled, low-cost manner. Whilst this is not a specific uptake of new technologies, many of which existed pre-COVID, it does represent an accelerated pace of digital change.

How will data analytics impact the middle market?

As more companies adopt data analytics initiatives, it will become more competitively advantageous for others to do the same. The adoption of cloud technologies that naturally lend themselves to managed service solutions will provide opportunities for middle market firms to outsource their analytics platform. If organisations would prefer to keep their analytics platforms in-house, the cloud solutions provide a cost-effective infrastructure and allow for incremental increases in investment based on performance and requirements.

How RSM is using data analytics to help clients

Firstly, RSM have been working extensively on defining our client’s data analytics strategy and roadmap. This requires an assessment of their current data sources, the quality of their data and then mapping that against the client’s business objectives and reporting requirements. This is a crucial first step that allows businesses to prioritise the deliverables that data analytics can offer and then break them down into manageable packages of work.

For many established organisations, they already have a wealth of data to work from but simply are lacking the tools required to effectively use it. This has led to many requests for RSM to help develop dashboards that sit on top of existing data, providing an interactive and visual output for decision makers.

The future of digital innovations within businesses is a bright one. Despite the global challenges being faced across middle-market organisations, data analytics has proven itself to be a powerful and essential tool to ensure long-term growth.