Harnessing the Power of Data Analytics

This article has been written by Dr Najib Murad, Senior Lecturer of Management, Work and Organisation at the University of Stirling.

There are various definitions of operational efficiency but in the simplest terms, it is the ability to deliver products and services cost effectively without sacrificing quality.  

There is a misconception that operational efficiency only applies to manufacturing and production. In reality, it applies to all businesses, and this is addressed in the Help to Grow: Management Course. 

A powerful tool that is becoming indispensable in achieving these goals is data analytics. This short article will outline some of the key ways in which data analytics can help to deliver value for small businesses.  

Many small businesses adopt some form of technology, be it point-of-sale (POS) systems, website, e-commerce platforms or social media sites.  

Small businesses can leverage analytics generated from this technology. The use of business intelligence tools provides valuable insights into business performance, customer behaviour and market trends. Tools such as Google Analytics or Microsoft Power BI enable businesses to analyse data, generate reports and make data-driven decisions to optimise business operations. These tools require little capital investment.  

A data driven strategy can then be developed to assist in every area of the business. By leveraging historical data from business intelligence tools, businesses can proactively identify patterns of consumer behaviours and trends.  

The use of analytics can also help businesses develop more streamlined processes in order to reduce costs and improve productivity. Predictive analytics allow businesses to anticipate equipment failures, identify potential bottlenecks and forecast demand with remarkable accuracy.  

Let’s take the example of a coffee shop. It can forecast demand more accurately by analysing sales data, foot traffic patterns and customer preferences. This would enable them to adjust inventory levels, minimise waste and ensure that they always have the right amount of fresh ingredients on hand. The coffee shop can also allocate staff more efficiently by leveraging data analytics to track peak hours and popular menu items. This allows them to efficiently manage staff, reduce wait times and improve customer satisfaction. 

Supply chains are the backbone of any business and optimising a supply chain’s efficiency is crucial for staying competitive. Data analytics allow businesses to gain insights into their supply chain processes, from sourcing raw materials to delivering finished products and services to customers.

Through providing the means to analyse vast amounts of data, businesses can identify inefficiencies, optimise inventory levels and streamline logistics operations. In this way, they can improve delivery times, reduce costs, and enhance customer satisfaction.  

If we return to our coffee shop example, we can understand the basic principles in a familiar set of procedures. The coffee shop can gain insights into which menu items are most popular and profitable by analysing sales data. This information can inform menu optimisation efforts, helping the coffee shop to focus on the products that resonate most with customers.

The coffee shop can then analyse the profitability of each item by factoring in ingredients cost, preparation time and selling price. Armed with this information, the coffee shop can adjust its menu to emphasize high-margin items while phasing out or reimagining less profitable ones. 

In a similar way, by tracking inventory levels and supplier performance, the coffee shop can optimise its supply chain management, reducing costs and ensuring consistent quality. By integrating point-of-sale (POS) systems with inventory management software, the coffee shop can track real-time inventory levels and identify reorder points when they reach a predetermined threshold.

Historical sales data can be analysed to forecast demand patterns, allowing the coffee shop to anticipate fluctuations and adjust inventory levels accordingly. This prevents overstocking, reduces the likelihood of running out of key ingredients and streamlines the procurement process. 

By monitoring supplier performance metrics such as lead times, order accuracy and product quality, the coffee shop can identify areas for improvement and negotiate more favourable terms with suppliers.

For example, if a particular supplier consistently delivers late or provides subpar ingredients, the coffee shop may explore alternative suppliers or renegotiate contracts to secure better terms. 

Informed decision-making is at the heart of operational efficiency, and data analytics helps small businesses make smarter, data-driven decisions. By leveraging real-time insights and predictive models, businesses can quickly adapt to changing market dynamics, identify new opportunities and mitigate risks. 

Whether it is adjusting production schedules, reallocating resources or optimising marketing strategies, data-driven decision-making ensures that businesses stay agile and responsive in an ever-evolving landscape.  

Continuous improvement is not a one-time endeavour but a journey towards excellence. Data analytics plays a pivotal role in this journey by providing the tools and insights needed to identify areas for optimisation and innovation.

By monitoring key performance indicators (KPIs) and benchmarking performance against industry standards, businesses can identify trends, track progress and implement targeted improvements that drive sustainable growth and competitiveness. 

Find out how to effectively implement technology that will improve operational efficiency through the Help to Grow: Management Course, by clicking here.