The amalgamation of an increasingly complicated world, the vast proliferation of data and the pressing desire to stay at the forefront of competition must prompt Ghanaian businesses to focus on using analytics for driving strategic business decisions. Managers of businesses must rely on business analytics to understand the dynamics of their businesses, anticipate market shifts and manage risks. Rather than ‘going with gut’ when maintaining inventory, pricing solutions or hiring talent, companies must embrace analytics and systematic statistical reasoning to make decisions that improve efficiency, risk management, and profits.
Data analytics are disrupting existing business models and ecosystems in the global world of business. It is worth noting that the proliferation of new datasets and the introduction of massive data migration capabilities are undermining existing information and technological silos in today’s business environment. From using granular data to personalise products and services to scaling digital platforms to match buyers and sellers, companies around the world are using business analytics to enable faster and evidence-based business decision-making.
Empirical works have shown that data-driven organisations not only make better strategic decisions, but also enjoy high operational efficiency, improved customer satisfaction, and robust profit and revenue levels. Contemporary research has also revealed that data-centred organisations are 23 times more likely to acquire customers, 6 times more likely to retain those customers, and 19 times more likely to be profitable.
Modern-times business analytics experts have developed a vast array of analytical tools and techniques to address present-day dynamic business needs. These range from the most fundamental techniques, ‘descriptive analytics’ which involve preparing the data for subsequent analysis, to ‘predictive analytics that provide advanced models to forecast and predict future, and to the top-notch of analytics called ‘prescriptive analytics which utilises machine learning algorithms and dynamic rule engines to provide interpretations and recommendations. With their diverse use-cases and applications, it is no longer a surprise that these techniques are now finding a way into customer, workforce, supply chain, finance and risk strategies at the organisational level.
Data is the new oil, and the best way for Ghanaian businesses to access and understand it is to digitise their processes. Digitising customer interactions can provide troves of information, which companies can feed into strategy, sales, marketing, and product development. Detailed and granular data can enable companies to micro-target their customers and to personalise their products and services.
Further, internal digitisation generates data that managers can use to improve their operations – including routing and transportation, resource allocation and scheduling, capacity planning and manufacturing. These trends are also causing many companies to converge their ‘Business Intelligence’ and ‘Operation Research’ units on the common ground of predictive and advanced analytics. Both communities are now using statistical and mathematical techniques to attack strategic business problems and systemise decision-making.
Data analytics, with its far-reaching use cases and diverse applications, is now emerging as the keystone of strategic business decision-making. From enabling businesses to make consumer-oriented marketing decisions to help them address key operational inefficiencies, analytics is radically changing perceptions toward the importance of data. Advanced statistical models are furthering this cause by providing valuable insights out of unconventional data sets and by enabling companies to explore new business territories.
In an increasingly customer-oriented era, I believe that most Ghanaian businesses gather a wealth of consumer information and data regularly. To remain competitive, Ghanaian businesses must utilise these consumer insights to shape their products, solutions and buying experiences. My recent analysis of some existing data has revealed that Ghanaian businesses which use their consumer behaviour insights strategically are outperforming their competitors by about 80 to 85 percent in sales growth margins, and by more than about 23 to 25 percent in gross margins.
Thus, managers of Ghanaian businesses need to consider the strategic use of consumer information. This is because a comprehensive and refined understanding of customers through thoughtful robust business analytics can offer business managers an insightful narrative about buying habits and preferences of their customers. For instance, a telecom company can employ advanced and predictive analytical models to reduce customer churn and measure the effectiveness of marketing campaigns. Likewise, an online retailer can understand its web presence by seeking answers to questions such as the mix of new and returning visitors, bounce rate and average session duration. Such questions offer crucial insights into what types of content over what channels and formats are likely to have the greatest impact on key consumer segments.
Furthermore, pattern-data can also generate valuable customer insights that can be used to direct marketing expenditures. For instance, an automobile seller can employ business analytics to study its consumers’ purchasing and behavioural history and discover that the majority of its high segment consumers are far more likely to rely on dealer distributors for product recommendations, and are less likely to be influenced by trade show exhibitions and marketing collaterals. This, in turn, can help marketing managers of such businesses to reallocate budgets. Therefore, it is my scientific opinion that business analytics can enable Ghanaian business managers to gain competitive intelligence on market conditions, target consumers more successfully, and optimise processes.
While encouraging Ghanaian businesses to spend considerable time analysing consumer data and frontline monetisation opportunities, it is equally imperative to focus on improving productivity and performance through business analytics. Data analytics can play a huge role in reducing inefficiency and streamlining business operations. For instance, reporting and analytical dashboards can identify data correlations and provide managers with detailed insights to perform cost valuations, competitive benchmarking and pricing segmentation. Likewise, using analytics to measure key performance metrics across areas such as operational excellence, product innovation, and workforce planning can produce calculated insights to solve complex business scenarios.
Business analytics can also improve the way Ghanaian businesses attract, retain and develop talent. For instance, a consulting group in Asia recently decided to undergo a major restructuring process. As part of this initiative, the leadership wanted to identify employees with high potential to succeed and gain a greater understanding of key performance indicators.
The analytics team began by streamlining data points such as professional history, education background, performance, age, marital status, and demographics. After running the collated data through multiple regression models, the team was able to identify the employee profiles that had the best chances of succeeding in particular roles. The research and analysis also suggested the key roles that had most impact on the company’s overall growth. As a result, the company restructured around the key functional roles and talent groups.
Another area where Ghanaian businesses can use data analytics to provide a unique value proposition is Supply Chain. Supply chains are great places to look for strategic opportunities and advantages; partly because of their complex nature and partly because of their important contribution to a company’s cost structure. By employing analytics in this context, Ghanaian businesses can not only identify hidden inefficiencies in existing structures to generate greater cost-savings, but also analyse significant supply chain investments and decisions by performing risk-modelling and assessments. Managers can then dive deep into specific improvement opportunities such as inventory management, channel management, procurement, and logistics.
Ghanaian businesses, like many other organisations across the world, are exposed to immense risk from structured data such as databases and unstructured data such as websites, blogs, and social media channels. By leveraging risk analytics, Ghanaian companies can find themselves in a better position to quantify, measure and predict risk. Managers of Ghanaian businesses need to see risk analytics as an enterprise-wide approach and must develop strategies to pull data across different organisational levels and functions into one central platform. By establishing a standard baseline for measuring and managing risk, Ghanaian businesses will be able to incorporate risk considerations into their core strategic decision-making process and predict likely scenarios.
It is refreshing to find out from my recent analysis that most Ghanaian commercial banks are leading this analytical space in discovering new ways to exploit transactional and behavioural consumer data. They are routinely going beyond the conventional structured information such as credit score reports and also looking out for unconventional sources of information, such as loyalty card consumer data and government information. By capturing such massive data sets, most Ghanaian commercial banks are able to increase the accuracy, reach and predictability of their credit risk models.
From identifying high-risk payments before they are executed to predicting the likelihood of a customer defaulting a mortgage payment or a loan repayment, risk models are leading the way by providing advanced and valuable insights. Therefore, other Ghanaian businesses should focus on enhancing and exploring operating business models. Advanced data models will make risky business decisions more uniform, enhance the quality of data and provide greater agility to address unconventional data requirements. By becoming more risk-intelligent, managers of Ghanaian businesses will be more adept at dealing with uncertainty and strategic at decision-making.
In concluding this article, I would like to emphasise that in this volatile environment of data-driven disruption, managers of Ghanaian businesses need to concurrently look through two lenses. Firstly, they have to identify high risk and rewarding opportunities such as entering new markets and changing existing business models. Secondly, they have to maintain their focus on including data analytics into their core business decision-making processes. By embedding data analytics into their core strategy, they can streamline internal business processes, identify unfolding consumer trends, interpret and monitor emerging risks, and build mechanisms for constant feedback and improvement. Driving analytical transformations will thereby enable companies to gain a competitive edge and stay at the forefront of digital disruption.