Data: A tool for business growth
Eniola Moronfolu, a digital transformation professional and Mara Mentor, who helps businesses make effective and efficient use of digital tools and technology to understand, respond to and exceed customer expectation, shares insights on how and why companies need to invest more in data capturing and analysis, as well as how acting on data insights drives growth.
“In God we trust; all others must bring data,” says W. Edward Deming, while cementing the invaluable place of data in modern day business operations. This is not fun. It is a huge and endless record of files, facts and figures. It is that flavorless residue most businesses throw away.
However, no matter how mundane data may seem, it is priceless. Data is an aggregate of individual and collective experiences with great insights. Everything a person does is valuable data. And with it, businesses cannot only predict customer needs, they could surpass expectations. Hence, to say data is the most valuable tool for business growth is an understatement. In fact, if cash flow is the life of a business, data is steroids!
But in Africa, there is an assumption that businesses do not generate data. As a result, data paucity is a reality on the continent. This is false. It is also unrealistic. Every business, small or big, generates data in one way or the other. Every activity within a business – every purchase, complain, payment, return – all constitute data. The problem, however, lies in the inability of businesses to effectively capture, analyse, and use the data.
From Data to Money
It is quite disturbing to find companies sitting on a massive amount of data and not leveraging it. One of the worse things that can happen to a business is not being able to turn data into money. This is happening in a lot of African businesses. From telecoms companies to financial institutions, ecommerce and retail, among others, most businesses are guilty of this.
The truth is, for businesses to thrive in a digital world, investment must be made not only to capture data, but to analyse and secure actionable insights. This can be as simple as looking through past purchase records to understanding the behavior of customers; changes that have occurred, and how their expectations have become either simpler or more complex. Also, setting up focus group activities and studying how customers use your product – what features make them frown, smile, makes them confused (this is particularly useful for businesses whose products are in pilot stage), among others,–could go a long way to revealing crucial insights on customer behavior.
Data is Useful for Every Part of Business
Data makes a company tick. While a company’s products team needs data to improve on the current product and services, its sales team thrives on data for go-to-market strategies and expansion. Marketing also needs data to measure the performance of current marketing mix and optimise it across all marketing vehicles and other touch points. Human resource managers need to know which passive candidate will be a good fit for an organisation and which employee is likely to make a move in the next three to six months. Data helps with that. Data helps a business stay ready, anticipate and get ahead of competition.
For businesses considering data-driven growth strategies, a good place to start is answering the ‘WHY’ question: why are we capturing data? What problem are we trying to solve with data? What would we use it for? Do we want to efficiently predict and effectively meet and surpass customer expectations? Are we trying to efficiently predict and effectively meet and surpass customer expectation? Do we want to identify other business opportunities and improve our business model?
Having a good idea of the ‘WHY’ helps in answering the ‘HOW’. What data points do we need to capture? How do we capture and analyse the data? What tools should we use for analysis? However, there must be a clear objective for data gathering, otherwise the wealth of insights data analysis could bring would be just a dream.
Finally, to paraphrase Michael Lewis in his book, ‘Moneyball: The Art of Winning an Unfair Game’, people operate with beliefs and biases, to the extent that you can eliminate both and replace them with data, you gain clear advantage. In context, decision makers, sometimes, tend to use insights from already analysed data to ‘confirm’ assumptions. They ‘panel-beat’ and twist insights to favour their beliefs. Such practices are wrong. Decision makers must not allow prejudices and biases to interfere with the data-driven decision-making process.
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