The relatively nascent adage “Data is the new oil” succinctly expresses the essence of the fourth industrial revolution. It is worth a moment to appreciate the gravity of it. We are all familiar with the manner in which the actual oil ecosystem has ‘matured’ over time, with significant socio-economic and socio-political ripple effects on the administrative entities (towns, cities, countries, economic regions, continents) around which they occur.
Arguably, it has been the case that a few individuals and entities were fortunate enough to inherit the rights to oil reserves, and consequently, those few have been enjoying, and will continue to enjoy, the vast financial and political leverage afforded them by their circumstances. And now, surely it cannot be the same case with the ‘new oil’.
It cannot be the case that a few get to enjoy the privileges afforded by data science. You need not look further than your preferred search engine, or your preferred social media platform, to witness a demonstration of the substantial advantages that data science offers. Surely SMEs need to tap into this ‘new oil’ as well. The best part of this being that they (SMEs) would have nothing to lose, given that they already produce the data, and all they need to do is extract value out of it.
The fundamental competitive edge, and leap forward, afforded by data science is the paradigm shift from retrospective business intelligence, to forward-facing actions. Data science can afford SMEs the capabilities to transform their raw data into actionable business strategies. This affordance can invariably enable them to make more efficient use of the resources at their disposal, and hence help them save and generate greater profit margins.
Of course, business intelligence has been around for some time now. However, data science does not offer typical business intelligence. Instead, it offers large-scale price optimisation, next-level segmentation, classification of customer bases, deep-diving on product profitability and building a forward-looking system that responds to insights embedded in historical data that would otherwise not be apparent without applying data science. The advantages offered by these is immense and surely, SMEs cannot pass up the opportunity to have them.
A relevant instance of evidence of this fact comes to mind. Recently, a team of four data scientists used transactional data on 20 million purchases from an auto parts distributor in the UK called Parts Alliance Group to develop a dynamic pricing engine which identified which products need to be discounted based on historical purchase patterns in order to boost sales. It is expected that the company will boost its revenues by 30 per cent, which translates to 6 million pounds (ZAR110 083 609). This was only achieved in 5 weeks!
Approximately 38 per cent of South African companies had adopted data science according to a survey conducted by EMC Corporation in 2013. However, this has not necessarily resulted in positive transformations similar to the example above. For larger companies, adoption has been relatively easy, given their vast resources and the motivation that they would certainly have plenty to gain. Unfortunately, success stories for smaller businesses have been thinner on the ground.
SMEs have heard the same hype as the big corporations. Many are keen to harness the capabilities. But they are often stuck in a nervous state of paralysis. While corporations like banks, retailers and ad agencies can easily bolt on new disciplines at scale, smaller companies don’t necessarily boast the skillsets or budgets to follow suit and they are left continuing to hammer out rear-view reports in Microsoft Excel. This is a sad reality, given that such SMEs are, to a large extent, the backbone of an economy. It stands to reason that the economy would undoubtedly benefit the most from increased data science adoption by SMEs.
The SME sector employs 47 per cent of South Africa’s workforce and contributes more than 20 per cent to the country’s gross domestic product (GDP) and pays about 6 percent of corporate taxes. So, improving the efficiency of SMEs using data science to transform them would be a plus on so many levels.
The unfortunate fact is that SMEs have tended to have a false preception that adopting and embracing data science would be difficult and different for them compared to big companies. This couldn’t be any further from the truth. The bottom line is that any business with a problem needs to find an effective solution for it and data science is merely a tool to this effect. In fact, SMEs have distinct advantages when it comes to operationalising data science based solutions.
The fact is, when a company, or industry wide, problem arises, the most elegant insights of the problem are valueless if a business is not agile enough to act on them in a timely fashion. Herein lies the distinct advantage that SMEs can realise should they use data science to obtain relevant insights. They essentially have the agility to act on data derived insights in a timely and efficient manner, given their relatively small size. It is only imperative that SMEs prioritise adopting data science.