Are we ready for the fourth industrial data revolution?

Wed, 12 Apr 2017 06:11:34 +0000

By Kelvin Chungu

In the previous article, I wrote about the global trends (as adapted from an EY Upside of Disruption, thought leadership publication) that are currently disrupting industries boundaries and in turn adding stress to the bottom line of many enterprises, partly enabled by the advent of mobile communications and increasing social media platforms.

It has become well understood that the mobile communications and social media platform generate significant data from willing participants and those companies that embrace this platform will find a lot of opportunity to gain insights that would be useful to them to be able to gain competitive advantage. Data from Facebook, LinkedIn, Twitter or Instagram deliver the sort of niche information about the users proclivities and demographics that can enable an innovative company to realign their offering and be better at targeting its customer’s needs. And it is yearning for willing users to mine it.

The likes and dislikes that social platforms users generate provide opportunities for companies to mine and analyze. Now to be clear, it is not just the mobile or digital platform that can generate information to analyze, there other information sources that can be harnessed, because any company that has been in operation for a while will likely have an enormous store of data waiting to be mined for valuable pieces of insight.

For instance, all records that a company keeps, which may include production records, sales and marketing statistics can be compared and matched with other data kept by a company to decipher unknown insights using reasonably priced cloud-based data analysis services which can also assist in transforming non-digital data into computer user friendly form.

And it is important to note that regardless of the size of business, new data mining tools are now available that facilitate access and analysis to take advantage of big data, and gain productively by uncovering silent patterns, relationships and other insights. Even so, many companies are embracing these tools and are now able to understand more of what motivates their customer, their supplier and perhaps their employee behavior and on that basis are able to focus on adapting their value proposition and direct their efforts accordingly.

And so as digital data increases, those companies that embrace these new data mining tools can take advantage of them to better innovate their product and service offering to meet the differing needs of their different customers groups. Of significance is that the number of companies collecting and then enhancing the information value of the data that they collect using these data mining tools is increasing and the current assessment is that those companies that digitalize and mine the enormous amounts of data being generated will continue to be a step ahead of the rest.

It is therefore important not to underestimate that this digital revolution is real and it is affecting every industry, lowering market entry costs & barriers and making it easy for a new upstart company to enter new unchartered industry sectors even as they are currently defined by another industry sector.

The information value of data analysis and mining is made even more tenable by the decreasing costs of technology that allows the examination of what we are, who we know, our location and our plans and this in turn empowers companies to be able to predict the potential customer’s social behavior.

The added advantage of these new data mining tools is that they can easily be implemented on existing systems to allow data mining capabilities to enable the analysis of the data storage systems and allow for data interrogations to answer ‘what if’ and ‘why’ questions.

This process of turning raw data into useful information is also enabled by falling technology costs and availability of new tech tools that display complex information in ways even those that are not technologically adept can appreciate.

The falling cost of the technology means that smaller companies can now begin to unlock many more insights from the data they generate by linking up the company’s data storage systems to the growing mass of data generated internally and externally.

Added to that, the convergence of social, mobile and cloud is increasingly expanding the capability by private enterprise to gather information, enter new markets, transform existing products, introduce new go to market strategies, while presenting significant challenges, such as new competition, changing customer engagement and business models.

It is therefore of growing imperative that small businesses begin to embrace the data world as significant benefits can be derived from data analytics for small businesses, particularly because of the inherent advantage that small businesses have over their big businesses in that they can act on insights quicker and more efficiently.

To buttress the information value of data, McKinsey Quarterly in their February 2017 ‘a case for digital reinvention’ offers their analysis of the implications for revenues, profits, and opportunities. That these will be dramatic and notes that as digitization penetrates more fully, it will dampen revenue and profit growth for some, particularly the lower end tranche of companies, while the top performing companies will likely capture lop-sided gains. As such they recommend bold, tightly integrated digital strategies as the biggest differentiator between companies that win and companies that don’t, and they note that the biggest payouts will go to those that initiate digital disruptions.

Their survey suggest that as digital increases economic pressure, all companies, no matter what their position on the performance curve may be, will be affected. Companies that are savvy with the data tools can then collect and use this data in order to monetize it by adapting their offering to the dictates of the information that they get. Data has evolved as a new resource that can assist in unfolding an increase in productivity.

EY in their ‘Becoming an analytics–driven organization to create value’ thought leadership research in collaboration with Nimbus Ninety noted that big data has become an invaluable tool for creating value in a business by providing a comprehensive view of market conditions, customer needs and preferences, and potential project risks and eliminate reliance on “gut feel” decision–making. They also note that Organizations must understand and embrace emerging opportunities and align products and services with changing customer needs. Additionally the research show that big data can help organizations protect value based on effective risk mitigation and compliance with ever-changing regulations and that analytics can help organizations find and measure intangible sources of value more effectively, bringing together hard facts from the balance sheet with a range of qualitative evidence, such as employee skills, customer sentiment, product innovation and geographical footprint.

The EY finding show that 81% of companies understand the importance of data for improving efficiency and business performance and that most are embarking on some kind of big data strategy. This research sheds new light on the drivers for big data adoption as (1) To understand customers better, (2) To improve products and services (3) To improve the management of existing data, (4) To create new revenue streams, (5) It is a necessity for our business model, (6) To monetize existing data, (7) to become leaner –improve internal efficiencies, (8) To find and exploit new data sources, (9) For better management of governance, risk and compliance and (10) To improve the detection and prevention of fraud

The research noted that “Understanding customers better” was the most common driver for big data projects, cited by 73% of respondents as a key area where additional value could be created. “Improving products and services” came a close second, while almost half of respondents also cited “improving the management of existing data” as a key focus.

The finding of this research noted potential widespread underinvestment in the structures, processes and controls needed to support value-driven decision–making, poor data quality and a lack of strong data governance were undermining trust in the value of data across entire organization and that while the widespread lack of specialist big data skills makes it difficult to budget and plan for big data projects and effectively calculate return on investments.

According to this EY research, the use of analytics driven by bid data to drive board-level decision making will double in the foreseeable future, it is therefore important that Companies develop strategies to harness this. Chris Mazzei, Global Chief Analytics Officer at EY, noted that Data Analytics is not a technology issue, it’s a strategy and operational issue. And as such companies ignore this imperative at their own peril.

The research above goes to show that it is becoming well acknowledged even by those that do not use data effectively that data now represents a new post-industrial era and will rule in a world where the majority will connect in real time and thus specialist big data skills will be an important highly sought after skill to provide insight into this social fulcrum. That is why institutions of learning, colleges and universities in Zambia rather than just business houses must begin to relook at their curriculum to embrace this defining new order.

Kelvin Chungu is an Associate Director in the Assurance, Advisory and business development service department of EY Zambia and can be contacted on Kelvin.Chungu@zm.ey.com