The fourth industrial revolution is exciting. It would be even more so if it could be more aggressively leveraged in Africa; Two of the essential components and assets in 4IR are data and data analytics. We need to know how these can be used to support the growth, development, and expansion of business in Africa.
By Keith Matthews, country manager for South Africa and sales director sub-Saharan Africa at Orange Business Services
Let’s define data and analytics and specifically how they are interpreted within the business context. Data analytics is trendy right now, but what exactly is it? When the revolution started, data was considered the “new oil” due to the volume and inherent value of both structured and unstructured data.
Every day, there is a constant flow of different data streams coming from many sources and in many formats, which creates challenges for decision-makers, engineers, scientists, and citizens. Making sense of this “big data” requires understanding, and the use of innovative technologies that can analyse and extrapolate useful insights and knowledge from them.
Exploiting big data could lead to an assortment of important collective benefits, from empowering consumers with the full landscape of information they need to make decisions that enable them to identify efficiencies, from optimisation and identifying potential risks to informing more accurate predictions of events, and many more.
But we need to work collectively to harness the power of big data to reach African goals of economic growth, education, health, clean energy, and continental innovation.
We can describe big data in “5 Vs”:
* Volume – The data is increasing exponentially;
* Velocity – Once generated, data needs to be processed in real-time;
* Variety – The type and nature of the data is heterogeneous e.g., text, images, audio, video etc;
* Veracity – The quality of data must be controlled and ensured; and
* Value – The data must be transformed into meaningful information.
To obtain this information, we must integrate the fact that each use case needs a specific and different analysis and interpretation of the data. This leads to a complex but fundamental question: “As an organisation, what do you want to achieve from this data?” Indeed, the answer to this question will structure all the parameters and decisions defined in the 5 Vs.
When implemented correctly, an information system will deliver immense value to the business. Take the simple example of a large facilities company that is managing hundreds of buildings, each hosting many workers who make use of company coffee machines. With the appropriate sensors to monitor their use, the data collected can improve efficiencies by triggering machine maintenance or consumables refilling.
Additionally, in depth information about customer behaviour and consumption habits can be used to drive consumables forecasting and upsell of rentals.
So, we see that the positive effects will be found at different levels:
* Optimise resources and improve efficiency;
* Better maintenance management (predictive analysis etc);
* Saving natural resources (water, energy etc), decrease wastage; and
* Improve quality of service for the end user.
What can data do? What can data analysis do?
Big data will become a key factor in competition, as it influences not only the efficiency of an organisation but also productivity, growth, innovation, and quality of service but only if the right enablers and data treatment processes are in place.
In a report released early in 2020, the International Data Corporation (IDC) reported that after contracting 4,9% last year, IT spending across the Middle East, Turkey, and Africa (META) would make a welcome return to growth, increasing 2,8% to $77,5-billion in 2021.
Among the biggest investors identified, we find governments, the financial sector, and telecommunication operators and suppliers.
Whether it is for epidemic tracking, crime prevention, political opinion analysis, or customer behaviour, the exploration of big data will be more and more important in our day-to-day lives. New technologies allow us to leverage more information than traditional statistics methods have previously allowed, albeit that statistical algorithms will drive the Artificial Intelligence used to make decisions with big data.
According to research by MGI and McKinsey’s Business Technology Office, leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers.
The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future, allowing faster insights and competitive advantage.
What are the essential steps to unleash the power of data in the African context?
In Africa, it is easier to get access to a mobile device than clean drinking water. So theoretically this means that data is easier to obtain than to produce clean drinking water.
With more than 900-million mobile subscriptions on the continent, this has created mountains of new information e.g. consumer spending habits including spending through social media. One can only imagine what the full potential of this data and information will be.
Across the continent, both home-grown businesses and multinational companies are turning to big data to drive their growth strategies. Data-focused start-ups are also beginning to sprout up. The IDC predicts that revenue from big data and analytics operations will increase by 11% in Africa and the Middle East this year to reach $2-billion. It forecasts that growth will remain at about that rate for the next few years.
Africa has witnessed an unprecedented rise in the volume of unstructured data
Structuring the data to gain valuable and actionable insights is a major challenge that companies and governments will be looking to address. We need a complete realisation of big data capabilities that will potentially transform our economy so that big data can extend far and wide and affect a paradigm shift in our society.
Partnerships and the ability to measure success criteria will be key to unleashing the potential of big data analytics in Africa. We must learn from tried and tested markets to develop the value from big data analytics.
We are in an era where we cannot afford to “pay school fees” for mistakes. Let’s utilise the expertise of global companies and subject matter experts.
As big data analytics and IoT is all about an ecosystem; Telcos, governments, businesses, and other stakeholders need to work closely to realise this transformation.
According to Gartner, more than half of all analytics projects fail because they aren’t completed within budget or on schedule, or because they fail to deliver the features and benefits that are agreed on at their outset.
This leads to a few questions about the implementation strategy followed. Are the analytics initiatives tied up to the business needs, metrics, or KPI’s? Is the right data available for deriving the planned insights? Is the approach correct? Is the data of good quality?
It is essential to tie business metrics or KPIs to analytics projects in order to properly monitor the ROI of an analytics initiative. Despite its potential to be a game changer, big data analytics remains underutilised by economists. Big data should be leveraged to expand the digital economy, combat corruption, and to some degree, help nations fight poverty.
It is no exaggeration to state that big data analytics is the new pillar of strength for economic decision-making. However, in Africa, the generation of big data depends largely on the telecommunications networks of each country, who in turn depend on the allocation of the necessary spectrum. So indeed, full participation from all stakeholders must set the scene for economic transformation riding the wave of big data.
What are the challenges that have yet to be overcome?
Clearly, the challenges of leveraging big data are numerous, and it is difficult to identify all the pitfalls. What is known though is that big data projects are becoming a normal part of doing business which is by no means easy.
An October 2016 report from Gartner already stated that organisations were getting stuck at the PoC stage in their big data initiatives. “Only 15% of businesses reported deploying their big data project to production, effectively unchanged from last year (14%),” the firm said.
We may conclude that organisations are facing major problems when it comes to implementing their big data strategies. This is confirmed by the IDG Enterprise 2016 Data & Analytics Research found that 90% of those surveyed reported running into challenges related to their big data projects.
Similar to most issues in life, when encountered, what do we do? We go back to the drawing board, back to basics and then, KIS (keep it simple). We need to start by improving our understanding of big data in our unique context, consider the 5 V’s, and be clear about the desired outcomes.
Choice of infrastructure
One of the obvious problems when dealing with growth, data growth, yes an obvious one, is the question of where we store and analyse all the information. “To cloud or not to cloud”, should be considered for storage, depending on the types of information and on regulation.
Another difficulty arises when the data is unstructured like documents, photos, audio, videos, and others can be difficult to treat and analyse.
To deal with the immense increase of data volumes, organisations are turning to different technologies. Today, converged and hyper converged infrastructures and software-defined storage can offer the possibility to develop a well-adapted strategy.
Often, the information obtained from the data is useful in real time only. Therefore, organisations don’t just want to store data but use this data to achieve business objectives. These goals help organisations become competitive, but may often only be achieved when the extracted insights are available as a regular information flow. To achieve this, organisations need to choose well proven analytic tools.
To develop, manage and run these applications, organisations need professionals with the right skills. This has driven up demand for big data experts, and salaries have increased dramatically as a result. Organisations are at a crossroad when it comes to this decision: recruit, or use analytics solutions “as a service”. The solution is most likely a carefully considered blend of both.
How to integrate disparate data sources?
It is very well known that big data and IoT go hand in hand and come with many disparate devices and data sources. Finding the correct platform which can encompass data flows from multiple and disparate devices and other sources may seem impossible – but in fact, there are solutions available. Organisations should take the time to analyse their needs and if necessary engage with expert consultants.
Very often organisations get similar pieces of data from different systems, and these pieces do not always match. The process of getting those different sources and data types to agree, as well as making sure the records are accurate, usable and secure, is data validation and governance.
Data governance is cited as a growing area of concern for most companies. Structuring data governance is a challenge on its own, and requires a combination of policy and technology changes. Again, the crossroad dilemma comes into play: recruit teams to oversee the data governance or look at subcontracting this function to specialists.
And, how about security?
Indeed, hacks on big data stores have become a serious concern. One of the considerations for using well established cloud providers and cloud solutions, is that they are generally leveraging their scale to deploy leading technology and resources to avoid hackers and ensure that their customers data is protected.
Last but not least – organisational resistance
Ever heard of CDO (chief digital/data officer)? This is a new emerging role within the C level, and with valid reasoning. To establish and foster organisational buy-in and capitalise on opportunities offered by big data; we will need organisational leadership. We all know that technology is not the only challenge. People are much more difficult to deal with; you can’t just switch them off or change code.
How is South Africa faring in the implementation of data and analytics strategies that drive results?
South Africa has widely adopted big data, data analytics, and BI. This is seen from the efficiency created by leveraging big data, and the advancement of the supporting infrastructures like Sigfox and LoRA networks which facilitate the collection of data. South Africa has started to realise the potential of big data and analytics, and the adoption of these technologies across all verticals will accelerate in the coming years.
Political and economic instability has led to limited IT budgets. Having said this, the use cases for IoT and big data analytics within South Africa are unlimited and will drive optimisation and lead to greater efficiencies and, most importantly, improve ROI’s. Indeed, companies and governments need to embrace this big data era as it brings great insights, innovation, better service delivery and increases competitive advantage.
It will be crucial for organisations to establish a data-driven culture and encourage knowledge sharing to develop internal capabilities.
Partnerships and collaboration with the right experts are crucial to getting the best out of big data. We should leverage the skills of companies who have done this before to benefit from the traction of this era. Moreover, this field is about innovating with a pioneering mindset. We must keep our minds open to test new ideas, get mature with the subject, and move forward, learning from our experiences.