Three data and analytics predictions for 2022

By Jacques du Preez, CEO at Intellinexus.

Johannesburg, 07 Feb 2022
Read time 5min 20sec

The ability to make fast, accurate decisions over every aspect of the business was arguably one of the most powerful business capabilities of 2021.

Companies that can eliminate uncertainty by drawing real-time insights over every aspect of its operations and using the insights to make quick, accurate decisions are far better equipped to steer the business through stormy waters.

And with the world still in a state of heightened uncertainty, with a constrained global supply chain and the ever-present risk of a new strain of COVID-19 (or even some as-yet unknown wild card event), we are in for a bumpy 2022.

This puts greater pressure on companies’ data and analytics strategies. Without access to accurate, complete data in a timely manner and high levels of trust in the insights drawn from that data, companies will not be able to build a culture of data-driven decision-making.

What are the forces likely to shape the manner in which companies approach and execute their data and analytics strategies in 2022?

My three predictions are:

Prediction 1: The rise of the niche player

As businesses demand more from their data and analytics landscapes, their overall data architecture is under pressure to deliver to changing customer needs.

And while there are obvious benefits to acquiring technology tools and solutions for a broad spectrum of business applications from a single vendor – cost-efficiencies, single point of contact, easier management of SLAs – the rise of a new breed of niche technology provider is ending the dominance of bundled solutions.

Bundled data and analytics solutions have been overtaken in quality and innovation by a new breed of niche technology providers that have addressed the pitfalls and shortcomings of bundled mega-vendor offerings.

These niche players have a focused approach to their products and capabilities that seeks to solve specific problems better than the larger, bundled vendors.

For example, while bundled data solutions may offer data acquisition and ingestion capabilities, it often falls short of expectations in terms of its velocity or ability to deal with complexity.

In contrast, niche technologies have become so good at solving specific problems along the data and analytics value chain that companies now have the option to integrate a broad spectrum of best-of-breed technologies that combine to bring their digital and business transformation strategies to life.

Expect niche technologies to challenge legacy mega-vendors through modernised solutions that offer lower costs, greater performance and scalability benefits.

Prediction 2: Data protection, security and compliance will pose major challenges

Companies around the world are fighting off a tidal wave of cyber attacks that seek to bring their operations to a grinding halt and cause massive financial losses.

A recent report into ransomware attacks found that eight out of 10 companies have suffered a ransomware attack in the past two years. Large enterprises were hit by nearly 10 000 ransomware attacks over a two-year period – averaging more than 13 a day.

The situation is so dire that the US Department of Justice decided in 2021 that investigations into ransomware will be considered as important as investigations into terrorism.

Last year, an Interpol report revealed that South Africa experienced 230 million threat detections in one year, with an estimated 577 malware attacks every hour.

New data protection and privacy regulations – such as POPIA in South Africa and Kenya's Data Protection Act – compound the pressure on companies to protect sensitive data.

While regulatory compliance has driven a positive trend of improvements in data protection and privacy, more must be done to protect the integrity of company data to allow for true data-driven decision-making.

If the data that business leaders use to make decisions about the company becomes corrupted, or it is unavailable due to a cyber attack, the company loses its overall agility and suffers sub-optimal decision-making powers.

And with employees working in remote or hybrid environments demanding access "anywhere, anytime", companies have never been more vulnerable.

For companies to achieve true data-driven decision-making capabilities, data protection and data governance will have to feature highly on the corporate agenda in 2022.

Prediction 3: Focus shifts away from 'big data' to 'right data'

Big data is big business. Global spending on big data analytics passed $180 billion in 2019, and is expected to reach $274.3 billion this year.

It's easy to understand why.

With the amount of structured and especially unstructured data most companies have at their disposal, the impulse is to ingest as much of it as possible and then apply analytics to generate useful insights.

But this can lead to poor decision-making. For example, if the data you are ingesting is incomplete or inaccurate, any conclusions you come to based on that data are bound to be incorrect. You simply can't make good decisions with poor data.

And you shouldn't try. An IBM study from six years ago found poor data costs US companies $3.1 trillion per year.

Considering the pace at which the world has digitised, and the uncertainty created by the pandemic, it is likely that this number – and the resultant risk to companies – is now considerably greater.

That's why companies will focus more on building 'right data' capabilities that can support the execution of key decision-making processes that advance the overall business strategy.

A right data strategy requires that data is ingested from suitable and dependable sources, with a focus on covering all vital business processes, from procurement to HR to sales.

Companies must determine the speed at which they need different types of insights – for example, daily logistics reports and weekly sales reports – and ensure their data architecture can support this.

And to bring a right data strategy to life, business leaders will need to build a data culture where every business user feels empowered to make decisions using that data.