The hidden productivity tax sitting inside your business

Research released by Altron Digital Business in 2026 found that employees in South Africa's financial services sector lose an average of 76 minutes a week to technology disruptions, equivalent to 7.6 working days a year. Across 1,000 employees, technology-related friction was estimated to cost organisations between R3.2m and R30m annually.

And that is only part of the problem.

Inside many organisations, employees spend hours recreating presentations, searching for approved material, reformatting documents and producing different versions of work that already exists.

This creates a hidden productivity tax, paid every day through duplicated work, unnecessary administrative steps, inconsistent content and employee frustration.

More technology, but where is the return?

The rapid adoption of artificial intelligence is making this problem more urgent.

PwC's 2025 Africa Workforce Hopes and Fears Survey found that 64% of employees surveyed across five African countries had used AI at work during the preceding year, compared with 54% globally.

African workers are embracing new technology, but that does not automatically mean businesses are becoming more productive.

A company might invest in AI-powered content creation tools while employees continue rebuilding presentations from scratch. It might introduce automation while retaining unnecessary approval processes, or provide collaboration software while departments continue emailing multiple versions of the same document.

The technology is available, but the anticipated productivity improvement may never materialise.

For business leaders questioning whether their growing technology investments are delivering meaningful returns, this disconnect is becoming increasingly difficult to ignore.

The mistake is to measure technology adoption rather than business performance.

The number of licences purchased, employees trained or AI tools deployed tells management little about whether work is actually being completed faster, more accurately or at a lower cost.

The cost of doing the same work twice

Content creation offers a particularly clear illustration of the problem.

What was once largely the responsibility of marketing teams is now part of everyday work across almost every business function.

Sales teams create proposals. Human resources departments produce training material. Executives prepare presentations and reports. Regional offices create material for their customers.

When these activities are poorly coordinated, duplication becomes inevitable.

Employees recreate material because they cannot find existing versions. Brand teams correct inconsistent logos and layouts. Managers approve changes that add little value.

Consider a business with 200 employees involved in creating presentations, reports or customer-facing material. If each wastes just 30 minutes a week duplicating work or correcting avoidable mistakes, that amounts to 100 working hours lost every week, or 5,200 hours over a year.

This illustrative calculation shows how quickly small inefficiencies accumulate.

More importantly, time spent recreating existing work cannot be spent serving customers, developing new business or improving products.

Stop buying solutions before identifying the problem

One of the biggest mistakes organisations make is approaching productivity improvement as a software purchasing exercise.

They identify an attractive platform, roll it out to employees and assume the benefits will follow.

A more effective approach begins with the work itself.

Where are employees losing time? Which processes are being repeated? Where are approvals slowing delivery? Which existing systems are underused?

These questions help distinguish between problems requiring new technology and those that can be solved by improving existing tools and processes.

This is the approach Learning Curve takes when working with organisations: identifying operational inefficiencies, determining which technologies are appropriate, and helping businesses implement them through the right configuration, governance and practical training.

The distinction matters because technology alone rarely fixes a poorly designed process. Automating an inefficient workflow can simply mean doing the wrong thing faster.

Adoption is a business process

Successful technology adoption begins before employees receive their login details.

Organisations must understand which business functions will benefit, how new technology fits into existing processes and what employees need to do differently.

Consider a platform such as Canva. Employees may already use it independently to create presentations, training material and internal communications.

That familiarity is valuable, but it can conceal fragmentation. Employees may use separate accounts, outdated brand assets or content that cannot easily be shared or reused.

Connecting users, establishing shared resources and providing role-specific training can turn individual use into a coordinated business capability.

The same applies to AI and automation.

Training should reflect actual responsibilities. Sales teams need to produce proposals faster. Communications teams need to maintain brand consistency. Finance teams need to reduce repetitive administration.

Without this connection to everyday work, technology adoption risks becoming an expensive training exercise.

Measure outcomes, not enthusiasm

As businesses become more demanding about technology returns, productivity measurement must move beyond vague promises of efficiency.

Start by establishing a baseline.

How long does a sales proposal currently take? How many revisions does a presentation require? How much time does finance spend processing invoices?

Then measure whether those numbers improve.

For sales teams, relevant measures include turnaround times, error rates and conversion. For finance, processing costs and accuracy. For marketing, content production times and revisions.

The calculation must also include implementation, licensing, integration, training and support costs.

Importantly, hours saved do not automatically translate into financial savings. The real return depends on whether the business uses that capacity to reduce costs, increase output, improve service or generate revenue.

A technology investment that saves an employee an hour a week may be useful. One that allows an entire department to serve more customers without increasing headcount could be transformational.

Start with the work, not the software

For African businesses facing sustained cost pressure, improving productivity without continuously adding technology deserves serious attention.

Instead of asking which platform to buy, leaders should identify where resources are being wasted. Instead of measuring AI adoption, they should measure whether AI improves business performance.

The organisations that benefit most from technology are not necessarily those with the most tools. They are those that understand where value is being lost, address the causes and measure the results.

Until then, the hidden productivity tax will continue to be paid, one duplicated presentation, unnecessary approval and underused software licence at a time.