Organisations no longer compete solely on the basis of their product, size or financial capacity. Today, competitive advantage also depends on speed, adaptability and the quality of decision-making. In this context, automation and the intelligent use of data have become strategic priorities.
Automation and data are now essential for competitiveness
Today, organisations do not compete solely on the basis of a product or their size, but also on speed, adaptability and the quality of decision-making. In the current context, automation and data have become priorities because they enable operations to run more smoothly.
The main problem is not usually a lack of talent, but rather that teams spend too much time manually coordinating processes, information and systems.
The current environment demands greater productivity, faster response times and much more nuanced management of complexity. This means that any operational inefficiency carries greater weight than before. It is common to find people working at the limits of their capacity, and the growth in demand can no longer be sustained by human effort alone.
Many organisations do not have a problem with effort, but rather with operational friction. Highly capable people who could deliver significant value spend time gathering information, moving data between different tools or systems, checking statuses or chasing up tasks that could be far more systematised.
Therefore, the aim should not simply be to speed up existing tasks, but to rethink how day-to-day work flows, how value is generated, and at which points time is being wasted on steps that add no value. The real value of technology does not lie in a pilot scheme or on the surface; rather, it becomes apparent when it is integrated into the actual running of the business and into the redesign of workflows, making them more efficient, measurable and results-oriented.
In short, automation brings speed and consistency, whilst data provides visibility and insight. If both elements are combined and optimised, they enable organisations to work in a much smarter way.
The true value lies not only in saving costs, but in freeing up high-impact capacity
It depends on the stage of the project. At the outset, there is usually a fairly clear need for efficiency. This is the most tangible aspect: demonstrating that something will take less time, fail less often or require less manual intervention.
Of course, savings and cost reduction are also factors to bear in mind. They often help to justify projects and secure approval, particularly when competing for budget or priority.
However, the most powerful benefit is usually that the team regains the capacity to focus on more valuable tasks. It is not easy to measure, but it is the aspect on which the greatest focus should be placed. It is by no means about taking away work, but rather about removing routine tasks so that the team can devote itself to higher-value activities such as analysis, continuous improvement processes, decision-making and foresight.
I would highlight a few examples that are common to most companies:
- Reporting tasks. This adds value for management, particularly when it comes to decision-making. However, it should not require a team to manually review and compile information; rather, both the extraction and submission of reports should be automated. People should oversee the process, but not be part of it.
- Status tracking. Many company processes involve tracking statuses, whether for projects, requests, budgets or staff. Automation not only lightens the workload for teams, but also reduces manual errors and allows for greater control and up-to-date information.
If I had to answer the question in a single sentence, it would be this: the best project is not just the one that saves time, but the one that improves the quality of the team’s work.
Repetitive tasks are holding back productivity in many organisations
The most repetitive processes are not usually spectacular ones; rather, they often consist of many small, repeated tasks which, individually, seem manageable, but whose cumulative effect turns them into activities that create difficulties for teams.
I would divide this type of process into four categories:
Manual transfer of information
Tasks such as copying and pasting data between tools, consolidating data across systems, updating files or reports, and reviewing various sources to compile a single view.
Manual operational monitoring
Updating statuses, chasing confirmations, sending reminders, and reviewing changes, milestones or bottlenecks.
Simple classification and validation tasks
Classifying requests, incidents or emails; repetitive validations based on basic rules; data reconciliation; and checking compliance with conditions.
Low-value-added reporting
Preparing recurring reports that follow the same pattern; compiling information that is then interpreted by someone else; and spending a great deal of time building visibility rather than using and exploiting the information.
These processes and tasks are dangerous because they seem minor and their impact does not materialise all at once, so they become normalised. Collectively, they constantly drain focus, time and energy, which is detrimental to organisations.
In our department, we have implemented various solutions to mitigate this and make more efficient use of our time:
- Implementation of automated test tracking
- Automatic consolidation of operational data for dashboards
- Automatic generation of notifications and alerts for upcoming deployments
- Unified visibility of processes that were previously scattered
Precisely because these processes are frequent, repetitive and of low value, they tend to be an excellent starting point for automation.
How to identify which processes are truly suitable for automation
A task is usually a good candidate for automation when it meets a series of conditions. Here is the framework we use in our department:
- It is repeated frequently
- It follows relatively clear rules
- It consumes a significant amount of time
- It generates errors or rework when done manually
- It can be measured
- It does not require complex interpretation in each case
- Its automation has a real impact
It is important to note that:
- Not everything that is repetitive is worth automating
- Not everything that is manual is bad
- Not every complex process needs to be automated end-to-end
Just as we define a framework in positive terms, we could also identify the following as the worst candidates: those that rely heavily on:
- Highly contextual expert judgement
- Negotiation
- Empathy or relationship management
- Creativity
- Strategy
- Complex exception handling
To summarise the answer, what I want to convey is that a task is automatable when it can be clearly explained, reliably repeated and accurately measured. To achieve this, preparatory work is required to understand the process, simplify it and finally automate it.
The impact of eliminating operational friction goes far beyond simply saving time
The first impact—and also the most visible—is that the team gains time and focus. But we must not stop there; the real impact goes considerably further.
Operational impact
This translates into less time wasted, fewer manual errors, less work and rework, faster response times and greater process stability.
Impact on the team’s experience
This translates into less operational fatigue, a reduced sense of ‘putting out fires’, fewer interruptions, greater ability to concentrate and a greater sense of control over their work.
When systems aren’t properly connected, it is people who suffer the consequences and end up acting as a bridge between tools.
This leads to fragmentation of work and a drain on capacity that could otherwise be allocated to higher-value tasks.
Organisational impact
It leads to improved traceability, reduced reliance on specific individuals, greater process stability and scalability, and makes it easier to measure and improve performance, whilst enabling the anticipation of deviations or bottlenecks.
To capture the real value, these solutions must be integrated into organisations’ workflows and governance frameworks, rather than simply being deployed in isolation.
We are often afraid to eliminate low-value tasks for fear that it might be perceived as a measure that means the team works less. The team does not work less simply because it is not carrying out repetitive tasks; in fact, it works better. When you reduce operational friction, you increase the team’s actual capacity.
AI expands the scope of traditional automation
Traditional automation handles structured, rule-based tasks very well and efficiently. AI, however, broadens the range of tasks that can be accelerated because it allows us to work with less structured and more variable information.
The key lies in knowing how to apply both, and even combine them to amplify their benefits.
What does traditional automation do?
- Move data
- Change statuses
- Launch workflows
- Send notifications
- Generate reports
- Execute steps defined in the same way every time
What does artificial intelligence add?
- Interpret text
- Classify requests or incidents
- Summarise information
- Detect patterns
- Extract data from less structured content
- Suggest a next action
- Support decision-making
But here’s the key:
Traditional automation optimises execution, whilst AI also optimises understanding, classification and aspects of decision support. Organisations are reaping benefits primarily in productivity and efficiency, but also in improved insights and decision-making.
The greatest impact lies not in using technology in isolation, but in integration through comprehensive workflows that combine these capabilities.
Ultimately, AI does not replace traditional automation, but rather multiplies its impact. One better understands the input, whilst the other scales up execution. One greatly improves efficiency, whilst the other broadens the scope of what can be improved.
Telefónica’s value proposition
At Telefónica, we help businesses accelerate their digital transformation by combining artificial intelligence, automation, connectivity and advanced data analytics. Our unique capabilities integrate leading digital infrastructures, cross-sector expertise and scalable solutions to optimise processes, improve decision-making and create more efficient, secure and sustainable business models.
