Our Journey: From Lack Of Operational Visibility To A High-performing Organization

Nov 28, 2019

car journey

Picture yourself driving late at night on a lonely country road. The road ahead is pitch-black, there are no street lights, and you are driving without headlights. You have no idea what’s coming up on the road ahead. There could be one or more deer standing in the middle of the road. There might be a massive pothole right where your wheels will pass. But, without your headlights you’d have no way of seeing what’s coming. And no way to prepare for any action you might need to take. You’d be at the mercy of what lies ahead. 

Of course, neither you nor I would drive under such conditions without headlights. Yet this is how many factories continue to operate every day – with lack of operational visibility.

Lack of operational visibility – the push to digital transformation

This was also the modus operandi at Elisa corporate network and services business unit back in 2009.

We lacked visibility into what was happening in our customer networks, or why something was happening. As a result, it happened more than once or twice that our corporate customers lost their network connectivity and access to their business-critical applications – sometimes even for a couple of days. This meant both losing revenue and losing trust in Elisa.

To make matters worse, we were typically not the first ones to find out about our network failures. In fact, it was our customers who informed us about problems.

It was time to improve our operations and get ahead of the game.

A step by step process to gain control

That was the beginning of our digital transformation journey. Step by step, with help of data analytics, we gained visibility into our customers’ networks and services. This allowed us to transform our operations from reactive to proactive.

But, we didn’t stop there. We proceeded to prevent problems instead of just fixing them faster. This meant predicting problems based on data, attacking the problems at the root and resolving them automatically before they affected our customers.

Finally, we were driving with the headlights on.

Today, Elisa prevents 80% of the network incidents by predicting and automatically resolving them before customers are affected. Also, the number of network incidents has fallen by 70% even though we provide more services than ever before.

Elisa IndustrIQ – unlocking Elisa’s operational excellence

When Elisa started its transformation journey back in 2009, building solutions to industry manufacturers’ toughest problems were not in the plans.

However, we quickly noticed that lack of production visibility was not just our problem. It is, in fact, a problem for most manufacturers. Regardless of the industry you are working in, it is real-time, end-to-end visibility of actionable insights that allows manufacturers to proactively respond to the reality of the constant change going on in their factories.

As a result, Elisa IndustrIQ was created in 2016 with a simple idea: to leverage Elisa’s technology, people and know how to help industry manufacturers digitize their factories.

To date, Elisa IndustrIQ team has helped manufacturers to solve demanding industrial challenges. Here’s a snapshot from our fascinating industrial endeavours around the world:

P & G
With Elisa IndustrIQ, P&G is able to monitor their key KPIs and material availability across departments in real-time. The dashboards allow real-time, role-based views for all stakeholders, helping increase machine uptime, improve inventory flexibility and overall operations efficiency.

A global pharmaceutical company
With anomaly detection, Elisa IndustrIQ enables the company optimize its bioreactor process to maximize yield.

e.GO Mobile Electric Car Manufacturer
Elisa 3D Digital Factory provides real-time visibility to all production stages, helping the factory gain insights to material demand and increase operational efficiency.

factory 3d render

Elisa has reached 80% level automation in incident prevention

Today, Elisa is managing its entire mobile and fixed network infrastructures and the production of its more than 1,200 enterprise customers’ infrastructures based on predictive analytics and automation.

We have increased the level of automation gradually while expanding the use of predictive analytics and robotic process automation. Today, 80% of the network incidents are prevented – i.e., predicted, and automatically resolved, before they impact the customers. We’ve succeeded to reduce the network incidents by 70% in ten years.

As a result, today Elisa runs its networks with the same workforce it had in 2007, even though network traffic has grown twenty-fold. The network specialists, who were once fixing the network faults, are now working on automating the manual processes.

The challenge of change

Digital transformation is not a project. It is a comprehensive evolution process, which, ideally, never ends.

For Elisa, the path from the reactive management to proactive and preventive automation has involved changing processes, transforming people, and developing tools to solve the fundamental challenges.

The first step of the journey was to start monitoring of the customer network components and services. When an incident interrupted a service, a ticket was created to request engineers to start restoring the services to normal working levels.

A year later, we had automated the 24/7 network and service monitoring. When incidents occurred, relevant stakeholders received an automatic alarm. We were now able to inform our customers about the problems, and not the other way around.

The next crucial step was to focus on metrics that would help us learn and improve our processes. We established the right service-level KPIs (key performance indicators) for measuring service availability, and the time it takes to repair an error, among many other indicators. Simultaneously, we started to create a KPI monitoring culture. The technical team engaged in the big-picture business conversations to ensure they had ownership and accountability for the KPIs.

The status-quo: faster in being reactive – but not yet proactive

As we were striving for better performance, the critical enabler was the abundance of available real-time and historical data that we could turn into useful insights.  Since traditional analytics tools and human minds are not enough to detect trends and patterns from vast amounts of raw data, we created advanced analytics solutions, such as anomaly detection, to uncover patterns and trends that differed significantly from the majority of the data.

We deployed robots to monitor the network and to identify data points and abnormal events. In case of an anomaly, engineers received a notification.  Depending on the anomaly, the engineer would prioritize when it required manual intervention.

As a result, we were faster in being reactive, but not yet proactive.

Becoming proactive means addressing problems at the source

The traditional approach of identifying problems by responding to alerts based on static thresholds is not the optimal solution for today’s cloud infrastructure. With so many components in constant motion and “normal” behaviour constantly being redefined, we needed a new approach.

The only way to become proactive is to address the problems at their source. And, that’s where Artificial Intelligence comes in. We started harnessing predictive analytics and continuous machine learning to eliminate guesswork and to stop spending time hunting down problems. Instead, we applied AI algorithms that automatically determined whether a performance issue has an actual or potential impact on customers.

The incident alarms triggered by the network components are captured and solved by automation; 90% of the incidents are resolved automatically, and as many as 87% are proactively remedied before they affect customers. The number of preventative measures increased by 82% between 2011 and 2018.


Elisa continues to work to reduce the number of faults by 15% annually across its consumer and enterprise services. The optimization software is on duty around the clock, freeing up the human workforce to focus on more valuable tasks.

By harnessing data, Predictive Analytics, and algorithms, you can transform from reactive to proactive and preventive mode, and take a quantum leap ahead in manufacturing productivity and process efficiency.

Now it’s your turn to switch on your headlights – contact Elisa IndustrIQ team to jump-start your transformation journey!

How To Improve Resilience And Grow Your Business Sustainably

Unexpected disruptive events in manufacturing always interrupt normal production conditions and cause production loss. How resilient are your planning and manufacturing processes? Are you prepared to deal with the unexpected?

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