In what direction are data-driven organizations developing right now? What kind of data expertise will be needed in the future? And what are the most interesting and important data trends for the coming years?

We interviewed eight Finnish data experts to find out what a data-driven organization looks like now and how it will develop going forward.

One of the most significant developments is that data is becoming more directly integrated into businesses, with information increasingly being used to support decision-making. For this reason, the continuous development of data understanding is also on the agendas of many organizations.

Data leaders and experts see data use becoming more commonplace as a significant future trend. In the future, information will be easily accessible and so easy to process that, alongside data analysts, so-called citizen data scientists will emerge, using data as part of their own work and adapting it to develop the customer experience.

As data becomes more accessible, automation is being developed so that human input is no longer needed to maintain basic processes or provide quick responses. Above all, it is a question of how data can be used to make even better decisions, provide positive customer experiences and encourage new innovations.

This report is divided into four sections. The first deals with the current state of the data-driven organization. The second focuses on the future of data: specifically, what trends and opportunities can be identified? The third section is a deep dive into what kind of data expertise and skills organizations will need in the coming years.

In the final section, data experts share their seven top tips for developing a data-driven organization.

According to prominent data leaders and experts, three essential and interconnected characteristics define data-driven organizations.

One of the most significant developments in recent years is that data is no longer seen only as a technological initiative, but as an integral part of a business strategy. At the same time, data is moving closer and closer to the end user, such that businesses take more and more responsibility for ownership of data and data development. This in turn requires a new way of organizing around data and therefore the creation of new roles to support common goals.

However, change cannot occur if the business value of the data is not first understood in the organization. Therefore, data understanding is actively developed as part of everyday organizational culture. In this way, decision makers can use the available information both in their own work and for the benefit of their customers. Increasing understanding within organizations starts from top management with knowledge then trickling down to the different levels of the organization.

Centralized data expertise will not disappear, but data ownership will be increasingly transferred to businesses while only the most complex technology and analytics will be developed centrally. In addition, the data management model and decision-making structures will be managed centrally but implemented at different levels of the organization.

01 / DATA IS NOT AN INDIVIDUAL PROJECT, BUT PART OF A BUSINESS STRATEGY

While in the past data was managed in separate projects, it is now an integral part of business strategy. The main focus for data today is to generate significant business value.

To make data easily accessible, a working data strategy that engages the organization through a shared state of mind is needed. It is essential that the data strategy is connected to the business strategy. The most important focus areas of the data strategy are derived from the business strategy, for example in terms of availability, accuracy, and timeliness of information. Only in this way can data answer business-relevant questions.

The technical know-how of data utilization has increasingly been transferred to business; the boundary between technology functions and business is blurring. Technology and data must be strong enablers of business strategy. Business management and the rest of the organization need to be more aware of data capabilities and the opportunities to leverage them. And equally, IT needs to better understand business needs.
Tero Miikki, UPM

Business-driven data leadership is a must for harnessing data in a high-quality and efficient way in order to create business value.
Minna Kärhä, Finnair

The point is not individual IT systems. It’s about what business challenges we want to address and what innovative data sources we can use.
Maija Hovila, KONE

Data-based services have been placed at the heart of strategy, and data quality is an integral part of quality operations. This affects the performance of every Ponsse employee and thus our customer service.
Miika Soininen, Ponsse

In a data-driven organization, information is accessible to everyone, meaning that data is processed and analyzed where it is used. That is why Finnish organizations are moving to business-driven data management, where data and analytics expertise are not only centralized, but capabilities are increasingly found within businesses.

As a consequence of digitalization, business processes are producing such huge amounts of data that traditional methods of data management and processing are insufficient and can no longer generate value. Therefore, data must be genuinely identified as a business asset and must be managed like any critical asset. As a result, responsibility naturally shifts from IT to business.
Minna Kärhä, Finnair

When data ownership is firmly rooted in a business, completely new types of roles are needed. In particular, a product owner role is needed, indicating who is responsible for developing the data and analytics portfolio and related operations.

Data is an important asset to us. More and more, we are focusing on how data could be better understood and utilized. In recent years, we have been organizing ourselves strongly around data. Each business area has a Head of Data, who is responsible for their area’s development portfolio. Under each Head of Data role, the internal data organization has evolved, forming a vision of what the information architecture of that business area is and what its most important assets are. In this way, understanding and data utilization increase all the time.
Tero Miikki, UPM

There is still a lot to be developed in product owner expertise. It is important that there is ownership on the business side for each development objective and that active management is occurring. We at Kemira are moving in this direction, and training programs are underway, but a change in culture across a global organization takes time.
Kristiina Tiilas, Kemira

At Ponsse, we have delved into questions about data ownership. Ownership is found in businesses that have the ability to say what the “true truth about data” is. Attempts have been made to understand the relationship between data ownership and process ownership, as it is important that development is collaborative.
Miika Soininen, Ponsse

Data offers powerful support for decision-making, so high-quality and easily comprehensible information must be available to decision-makers. High-quality information makes decision-making easier, and decisions are better when based on up-to-date data.

Data must support decision-making. The question is how we get people the right information at the right time so that decisions are based on the latest information rather than being made on the basis of outdated perceptions.
Maija Hovila, KONE

The traditional purchaser-provider model is moving aside. Businesses are no longer internal customers that are, for example, requesting various data reports and analytics solutions. Instead, data is an integral part of businesses, and businesses are supported in working with data. There is a tremendous difference between having data in a report or having a data scientist on your team who is capable of understanding it in a variety of ways. Therefore, data and its understanding have been more tightly integrated in business and support functions.
Antti Myllymäki, OP

03 / DATA UNDERSTANDING GROWS THROUGH CO-OPERATION

In a data-driven culture, there is currently a strong focus on expanding data understanding to all levels of the organization. Management needs to understand the potential of data, and businesses, in turn, need to understand the importance of data for competitiveness. At the same time, data experts need to better understand the business context.

This is a significant change in thinking: data competence is no longer the exclusive right of the IT department and data teams, let alone their responsibility.

Ensuring the top management understands the strategic value of data is one of the most essential steps in developing data understanding. To get the most out of data, top management needs to understand its potential.

The shift towards a data-driven organization is largely based on management’s understanding. That is why it is important to communicate about data and its possibilities. When management understands the potential of data, progress is easier.
Maija Hovila, KONE

Generating strategic value also requires new types of cooperation models within the organization. Organizations are now organizing themselves into data tribes so that specific areas of expertise – such as information architecture expertise – can be found within one tribe. In this way, the sense of community among data experts increases, but at the same time, each data tribe still works towards the strategic goals of the organization.

We have extensively focused on creating the right roles for both IT and business. Discussion via the data organization and collaboration between businesses and functions has accelerated. We have formed tribes throughout the organization – such as information architects, data scientists, and data architects – that actively advance shared capabilities and communicate about the data benefits.
Tero Miikki, UPM

Our analytics experts are organized into a tribe-like model that enables contact with business, but at the same time, collaboration between experts is even tighter. We have a “situation room” project to increase data understanding in our organization. The purpose of the situation room is to provide each team with a view of the most important performance indicators of their own operations, enable self-direction and development of operations, and develop a knowledge-driven culture.
Jarkko Levasma, Finnish Tax Administration

It is important to remember a certain kind of data trinity. It is not just an IT exercise, but a collaboration where the business owns the data and shares its focus, IT brings the tools and technologies, and data experts build the necessary solutions to meet the business’s needs using selected technologies with the chosen architecture.
Kristiina Tiilas, Kemira

A prerequisite for a more data-driven culture is that the understanding of the importance of data increases throughout the organization. Therefore, training is offered extensively at different levels, from the individual employee level to the management level. It is no longer enough to talk about what is possible with data; now we also need to talk about why this is being done and what can be achieved.

Our aim is to increase data understanding on three different levels: All employees are offered basic training to provide a basic understanding of the terms and tools available. Teams who utilize data in their work, in turn, are offered in-depth training. In addition, learning paths are created for data analytics experts in, for example, data science and data modeling.
Kristiina Tiilas, Kemira

Change is hard to come by if people don’t understand why the change is important.
Maija Hovila, KONE

The most interesting data trends of the future are that:

• data is becoming part of day-to-day operations,
• the importance of automation and forecasting is growing rapidly, and
• collected data is being transformed into deeper customer understanding, enabling the development of products and services that better meet customer needs.

In the coming years, citizen data science in particular will change organizational cultures. Everyday work on data becomes a basic skill that belongs in everyone's competence profile.

More and more people will process data in the future, but at the same time, people are no longer needed to maintain basic processes; advanced automation changes decision-making, and operations based on continuous forecasting will further accelerate data management.

01 / DATA IS BECOMING PART OF DAY-TO-DAY OPERATIONS

In knowledge-driven organizations, data has moved closer to business operations. In the future, data will no longer be separate from the rest of the organization but will have a well-established role in everyday work.

Our goal is to expand data expertise and its utilization throughout the organization. We have put a lot of time into identifying data assets and creating common data models, tools, and vocabulary. Not everyone needs to know how to code, but the goal is that, in the future, the data organization, data assets, and understanding of how a possible data idea will be driven forward will be more widely available. On the other hand, the data must be “business as usual” and used to support day-to-day operations.
Tero Miikki, UPM

As data becomes a natural part of everyday activities, citizen data science increases. The advantage of a data-driven organization is that data is used not only by professional data scientists, but also by citizen data scientists as part of their daily work. The more easily the tools can be used, the smoother the everyday use of the data will be.

Advanced self-service automation, in turn, makes it easy for business users to utilize available information in their daily work. In the future, utilizing data will be a basic skill just like using any other digital tool.

Additionally, other experts – not just analysts – must also be able to analyze data.
Jarkko Levasma, Finnish Tax Administration

Instead of a hundred people working on data every day, you need 300 people who don’t work with data as their main job, but who have sufficient data skills to do it a few days a week. By recruiting data professionals alone, the road quickly becomes more challenging, as it is difficult to find enough experts. It can be said that we are moving from a small group of professionals towards a broader citizen data scientist model.
Antti Myllymäki, OP

One of the most important tasks of data is to improve the customer experience. When information is actively collected and explored, it makes it possible to find answers to what the customer needs and what would make the customer’s life easier.

Generally, in the airline, travel, and logistics industries there is a lot of potential to utilize customer information (customer experience, expectations, behavior patterns) in the development of service planning and operations. The industry has traditionally focused on optimizing standard processes that focus on route operations, but today’s consumer expects services to run smoothly and seeks the offering that best meets their needs.
Minna Kärhä, Finnair

Information plays an essential role in understanding the factors affecting taxation. It is therefore important that sufficient information is obtained and that it is actively interpreted. It is essential that the information collected is used to improve customer insight: the information indicates what customers need and what would make their lives easier.
Jarkko Levasma, Finnish Tax Administration

Added value for the customer is generated, for example, through new types of innovations and services based on artificial intelligence. Not only do the customers get more value, but organizations also save money by harnessing data to serve them more efficiently.

By using smarter chatbots and digital assistants alone, it is possible to save several million euros a year while improving the customer experience with rapid and correct answers.
Antti Myllymäki, OP

Data has the power to make people’s lives easier and to meet our everyday needs; it can also play an important role in improving the quality of healthcare.

Data is used to do very meaningful work, both in terms of cost improvement and, above all, from the perspective of improving people’s lives. Therefore, resources need to be channelled into genuinely effective development projects, such as analytics of brain imaging or cancer spread.
Mikko Rotonen, HUS

Data has enormous untapped potential. In addition to achieving a better customer experience, data can be used to generate new insights and create various innovations that are important from the perspective of sustainability, for example.

Forests are known to be efficient carbon sinks, and the sustainable use of these valuable resources can be managed using data. Data can be used for the sustainable and simultaneously efficient utilization of forest resources by controlling the quality, quantity, and logistics of wood.
Miika Soininen, Ponsse

With the help of data, new business areas, new innovations, and completely new types of products will be developed in the future. I hope that data scientists and R&D scientists will together be able to innovate something we have not seen before.
Tero Miikki, UPM

The amount of data is increasing, and manually processing it is becoming more and more laborious. Automation, which will be developed to be even more innovative in the future, will handle an increasing amount of this work. Soon, basic processes will be managed by automation, and quick responses will be possible without brain work. When artificial intelligence handles the basic processing of data, knowledge resources are freed up for other uses.

There is no longer a present, let alone a future, in which data is only used to support human decision-making. At OP, the human role as a decision-maker in, for example, loan decisions and several other data utilization chains that require a quick response has been reduced or eliminated. For example, the implementation of personal product and service recommendations and the marketing campaigns based on them are highly automated without a person being a decision maker at every stage.
Antti Myllymäki, OP

A major question for the future is how is it possible to automate existing processes so that things can be done more wisely than before.
Maija Hovila, KONE

Hand in hand with automation goes predictive analytics, which takes the degree of data utilization to a more sophisticated level. With advanced predictions, it is possible not only to direct action but also to turn information directly into concrete and even automated actions.

Different types of forecasting have long been a necessity, and the use of forecasts has evolved significantly. The next trend in prediction and tracking is to directly change data into action. The amount of data is growing all the time, and the demands for real-time information to manage what is being done are simultaneously increasing. People do not have the time and ability to process the masses of data themselves. Therefore, we are increasingly moving to identifying phenomena from the data and creating alerts or work requests based on it, for example.
Miika Soininen, Ponsse

Self-diving cars and blockchains are here. All the necessary technology already exists. The question is, how do we make better use of the existing technologies?
Kristiina Tiilas, Kemira

Above all, the focus of the future is predictive analytics. The most important aspect is what will happen next: what would be the optimal situation for you, your organization, or society, and can corrective or protective action be taken using the data?
Mikko Rotonen, HUS

In the future, responding to requests will not only be increasingly automated but also faster. Scenarios that make it possible to predict the future at a much faster pace than today will be created using data.

Faster response to market cycles is required. Data-supported “what if” scenario thinking could go much further.
Tero Miikki, UPM

The advantage of a data-driven culture is that good-quality information is easily accessible and can more easily be processed further. Data literacy is needed so that the everyday use of data gradually becomes a basic skill for everyone. In the future, citizen data science will also expand to machine learning and advanced analytics.

As data competence is becoming more mainstream, more in-depth data knowledge is needed. Huge data resources contain hidden potential that can be leveraged by inventively combining existing data. However, innovations cannot be created without data experts who not only identify the potential of data assets but also know how to translate this potential into concrete actions.

Equally important is to integrate legacy systems and modern solutions so that good-quality, reliable information is available as a raw material to develop new insights.

Ultimately, it is a matter of harnessing data expertise to meet the real needs of customers. Alongside the ascent of technological competencies is the rise in strong service-design knowledge that enables data to be transformed into an even better customer experience.

01 / DATA LITERACY IS A MUST FOR EVERYONE

For future organizations, data literacy will be as essential as the ability to use any digital tool. As data literacy develops, everyone can make more effective use of available information as part of their own work and gain support in making better decisions.

In terms of importance, citizen data scientists are rising to the same level as professional data scientists. User-friendly analytics tools enable even more agile utilization of data. Only when data is easily accessible, easy to read, and smoothly utilized will genuine business value be created.

Utilizing data and information becomes part of every employee’s core competency: data literacy becomes a basic skill. This means that each competence profile also includes knowledge processing and utilization in the performance of one's own tasks.
Minna Kärhä, Finnair

In the future, better data literacy is needed – meaning, the ability to harness data on a daily basis.
Jarkko Levasma, Finnish Tax Administration

In the future, elements of machine learning and advanced analytics will also become part of everyday work. This big change will not happen by itself: it requires not only the right kind of tools but also that the basic user is guided and supported during the first steps.

The question is how we provide capabilities so that businesses can also independently create more and more “low code” or “self-service” entities. It’s also about scaling so that, in practice, anyone can take advantage of data, analytics, and even machine learning to get benefits out of data faster and more widely.
Tero Miikki, UPM

02 / DEEP DATA KNOWLEDGE ENABLES INNOVATION

There is a wealth of data available, and it can be combined in an innovative way. This enables new ideas, phenomena, and insights, which translate into significant customer benefits in the form of new types of products and services. For this to be possible, in-depth knowledge that takes the processing and utilization of the data to an unprecedented level is needed.

One significant trend is the arbitrary combination of data – a mashup that enables new trends to be identified more effectively. Data is available in huge quantities, and it is possible to utilize it simultaneously, so it is a question of what kind of new ideas and correlations can be found by combining the data.
Mikko Rotonen, HUS

There is a need for experts with deep knowledge of data who can technically process and wrangle various insights and new information from data.
Minna Kärhä, Finnair

The growing need for in-depth expertise is inextricably linked to technology expertise. In the future it will be critical to find ways to combine legacy systems with new solutions. It is clear that a new kind of data architecture expertise is needed in the future. In addition, there is a growing need for data engineering expertise that prepares the data and ensures the data environment is frictionless.

There is a lot of data science expertise on offer, but less common is a combined understanding of traditional IT, data analytics, and cloud services. In the future, above all, we will need data architects who understand how to integrate traditional systems with new technologies in the best possible way. It is no longer enough to pilot the newest AI feature – it must be able to be scaled and integrated into existing systems and operations.
Kristiina Tiilas, Kemira

There is a significant growing need for data engineers who understand business and for basic data processing skills. Businesses have been trained in information modeling, and expertise in general is constantly converging with business.
Miika Soininen, Ponsse

03 / DATA, TECHNOLOGY, AND SERVICE DESIGN ARE BECOMING INTERCONNECTED

In the future, data will be transformed into inventive services that genuinely benefit the user. Therefore, solutions aimed at in-depth customer understanding and data-based services require a service design approach so that information can be processed for the benefit of the individual – or, more broadly, for the benefit of society as a whole.

The technology is quite advanced, but that alone is not enough. People-centered service-design thinking is needed to transform technologies and information into problem-solving innovations.

Service-design thinking as part of data development is emphasized: the aim is to better understand what the customer journey is and whether a certain functionality will ultimately serve the customer’s need. Not everything can be based on customer understanding, but the push effect of technology must be used proactively to provide customers with useful functionalities and help.
Miika Soininen, Ponsse

The technologies are already here, and service design is already well integrated into data projects. The biggest and most challenging change is to change culture and how people work. Without a major change in human activity, data development will remain a benefit for only a small, technology-driven group.
Kristiina Tiilas, Kemira

There is an increasing need for a role that acts as a facilitator between business experts and in-depth data experts in achieving a fruitful dialogue between functions. Also, design thinking is an essential skill for this role: approaching a certain business challenge from the perspective of the customer or end user and modifying the solution to benefit them optimally.
Minna Kärhä, Finnair

By utilizing data, the customer can be better served, for example, in everyday payment situations. Let’s say you’re paying with your debit card for a €1,040 couch at a furniture store. However, the payment doesn’t go through and you wonder why. What if, at that point, the digital advisor on your mobile phone reminds you that your account's daily usage limit is currently €1,000 and asks if you want to increase your limit by a few hundred euros with one click? A digital advisor, a bank on your phone, would make your daily life a lot easier.
Antti Myllymäki, OP

01 / INTEGRATE YOUR DATA VISION INTO YOUR BUSINESS STRATEGY

To turn data into a success factor for your organization, create a clear data strategy and make it an integral part of your business.

Data-based services have been placed at the core of strategy, and data quality is an integral part of the quality of operations, which affects the performance of every Ponsse employee and thus our customer service.
Miika Soininen, Ponsse

02 / CREATE A DATA ORGANIZATION TO SUPPORT OPERATIONS

Organizational structures must support data management. Carefully organize around data and move step by step towards common practices. Ensure that data is used first and foremost to fulfil business needs.

For us, certain key roles in the data organization will, at least initially, be centralized. As data expertise grows, responsibility and ownership are rolled out as far as is possible in the business units.
Kristiina Tiilas, Kemira

03 / ENSURE DATA QUALITY AND USABILITY

Make sure your data is of high quality, reliable, and easily accessible across your organization. Invest in data management skills to improve data quality at the points where the data is created. By leveraging a centralized data platform, you ensure that data that is fragmented across the organization can be found in one place and is easier to use on all organizational levels. By leveraging a data catalog, you increase visibility in terms of what kind of data exists and where it is.

We have deployed a comprehensive data lake solution that covers data from more than two million Finns. This data lake is connected to existing patient and customer information systems, through which the obtained information is stored and organized into the data lake so that the data can be combined in near real time according to needs.
Mikko Rotonen, HUS

04 / TRANSFER DATA RESPONSIBILITIES TO BUSINESS

Generate true business value by transferring data responsibility and ownership to businesses. Support their data capability centrally, actively increase data skills, and contribute to the development of data literacy in particular. Additionally, make sure that a common “data language” is spoken throughout the organization – that is the key to a functioning data culture.

It is essential that business experts and data experts work closely together. When an organization’s data expertise is low, it makes sense to invest in a centralized team of data experts who are close to business experts and who are able to increasingly transfer data expertise to business experts.
Maija Hovila, KONE

05 / MAKE IT AS EASY AS POSSIBLE TO USE DATA

One key advantage of a truly data-driven organization is that data utilization is effortless. Make sure your data and analytics tools are easy to use and increase data understanding across all organizational levels.

In the future, data analytics tools will be so simple to use that data can be easily utilized, and it will be possible to make data-driven findings as part of everyday work.
Jarkko Levasma, Finnish Tax Administration

06 / TAKE ADVANTAGE OF AUTOMATION

Harness automation is not wasted in maintaining basic processes and rapid responses are possible without human intervention.

Smarter processes improve operational efficiency, and repetitive data collection and analysis is automated. This way, resources are transferred from recurring manual customer service tasks to tasks related to training artificial intelligence to work better, for example.
Antti Myllymäki, OP

07 / FOCUS ON PEOPLE

Data and related technologies only generate business benefits when they are focused on solving people’s everyday problems. Combine data expertise with service design thinking and put customer insight at the center of all your operations.