Only 32% of companies say they are extracting value out of their data efforts. Here is why.

Jussi Olkkonen Consulting Director, Solita

Published 16 May 2023

Reading time 5 min

Almost every company has stated in their strategies that data and analytics are core development areas both in the short and long term. Still, according to research, only 32% of companies say they are extracting real business value out of data efforts. We at Solita have learned a few key roadblocks in becoming truly data-driven, such as the unclarity of roles responsible for data development and governance, the lack of a data strategy, and having no clearly defined portfolio development programs.

Structuring the journey

From our experience, having worked with over a hundred clients in thousands of projects around data we have identified the secret sauce of success in data endeavors. The sauce consists of four main ingredients, and they are all connected. Introducing the positive cycle of data development.

The positive cycle starts from curiosity and willingness to change. The deep cooperation with technical and business people and the willingness to adopt changes in the way of working at all levels of the organisation are key to getting value out of data. As a matter of fact, none of the four key elements of the data cycle is possible without merging the technical and business development into one. There is a lot of value to be gained by improving any of the elements in the cycle and the cycle can start from any stage or dimension described here. Here is a short description of each of these four elements:

1. Constant improvement of data asset quality and accessibility.

It is the most important asset on your balance sheet. The asset should be owned by a member of the board and led as a true business asset or function similar to sales marketing, R&D, or IT. Data should not be “only” ITs headache or a siloed IT development project even though the IT professionals are the ones doing the heavy lifting. Data assets are a key competitive differentiator, and now more than ever, as a strategic asset class in for example corporate transactions.

When it comes to mergers and acquisitions, data can represent a significant part of the company value and enables core aspects of a business model. Data quality is one of the factors that determine its value, but if it is not taken care of it may also cause problems when it comes to regulations. Data quality is therefore a critical factor and its quality must be managed. This applies to all organisations. Also in the public sector well structured data asset can save a lot of time, effort, and money as shown in Istekki’s case: Three wellbeing services counties implemented a common data pool solution – for the benefit of the taxpayer.

2. Maximise automation with open operative data.

Everything that can be automated will be automated. This is an inevitable development. It affects not just cost structures but also how companies and value networks are organised. Data is not just for visualisation and better decisions, it is the most important operative enabler. For example, do you know how automated your core processes are and where the greatest potential is? Automation also means transparency and the ability to ensure better investment allocation. For example, at KONE data is used to automate the maintenance need prediction. Meaning elevators are maintained when needed not according to the calendar. Resulting optimisation in travelling, spare parts logistics and better elevator uptimes for users.

3. Dynamic offering

Products and services are not static anymore. They will increasingly consist of automated processes that will improve both cost efficiency and customer experience. Data-oriented companies are also productising internal capabilities as data products. When capabilities are productised and in open use internally and externally they enable lower costs, faster innovation, and new more agile business models. For example, in Coxa’s case surgical operations data and machine learning as a medical product is used to predict the outcome of a surgery plan helping surgeons to be better at their work.

4. Win and keep more customers with data-driven customer engagement

We live in an age of relevance. Big data-oriented giants like Amazon, Apple or Google all collect customer data and develop products and services based on predictive customer analytics. They know what we want or need in real-time in some cases before we do. They are setting the standards on how customers assume they will be served. This is quite simple: you need to have the same real-time customer understanding in all customer touchpoints to be able to serve each of your clients in the future. For example, HSL has started their journey to profile customers, automate and improve communications in order to serve citizens better.

Data-driven is about becoming business-driven

Coming back to the question why only 32% of companies see that they are extracting true business value out of data efforts. It is because they think data and analytics are a project, separate function, or an IT system. Data is a journey that starts the positive data cycle and changes fundamentally the ways of working, existing business models, and processes. It is not easy to become data-driven.

We at Solita are fortunate to be on this journey with many of our clients. A journey that makes the data and analytics statements from corporate strategy reality. Successful ones are seeing radical improvement in efficiency, automation, conversion, and innovation. They are building a substantial competitive advantage and others will have to follow. For example, Fintraffic is optimising its operation at all levels with data. Read how Fintraffic Railway is on a data journey towards the most advanced rail traffic in the world.

If you are interested to discuss more with us about extracting value out of your data please don’t hesitate to contact me at [email protected].

  1. Tech