noun_Email_707352 noun_917542_cc Map point Play Untitled Retweet Group 3 Fill 1

Data as an Enabler part 1: Finding the purpose for data

Why still talk about data? The answer is clear – there is so much to be developed when you look at projected value growth. It is time to give data a purpose, writes Kirsi Linke.

Kirsi Linke / October 27, 2022

In the first blog of this series, Kirsi talks about the underuse of the massive amount of data in organizations.

To make change, data, IT, and businesspeople need to cooperate, define a purpose, and decide on tools and processes. This blog series guides you to do it.


'It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.'

- Sherlock Holmes in A Scandal in Bohemia

Lucky us, contrary to Sherlock, we do have data! Statista Research Department recently stated in a study that the total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, from 64.2 zettabytes in 2020 to more than 180 zettabytes in 2025 (source 1). That is 180 x 1,000,000,000,000,000,000,000 [1021] bytes of data at our disposal.

This means that we live and operate in a complex ecosystem, where interconnected internal and external systems, operators, and operations create networks, in which the number of data sources is rapidly increasing. To navigate one’s way to the correct data source is challenging. Evaluating the accuracy of data might well be a mission impossible for an individual user.

On many occasions we are still using our time hunting for information, finding and correcting errors, and looking for corroborating sources of information to replace those they do not trust. Forrester (source 2) reports that nearly one-third of analysts spend more than 40 percent of their time vetting and validating their analytics data before it can be used for strategic decision-making. It's unbearable in the long term if the search for data continues to be a time-consuming, laborious treasure hunt requiring specialized skills.

Have you ever counted how many data sources you use daily in your work to make decisions?

According to Matillion and IDG (source 3), the mean number of data sources per organization is 400. More than 20 percent of companies surveyed were drawing from 1,000 or more data sources.
Also, the data itself is changing along with locations where data is stored. We do not store and consume only structured data in SQL databases and have point-to-point integrations between them, but we do it in almost 15 billion mobile devices (source 4), estimated 14.4 billion connected IoT devices (source 5), and on websites, social media, and other platforms.

And we are rapidly moving from structured data to unstructured such as MS Office, pdf and other documents, emails, text and instant messages, images, videos, technical log, xml, and Json files and so on. IDC predicts that 80% of global data will be unstructured by 2025.

Figure 1: An organization and individuals navigate in a complex data ecosystem. Sometimes, people are not aware of the data they have and how to use it in everyday decision-making. In some cases, data is even seen as a necessary evil, just needed for mandatory, regulatory reporting instead of an enabler for anything productive or new.


No purpose, no benefits

After describing the situation with data, it is reasonable to ask what one’s organization has achieved with data.

When we look at figures, we see that we underscore in Finland. The projected value growth of the data market is modest in relation to our digital capabilities, the business conditions based on digital technologies and key reference countries. Sweden and the Netherlands are expected to double the value of their data markets to EUR 7–8 billion by 2025, while our forecast as nation remains below EUR 1.5 billion (source 6).

Why do we really lack behind? I see two reasons.

  1. Data investments are isolated one-off initiatives, not triggered by the business per se, and therefore fail to create tangible long-term benefit to the business.
  2. The meaning of data – its purpose in the business context – is unclear, and organizations struggle to justify the investment. No investment, no return.

I have seen that organizations often fail in communication, as finding the common vocabulary over data is not easy. People approaching data from technology point of view fail to sell the benefits in the language that the business stakeholders can relate to. Also, it’s fairly common that the organization has a business problem that could be solved with data, but they lack the required data expertise, or an interpreter who is able to build a bridge between business context, data content, technologies, and the people involved.

Data should be treated as an asset like anything that has economic value to a business. It must have an understandable purpose for its existence, and in order for it to be productive it needs to be targeted with investment, maintenance, and development.

Organizations believe poor data quality to be responsible for an average of $15 million per year in losses (source 5). Possible reasons for this vary; data is not managed like other assets in an organization, it does not have a dedicated owner, no one is responsible for its accuracy, availability, and maintenance. Even simple poor data entry practices, for example allowing duplicates to be created, cause poor data.

Still, I have high hopes as many of our customers and other actors in our society are actively taking part in discussions around data, engaging themselves with data development initiatives. They are taking concrete steps to improve data literacy in their organization, enabling data to move closer to the end user. Businesses are taking more responsibility for ownership of data and data development.

We made a finding in our Data x Business report (source 8) that one of the significant recent developments is that data is no longer seen as a pure technological initiative, but as an integral part of a business strategy. However, change cannot occur if the business value of the data is not understood in the organization.

How is the current state in your organization?

Figure 2: Data strategy is derived from the business strategy.



Value from data - the whole is greater than the sum of its parts

A big question is left; how do we ensure that we get value from data? We need to change the way we work with data. It means different things to different organizations.

According to my experience, one of the most important things delves down to tight cooperation between data, IT, and businesspeople. We need to find a common understanding that data is an essential part of business, not a separate initiative.

Imagine that all stakeholders sit in the same table and understand each other.

To continue, the separation of the useful information from the vast amounts of data, verification of its accuracy, and its timely correct transfer in a secure way, is only possible if we know the people, cross-functional processes, and systems that produce the data in the first place and can also prevent it from flowing. We also need to understand how the systems are used and what are the interdependencies between the systems.

We need data literate people with data expertise at various levels of the organization. We need a data management model and decision-making structures established along with the right tools. In addition, we need experts for the advanced technologies that enable data usage. We need to raise data awareness.

And most importantly we need a purpose for the data, and the data itself needs to fit for the purpose!

Figure 3: Creating value from data requires teamwork, where the players are humans and machines. Data needs doers and they need tools to refine data into useful information. Value creation requires cooperation between and across different business functions. To achieve purposeful data and to have the data as a real enabler for our businesses, we need solutions, ways of working, and guidelines for all elements shown in the figure.


Data as an Enabler blog series

In this blog series, me and my colleagues will provide perspectives to understand data as an enabler for digital business. We hope to give something interesting to ponder, helping you to conquer challenges and find new opportunities in data. How to identify what purposeful data for your business is? What capabilities and tools are needed to capitalize on it? How to get data, IT and businesspeople to cooperate? How to derive value from your organization's most valuable, yet too often neglected asset, data?

In the next blog, we will delve into three forms of data ingrained in modern business applications: structured, semi-structured and unstructured and suitable solutions to balance it out. Stay tuned!

We at Tietoevry Create are experts in breaking information silos and bridging the gap between strategy and implementation. Our services span from business advisory and data architecture design to agile data development and operations ensuring value creation from data.
If you want to get your data in order and say goodbye to data silos, do not hesitate to reach out.

Our team is ready to help!

Kirsi Linke
Senior Data Architect, Tietoevry Create

Kirsi is a business-savvy data consultant who is infinitely interested in the cooperation between people, systems, and machines. She helps organizations to turn data into impactful insights and concrete actions. Advocate of lean and agile practices, she believes that ways of working, and our job satisfaction can be improved by good enterprise and data architecture and intelligent solutions combining human and artificial intelligence.

Share on Facebook Tweet Share on LinkedIn