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.
'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  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.
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.
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.
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?
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!
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!
1 Total data volume worldwide 2010 - 2025 | Statista
2 Data Performance Management Is Essential To Prove Data’s ROI | Forrester
3 Matillion and IDG Survey: Data Growth is Real, and 3 Other Key Findings published January 26, 2022
4 Number of mobile devices worldwide 2020-2025 | Statista
5 Number of connected IoT devices growing 18% to 14.4 billion globally (iot-analytics.com)
6 Suomen vahvuudet, haasteet ja mahdollisuudet datatalouden rakentamisessa | The Finnish Innovation Fund Sitra
7 How To Create A Business Case For Data Quality Improvement (gartner.com)
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.