{"id":2554,"date":"2022-01-05T23:43:30","date_gmt":"2022-01-05T23:43:30","guid":{"rendered":"https:\/\/datafruit.ee\/?p=2554"},"modified":"2022-01-05T23:44:16","modified_gmt":"2022-01-05T23:44:16","slug":"data-literacy-as-a-way-to-business-success","status":"publish","type":"post","link":"https:\/\/datafruit.ee\/en\/data-literacy-as-a-way-to-business-success\/","title":{"rendered":"Data literacy as a way to business success"},"content":{"rendered":"

Did you know that the global data volume, which in 2018 was 33 zettabytes (1 ZB = 10007<\/sup> GB), will amount to a whopping 175 zettabytes by 2025 according to projections? This means that in seven years, the data volume will increase as much as 430%. There is no doubt that we are living in an era of data. Every transaction or click, every move made, or sometimes even a move not made, is saved somewhere as a string of data. Today\u2019s technologies allow us to process these data and use them to formulate answers to all sorts of business problems, such as who to sell to, for which price and how to sell. However, one question remains: can we use this resource for the benefit of our business?<\/p>\n

Even though various studies have shown that data-based companies develop faster, and the efficiency of their decision processes increases, company CEOs are being held back by misconceptions relating to data projects. Let\u2019s take a closer look at them \u2013 perhaps we\u2019ll succeed in breaking a few myths.<\/p>\n

Myth No. 1 \u2013 Collecting data is enough<\/strong><\/p>\n

It is not. Data without any meaning is just, well, data. Usually, it is not in exactly the right format and ready for use right away. This is where data literacy comes into play. Data literacy is the ability to harness existing data in order to achieve the organisation\u2019s business goals, but it also means navigating modern approaches and mastering best practices. All this creates a foundation for turning data into a resource that allows the right strategic decisions to be made.<\/p>\n

The international technology research and consulting company Gartner predicts that by 2023, data literacy will have become an irreplaceable element of company value creation. In order to create additional value with the help of data, it is important to take a strategic approach. Just like many Estonian companies have already done.<\/p>\n

True, without data, there wouldn\u2019t be any use for data literacy. But let\u2019s be honest \u2013 in today\u2019s world, data is virtually everywhere. Data can be viewed as a tool, and data literacy as our ability to use this tool. In the right form and at the right time.<\/p>\n

Myth No. 2 \u2013 Data projects only belong to the sphere of IT<\/strong><\/p>\n

In today\u2019s world, every company is really a \u201cdata-based company\u201d, where every staff member should at least demonstrate basic data literacy. What\u2019s more, in the context of the digital economy, it is absolutely crucial to involve all decision-making parties in development processes. The same applies to data projects. While an IT Manager concentrates only on the technological level of processes, a Marketing Manager aims to improve the customer journey and experience, and to achieve business goals. If you leave data projects to the IT department alone, half of the equation remains unsolved, and as a result, the company\u2019s business results may also suffer. As a rule, it is the business people who lead strategic data projects that involve the whole company or organisation!\u00a0\u00a0\u00a0<\/p>\n

Myth No. 3 \u2013 Data projects are expensive <\/strong><\/p>\n

As with everything else in this world, the cost of data projects is relative. It depends on what you compare it with. For example, while production planning for one company might be a time-consuming and largely manual process, its competitors may have modernised their approach and automated the whole process. This translates into a considerable competitive drawback for the first company. Thus, in order to survive in the increasingly aggressive local and international markets, it is crucial that you learn about the opportunities that accompany the data economy.<\/p>\n

It is clear that any type of technological development and automation costs money, and any such project must be economically justified for the company. However, if there is one investment that improves your competitive advantage, significantly speeds up existing time-consuming processes or reduces costs in the long run, then it is investment in data projects.<\/p>\n

Myth No. 4 \u2013 Data projects are complicated<\/strong><\/p>\n

For a company that has not come into contact with the world of data, it all looks complicated and distant. It may seem as if only corporations such as Tesla, Boeing and Amazon engage in activities like that. In reality, for example, machine learning solutions based on algorithms \u2013 which give you timely information on things such as which clients are most likely to stop buying your services \u2013 are available to even the most \u201cordinary\u201d companies. The faster the company can react to changes in the surrounding economic environment, the better its competitive advantage, irrespective of its revenue or field of operation.<\/p>\n

People often think that data projects mean large amounts of work that goes on for years. It doesn\u2019t have to be so! Modern solutions are flexible and take into account the company\u2019s needs and possibilities. Sometimes, it doesn\u2019t even take a week to generate the first solutions to the business problem defined by the client based on the existing and available data.<\/p>\n

Myth No. 5 \u2013 Data projects are universal<\/strong><\/p>\n

Every company or organisation is unique. Every data project that starts with determining the most critical business problems is unique. To arrive at the right solutions, it is important to address the right questions, with the company\u2019s current situation, industry, goals and other factors in mind. An experienced data specialist helps to ask the right questions.<\/p>\n

In order to improve the data literacy of your employees, it is possible to organise training programmes with content, focal points and length customised according to your company\u2019s or organisation\u2019s specific needs. In those cases when simply training or a consultation is not enough, such as when collected data is not in the right format or is dispersed across different databases, the company needs a more tailor-made approach that covers the entire data project life cycle. This is where a trustworthy and experienced partner that leads you throughout the process comes into play.<\/p>\n

Data literacy as a way to business success<\/strong><\/p>\n

In today\u2019s data-driven world, it is absolutely essential to improve data literacy across the company. According to Gartner’s annual survey conducted among data managers, insufficient data literacy skills is regarded as one of the greatest obstacles on the road to business success. Data-driven companies produce data literate employees who are capable of contributing more to the organisation, thereby improving its competitive advantage. This is the strategy that can make a real difference to your company too.<\/p>\n

Modern tools and approaches help to solve a number of business problems or improve already existing solutions. Oftentimes, companies are simply not aware of these possibilities. In this case, it might be helpful to contact specialists who are experienced in managing data projects and can support your company throughout the entire process.<\/p>\n

Read more: https:\/\/datafruit.ee\/en\/training-coaching\/<\/a>. Request training or a consultation: hello@datafruit.ee<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"Did you know that the global data volume, which in 2018 was 33 zettabytes (1 ZB = 10007 GB), will amount to a whopping 175 zettabytes by 2025 according to projections? This means that in seven years, the data volume will increase as much as 430%. There is no doubt that we are living in […]","protected":false},"author":5,"featured_media":2889,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2554","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-maaratlemata"],"_links":{"self":[{"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/posts\/2554","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/comments?post=2554"}],"version-history":[{"count":2,"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/posts\/2554\/revisions"}],"predecessor-version":[{"id":2556,"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/posts\/2554\/revisions\/2556"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/media\/2889"}],"wp:attachment":[{"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/media?parent=2554"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/categories?post=2554"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/datafruit.ee\/en\/wp-json\/wp\/v2\/tags?post=2554"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}