012 Next steps from data theory to practical change
12 December 2024
014 Data silos and their impact on company performance
15 December 2024

013 The more tools, the more efficient the business

At first glance, it may seem that more digital tools lead to greater efficiency. In practice, however, this is not the case. With each new solution, whether it’s a cloud service, a legacy system, or another Excel report, a company adds another layer to its digital landscape – a layer that is often not integrated with the rest (Fig. 2.1-1).

Data is like coal or oil: it takes years to build up, compacted under layers of chaos, errors, unstructured processes and forgotten formats. To extract truly useful information from it, companies must literally wade through layers of outdated solutions and digital noise.

Grafik 13
Fig.‎ 2.1-1 Divergent data form compartmentalized layers – even “golden” insights are lost in geologic rocks of systemic complexity.

Every new application leaves behind a trail: a file, a table, or a whole isolated “silo” on the server. One layer is clay (outdated and forgotten data), another is sand (disparate tables and reports), and the third is granite (closed proprietary formats that cannot be integrated). Over time, a company’s digital environment increasingly resembles a reservoir of uncontrolled information accumulation, where value is lost deep within the company’s servers.

With each new project and each new system, not only the infrastructure becomes more complex, but also the path to useful quality data. Getting to the valuable “rock” requires deep cleansing, structuring information, “chunking” it, grouping it into meaningful pieces, and extracting strategically important insights through analytics and data modeling.

Data is a valuable thing, and it will last longer than the systems [that process the data] themselves (GoodReads, “Tim Berners-Lee,”).

– Tim Berners-Lee, father of the World Wide Web and creator of the first Web site

Before data can become a “thing of value” and a reliable basis for decision-making, it must be thoroughly pre-processed. It is proper preprocessing that turns disparate data into structured experience, useful information humus, which then becomes a forecasting and optimization tool.

There is a misconception that you need perfectly clean data to start analyzing, but in practice, being able to work with dirty data is an essential part of the process.

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Рисунок 2
Fig.‎ 2.1-2 Data is the root system and foundation of business, which in turn is based on decision-making processes.

As technology continues to advance, your business must also move forward and learn how to create value from data. Just as oil and coal companies are building the infrastructure to extract minerals, so too must businesses learn how to manage the flow of new information on their own servers and extract valuable insights from unused, unformatted and outdated data, turning it into a strategic resource.

Creating fields (data warehouses) is the first step. Even the most powerful tools don’t solve the problem of data isolation and multi-format data if companies continue to operate in siloed systems. When data exists separately from each other, without intersecting and sharing information, businesses face a “data silo” effect. Instead of a single, consistent infrastructure, companies are forced to spend resources on merging and synchronizing data.

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013 The more tools, the more efficient the business
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