Data analysis and tool selection

Why Excel is NOT Business Intelligence

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In today's customer-centric and digital world, managers suffer from the never-ending flood of information. Inevitably, they are looking for ways to gain more control over and understanding of their business data. As humans are creatures of habit, in many places this data is still processed using the same tool: Excel. But Excel is not business intelligence.

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The use of Excel in companies usually follows the same pattern. If an analysis or report needs to be created, data is imported into Excel. Now time-consuming processes begin: Rows are copied, pasted or deleted, data is sorted, filters are set up, columns are formatted and so on. Users can manipulate data in countless ways, even unintentionally and unnoticed by themselves.

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Small mistake, big impact
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Research has shown that around 88% of worksheets in Excel contain some kind of error, primarily due to manual input. Something as minimal as a misplaced decimal point or an incorrectly entered formula can devastate a company's financial statements or decision making.
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This is because Excel spreadsheets are also often forwarded or collaboratively edited. Each person involved runs the risk of further unintentional manipulation of the sheet. If there is a serious error in the original document, this has an extremely unpleasant effect on the overall result. Even with locked cells or other safeguards, there is still scope to inadvertently compound a single error.
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Typical Excel errors in data processing
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Faulty functions/formulas

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A formula error can invalidate an entire worksheet.

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Incomplete copying

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If not all information is copied from one worksheet and pasted into another worksheet, it will be permanently lost.  

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Poor formatting

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If data is only moved around, the bad formatting is passed on instead of being corrected

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Hidden information

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Information can be hidden in workbooks, making it impossible to track and check the calculation.

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Data analysis needs modern BI tools

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Excel should only be one of many tools in a company's BI toolbox, never the only solution. Working with Excel consumes hours, if not days, of valuable company time. The opportunities for wasted resources and errors are far too great to entrust the entire data management strategy to Microsoft Excel. Modern BI tools make reporting faster and easier by completely eliminating manual data processing. This makes reporting many times more reliable.

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Smooth transition instead of cold turkey Excel withdrawal in four steps
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When moving away from Excel, companies should initially focus on their smaller pain points. These are easy to tackle and usually have fewer dependencies on other areas. In addition, small successes become visible more quickly and motivate companies to tackle larger data analysis projects in the long term. All the experience that companies acquire in pilot projects can later be easily extended to larger and more essential processes in daily working practice. The following steps can be calculated when switching from Excel to a BI tool.

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Step 1: Small and simple milestones(½ day)
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Why do some BI projects fail? People often try to complete more projects than the possibilities allow. Initially, the focus should be on one subject area in order to achieve success after just a few days.
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ToDos
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• Selection of a standard business process that is easy to understand and improve
• Not too many data sources should be used at the beginning
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This also means that a business intelligence system must be used that is easy to start with and then scale to any BI level that makes sense for the company. A tool such as Power BI is recommended. It is free to start with, but can also be extended to the entire company at low cost.
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The BI project should go beyond the mere automation of all manual business reports. A business rethink could reveal other more important questions that need to be answered and for which the BI tool then becomes even more valuable. After that, the project leaves the standard area, so that more far-reaching BI measures must be expected.

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Step 2: Requirements engineering(½ day)
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To implement a first successful BI project in four days, the requirements should be clearly outlined. On the other hand, the business, result-related and technical requirements must be formulated clearly and precisely enough to keep the BI project on track for success:
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ToDos
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• Business requirements: What question do you want answered? For example, "What are the trends in the organization's monthly revenue?" Or: "Which product lines can use more marketing budget to achieve higher profits?"
• Result requirement: How should a result from the BI system be presented or communicated so that the business teams involved can understand and react to it as quickly and easily as possible?

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Step 3: Collection and transformation of the data(½ tag)

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Business intelligence relies on the input of data to output results and business insights. Data can come from many different sources. Some BI tools have built-in data connectors that make it easy to use data from different sources. The data should be correct from the start to avoid erroneous end results. A regular look into the data must be done regularly to make sure that the right things are being measured and collected.

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ToDos

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• The data sources should be able to answer the questions from step 2. The easiest way to get started is with raw data from ERP, CRM systems or Google Analytics data.
• The data sources often do not yet have the right format to visualize it simply and beautifully. Microsoft Power BI offers the option of formatting the data in Power Query.

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Step 4 - Creating the dashboard (1 ½ days)

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The creation of the dashboard should be approached in a playful manner. The drag & drop function of Microsoft Power BI makes it very easy for the user and creator of the dashboard to create a chart. A line chart is displayed in just a few clicks. If this does not meet the requirements, it can be deleted with a further click or replaced with a bar chart.

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ToDos

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• Use Microsoft Power BI's graph, chart and filter options to make the dashboard as useful and appealing as possible. Dashboards can also be accessed via a standard web browser, so viewers do not need to use or download an additional plugin.
• Information design: Keep it simple and stupid! The selection of suitable diagrams should be based on common sense.

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Power BI instead of Excel: Smart decision-making with business intelligence

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The main objective of a BI initiative is to transform the company's information into structured and analyzable information. Business intelligence is incorporated into strategic decision making throughout the organization. Data-driven, reconstructable, consistent insights and analysis lead not only to better business decisions, but also to improved performance across all areas of an organization.