Data Analysis and Tool Selection

Why Excel is NOT Business Intelligence

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In today's digital, customer-centric world, leaders are overwhelmed by an endless flood of information. Naturally, they are looking for ways to gain more control over and insight into their business data. Because people are creatures of habit, this data is still processed in many places using the same old tool: Excel. But Excel is not Business Intelligence.

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The use of Excel in companies usually follows the same pattern. When an analysis or report needs to be created, data is imported into Excel. Then the time-consuming processes begin: rows are copied, pasted, or deleted, data is sorted, filters are applied, columns are formatted, and so on. Users can manipulate data in countless ways, often unintentionally and without even realizing it.

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Small error, big impact
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Studies have shownthat about 88% of Excel spreadsheets contain some type of error, primarily due to manual entry. Something as minor as a misplaced decimal point or an incorrectly entered formula can ruin a company's annual financial statement or decision-making process.
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Excel spreadsheets are also frequently shared or edited collaboratively. Every person involved runs the risk of unintentionally altering the sheet further. If there is a serious error in the original document, it has extremely unpleasant consequences for the overall result. Even with locked cells or other security measures, there is always room to accidentally compound a single mistake.
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Typical Excel errors in data processing
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Flawed functions/formulas

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A single formula error can invalidate an entire spreadsheet.

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Incomplete copying

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

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Poor formatting

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When data is simply moved around, poor formatting is carried over rather than corrected.

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Hidden information

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Information can be hidden within workbooks, making it impossible to track and verify calculations.

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Data analysis requires modern BI tools

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Excel should be just 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 potential for wasted resources and errors is far too great to entrust an entire data management strategy to Microsoft Excel. Modern BI tools make reporting faster and easier by completely eliminating manual data processing. This makes reporting significantly more reliable.

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A smooth transition instead of cold turkey: four steps to moving away from Excel
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When moving away from Excel, companies should initially focus on their smaller pain points. These are easy to address and usually have fewer dependencies on other areas. Furthermore, small successes become visible more quickly, providing motivation to tackle larger data analysis projects in the long run. All the experience companies gain in pilot projects can later be easily applied to larger and more essential daily business processes. The following steps can be used to plan the transition 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? Often, the attempt is made to complete more projects than resources allow. You should start by focusing on a single subject area to achieve success within just a few days.
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To-dos
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• Select a standard business process that is easy to understand and improve
• Avoid using too many data sources at the beginning
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This also means using a business intelligence system that is easy to start with and can then be scaled to any level that makes sense for the company. A tool like Power BI is highly recommended. It is free to get started and cost-effective to roll out across the entire organization.
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The BI project should go beyond simply automating all manual business reports. A shift in entrepreneurial thinking could reveal more important questions that need answering, making the BI tool even more valuable. Once you move beyond the standard scope, you should expect to implement more extensive BI measures.

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Step 2: Requirements engineering (½ day)
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To successfully implement your first BI project in four days, your requirements must be clearly defined. Furthermore, business, outcome-based, and technical requirements must be formulated with enough clarity and precision to keep the BI project on track for success:
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To-dos
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• Business requirements: What question needs to be answered? For example: "What are the trends in the organization's monthly revenue?" or "Which product lines could benefit from more marketing budget to increase profits?"
• Outcome requirements: How should the results from the BI system be presented or communicated so that the relevant business teams can understand and act on them as quickly and easily as possible?

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Step 3: Data collection and transformation (½ day)

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Business intelligence relies on data input to generate 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 various sources. Data must be accurate from the start to prevent erroneous final results. You should regularly review the data to ensure that you are measuring and collecting the right information.

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To-dos

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• Your data sources should be able to answer the questions from Step 2. The easiest way to get started is with raw data from ERP or CRM systems, or Google Analytics data.
• Data sources are often not yet in the right format for easy and attractive visualization. Microsoft Power BI offers the ability to format data using Power Query.

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Step 4 – Creating the dashboard (1 ½ days)

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Creating a dashboard should be an intuitive process. Microsoft Power BI’s drag-and-drop functionality makes it very easy for both users and creators to build charts. A line chart can be generated in just a few clicks. If it doesn't meet your requirements, it can be deleted or replaced with a bar chart with another simple click.

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To-dos

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• Use Microsoft Power BI’s options for graphics, charts, and filters to make your dashboard as useful and engaging as possible. Dashboards can also be accessed via a standard web browser, so viewers don't need to use or download any additional plugins.
• Information design: Keep it simple and stupid! Choose appropriate charts based on common sense.

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Power BI instead of Excel: Smart decision-making with Business Intelligence

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The primary goal of a BI initiative is to transform company data into structured, analyzable information. Business Intelligence is integrated into strategic decision-making across the entire organization. Data-driven, reproducible, and consistent insights and analyses not only lead to better business decisions but also improve performance across all areas of a company.