Tools

Make your company fit for the future with Business Intelligence

Facts and figures are the basis for smart decisions in business. Business Intelligence tools can provide them for SMEs, too. Here is how you can benefit.

03.04.2019
9 minutes 9 minutes
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Table of Contents
Strategic company management sounds like a luxury for small and medium-sized enterprises (SMEs). But with a tool for Business Intelligence (BI), even small companies can make better decisions – and make their business fit for the future. In this article, you can find out what BI software can do and how you can use it.

Do you know at what time of day you generate the most turnover? Do you have a suitable new offer today for customers who shopped with you yesterday? What sales go through the tills how often? Which warehouse material is used up the fastest? How long is the time period between acquisition and ordering? Do you have more customers when it rains?

Data is an important resource

These are just some of the questions you could answer precisely with Business Intelligence. And every answer influences your balance sheet. Facts and figures are particularly important for company development within the digital transformation. In this context, it is not only the traditional key performance indicators (KPIs) that help management to better understand and manage costs and sales.

Precise, up-to-date knowledge about resources and processes within the company is also to be found in the data that is generated in the company on a daily basis. Unfortunately, it is still only on too rare occasions that it is collected and analysed. Data is a resource, like time or raw materials, that every company should use efficiently and comprehensively.

Business Intelligence makes data management intelligent

One approach that turns data into valuable information is Business Intelligence, or BI for short. This analytical information system collects, aggregates and presents data that is decisive for business success.

The reports help management to make more informed, and thus better, decisions. Corporate Groups and large companies have been using BI systems for some time. On that scale, Business Intelligence makes use of an enterprise resource planning (ERP) system, where all the key figures for the company and its processes are brought together.

In too many small and medium-sized companies, Excel tables are still used as a management information system for the collection and analysis of KPIs. Many people can work with them. That helps, but it doesn’t take you further, because it is not intelligent, not fast and not secure enough. Each manager updates the table differently and the manual data entry is subject to errors. Furthermore, this type of data management takes up a lot of time – from entering KPIs to evaluation and analysis. Links to various sources are complicated and the scope of data that can be entered is limited to one million items.

There are now many BI systems that you can understand, integrate and use even if you don’t have an IT degree or an IT department. Cloud-based services that automatically collect, link and present the relevant KPIs from existing systems via a tailored dashboard offer a simple entry point, for example. These services make it easier to get started, because they reduce costs and complexity and contribute to value creation more quickly.

Better planning and implementation with BI resources

For example, a baker can use the information from the BI tool to plan use of resources more precisely, understand demand more clearly and to provide corresponding service – including adjusting for the season. They can anticipate when customers will start buying Easter bread and how much of it they will purchase. By analysing data over a long period, they can optimise use of human resources and plan to have more staff at peak times. Marketing activities can also be measured and evaluated very differently with a precise BI analysis.

Even more Business Intelligence technical terms

Business analytics:

This term emphasises aspects of future development:

  1. Diagnosis (descriptive analysis): why did something happen?;
  2. Prognosis (predictive analysis): what will happen?; and
  3. Prescription (prescriptive analysis): what needs to be done? These are often essential elements of BI these days. Another name for this is advanced analytics.

Data warehouse:
This is a technical prerequisite for Business Intelligence. It is a transactional database that collects, stores and processes data from various sources and makes it available for analytical purposes. It is the basis for every BI solution.

Data mining:
A form of IT-supported data analysis using comprehensive algorithms and mathematical and statistical methods to uncover links, patterns and trends in collections of data. Artificial intelligence and machine learning processes are also used in this context. BI systems also make use of the principle.

 

Data-based corporate strategy and development

At the same time, Business Intelligence systems bring more knowledge into your business. They provide valuable input for strategic corporate planning and product development. Analytics make it possible to evaluate future scenarios: with predictive analytics, for example, maintenance cycles can be proactively recorded and provided. Early-warning systems that highlight critical trends can also be integrated, allowing management to react more quickly.

If you want to make use of these benefits for yourself and your company’s development, you need time and someone to develop and maintain the project, because data management is a process, not a one-off occasion.

Three steps to introduce a Business Intelligence system

What do you need to do if you want to implement a data management system?

  1. Analysis of business processes: which KPIs do we have and which ones do we need?

The quality of the initial data is decisive for the quality of the findings from Business Intelligence. The first step is an inventory that systematically and thoroughly collates all the important and interesting data, the data type and the data source. This is not about collecting all the data available, but rather that which is strategically relevant. That might also include data from external sources or data that is not yet digitally processed within the company.

  1. Create a requirements analysis: where is the data? How should it be connected? What questions should it answer?

For the analysis, all areas of the company define their expectations, which questions they want to answer with BI and what analyses and reports they would like. This understanding of the specific requirements and applications makes clear where data silos exist, what links between the departments are needed and what interfaces have to be established.

  1. Cost-benefit analysis to decide on a system: which one suits our requirements?

As with any purchasing decision, it helps to know what you need. On the one hand, this includes functional requirements such as ad hoc and real-time analyses, the option of your own enquiries (self-service BI), dashboard adjustments for different user groups and flexibility in scaling data quantities, interfaces and analyses. On the other hand, it includes governance and security requirements, service and support wishes and the budget available. A personal presentation by the provider and a test run are also options to help you select the right product.

BI providers: from big and strong to small and flexible

Even start-ups use BI to display, monitor and manage their processes in KPIs at an early stage. So there is no company too small to make use of the benefits, although there can be solutions that are too big. But that is becoming less and less the case. The major providers such as IBM, Microsoft, SAP and Oracle also offer small solutions that work well for companies with 20, 50 or 100 employees.

There are now also many new, small providers with special BI solutions such as MicroStrategy and Tableau software, as well as open-source providers, including BIRT Qlik, Knime and Knowage. The software itself costs nothing in those cases, but the set-up and orientation take time. There is even a free starter package for Power BI from Microsoft.

Slow to begin with, but secure

Business Intelligence is not available as a plug-and-play solution. The change from the Excel world to analytical reporting means changing your way of working. In order to ensure you don’t fail to meet expectations, the introduction should take place in phases. In other words, don’t integrate everything at once and offer all functions immediately, but rather increase the complexity gradually.

As a first step, instead of Excel tables, interactive reports presented graphically could help users get used to the new possibilities, for example. It is also advisable to train employees at an early stage. Training with the new tool supports practical implementation.

Check, adjust and expand regularly

Digitalisation is always an ongoing process. New data to be collected is generated every day within a company. New sources of data that you want to use appear. Over the course of time, new questions arise that can only be answered with new formulas and connections. Everything develops further, which means Business Intelligence and analytics need to be continuously maintained and expanded. Three simple questions can help with this process: are there new sources that are important for our business? How about new questions? And new interfaces?

How data as a resource changes companies

Investment in Business Intelligence is and will remain considerable. If not in budget terms, then in terms of effort, because the path from the idea to implementation is a lot of work. But once you are aware of how important data as a resource is for company success, you will recognise the opportunities and use the instrument in a sensible way. In this context, it is not all about numbers, graphics can also lead you astray. We always have to think for ourselves and view what the data is telling us from a critical standpoint.

This means Business Intelligence also becomes a cultural topic. The data does not spit out findings of its own accord. It is our questions that turn the data analyses into interesting findings. Anyone who wants to use BI will, sooner or later, also have data management and a data strategy, and will work in a data-driven way – whether they bake bread, provide care services or fix drains.

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