Decision Intelligence in SMEs: A whole new Level of Data Analysis

Digital transformation in SMEs is no longer limited to manufacturing automation or streamlining administrative processes. With Digital Intelligence (DI), managers are able to use new technology to make smart business decisions.

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August 23, 2022
minutes read
Data Culture
Decision Intelligence

Digital transformation in SMEs is no longer limited to manufacturing automation or streamlining administrative processes. With Digital Intelligence (DI), SME managers are able to use new technology to make smart business decisions.

Dealing with data-driven workflows has become a matter of course for most small and medium-sized companies. Even if they don’t use the terminology, they are still in the middle of the digital transformation. New technology has permeated private and business life; technology doesn’t just make our day-to-day living easier, but it actually influences and ultimately changes our lives. It provides the basis for developing new business models, optimizes processes, saves time and costs and increasingly enhances our approach to customer acquisition and retention.

Transformation often starts with baby steps – digitizing files, automating common work steps and communicating with customers via social media channels. Following this, optimizing existing business processes is but a short distance away. The huge amount of data that is available nowadays is perfect for the organizations that have learned how to analyze it in a systematic way and can leverage the results.

Where do SMEs stand with Decision Intelligence?

Companies that are able to re-imagine services and products and can respond quickly and flexibly to new requirements will always be the leaders of the digital transformation. As well as the global players, a considerable number of SMEs are relying on Artificial Intelligence (AI) for this very purpose – no less than 16% of companies surveyed by the Fraunhofer Institute. According to reports, up until now they have used AI applications most often for data analysis, process automation or in the form of chatbots. Now, as the next logical step, SMEs are increasingly interested in the use of AI in executive positions. This is where the technology is used to generate forecasts and prepare decisions on the basis of data analyses.

How SMEs make smart choices with Decision Intelligence

Many managers are dubious about the idea of leaving decision-making to machines. But DI has nothing to do with science fiction and the disempowerment of mankind by robots! So what is DI? Thanks to AI, advanced technologies help to sort and collate large amounts of related data to draw unbiased conclusions. These results are used to design alternative solutions and courses of action that decision-makers can follow but, of course, do not have to. DI is a strategic management instrument that helps to reduce the time it takes to make decisions, to make them more transparent and consequently increase the efficiency of business processes. Read the article “Decision Intelligence - How AI is Driving Business Success” to learn even more about the role of DI and its impact on the future viability of companies.

How does Decision Intelligence support digital transformation of SMEs?

DI enables companies to gain a competitive advantage and generate higher profits. The data science potential of DI is used in a systematic way. Examples:

  • Generate customer growth and improve customer experience, including personalized product recommendations
  • Pricing, cross-selling and upselling and advertising optimization
  • Optimize supply chains and inventory management to reduce logistics costs
  • Dynamically set prices for products and services in response to market changes
  • Fraud prevention
  • Damage control and risk management
  • Use and distribution of energy resources

In all of the above use cases, AI and machine learning can be used to generate evaluations as quickly as possible from internal KPIs in combination with unstructured data such as images, audio and video files, and external criteria (e.g., weather, traffic volume) to provide recommended actions and to create forecasting models. Market trends, changes in customer behavior and potential opportunities are available in real-time and this allows you to act more quickly and with greater flexibility rather than be frustrated by delayed reaction caused by having to analyze data for weeks on end. With DI, SMEs make smart decisions faster whilst taking into account all necessary parameters and, therefore, gaining a competitive advantage by shaping, optimizing and scaling the business more efficiently.

How SMEs get started quickly and easily with DI

Most SMEs tend to shy away from introducing AI because of the unjustified and outdated fear of horrendous personnel and investment costs. This is not the case because we now have technological solutions that require neither high acquisition costs nor expensive IT experts. Instead of developing costly and complex AI systems, it makes logical sense for SMEs to turn to external Software-as-a-Service (SaaS) providers such as paretos. With the help of an AI-based SaaS tool, medium-sized companies can perform extensive data analyses without the need for the expertise of data science specialists or even prior knowledge of the use of such systems. As a result there are no additional personnel costs, although it is definitely worth investing in employee training because DI requires a new mindset among all company decision-makers – from production managers to senior executives. As part of a continuous adaptation process, they will need to re-engineer workflows, reshape organizational structures and learn how to interpret and use data analyses. Flexibility, iteration and cooperation are skills that are in demand nowadays.

It is very important to align all collected data in every department of the company with the efficiency of DI. Use the DI view (see graphic) and, as a rule of thumb, think about the use of technology for the needs of the business before considering the acquisition of the tools. So identify the business use cases first and then, and only then, decide on the models and type of data that is needed to optimize them.

For your convenience, we have summarized how to implement DI within your company in the article “10 Tips to Get Started with Decision Intelligence”.

We are the leading AI-based decision intelligence platform for effective, data-driven decision-making processes in companies. No more bad decisions!
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