The importance of using artificial intelligence and machine learning to create more advanced analytics and predictive decision support to drive business outcomes to the next level is growing. And as AI/ML becomes more commonplace to increase competitiveness, it will also create strong incentives for all companies to use it. The main benefits of using AI/ML models are increased efficiency and better financial results. But there are also important elements of improvement for business innovation and customer service.
Modern BI platforms have data management and advanced analytics capabilities, including the ability to run AI/ML models for predictive modeling and decision support. In addition to increased advanced functionality, the massive increase in computing power and data management capabilities has made BI platforms very powerful. However, a solid understanding of how AI/ML models work and how data is structured is still required to produce results that are reliable and transparent.
For many organizations, it is a challenge to start working with predictive decision support based on AI/ML models. Implementing predictive decision support requires skills in data structure, statistics and machine learning to develop a documented solution that delivers the expected results. It is not enough for a solution to deliver data, it must also be possible to verify that the output is accurate and can be used in the organization’s work.
Data is a powerful asset, but structuring data is becoming increasingly complex as the amount of data increases and new types of data with less inherent structure become more common. Many data sources also need data quality analysis before data is used for AI/ML models. Companies need a data strategy to manage data assets so that they can be used in analysis and facilitate the creation of the next level of business intelligence.
Companies need to invest in platforms and the development of the data science teams, and management needs to work with well-defined goals to drive a strategy around predictive models for decision support. For decision support models to be an important part of the business outcome, the models need to be well documented and transparent so that the output is quality assured.
Decision Labs can help create AI/ML models and help your organization use the advanced features of PowerBI as part of its daily operations. Decision Labs can also support companies with the design of predictive models and advanced analytics, including quality assurance and documentation. Decision Labs want to help companies unlock the power of advanced BI tools, and create a foundation for predictive decision support.
