5 Myths About the Use of BI and AI Adoption

This article was originally written in 2016, and the points made back then remain even more relevant today. The observations about Business Intelligence (BI) still resonate, and now the conversation extends to Artificial Intelligence (AI). In particular, small and medium-sized enterprises (SMEs) often have similar concerns regarding the adoption of both technologies. However, implementing BI and AI is far simpler and more cost-effective than it might appear at first glance.

For years, having an ERP system and computers was no longer a competitive advantage for businesses of any size. Today, the real challenge is turning data into actionable insights to optimise processes and drive better outcomes.

It’s impossible to discuss this without mentioning BI- Business Intelligence. While it has been around for decades - I worked on BI projects in the 1990s - it is still sometimes viewed as a tool reserved for larger corporations or those with deep pockets. But the landscape has shifted. The internet, on-demand computing, and the vast availability of learning resources have made BI and AI more accessible to companies of all sizes. Let’s debunk a few common myths.

1. It’s Expensive

In the 1990s and early 2000s, BI projects did indeed require significant investment in terms of time and money. They often involved complex data warehouse structures, costly tools, and substantial hardware investments. Budgets running into millions were not uncommon.

Today, however, the story is quite different. With open-source databases like MySQL, PostgreSQL, and MongoDB, and tools like Microsoft’s Power BI (available for free), the cost of entry has dropped dramatically. Businesses can start small and scale as needed, leveraging cloud infrastructure to reduce upfront hardware costs. Cloud platforms, such as Microsoft Fabric, make it possible to integrate data from sources like Google Analytics, MailChimp, and Google BigQuery quickly and effortlessly, without the need for costly infrastructure.

2. The Company Isn’t Ready

What does it mean to be "ready" for BI or AI? Many businesses believe they need to be highly sophisticated before embarking on a BI or AI journey, but the reality is that it is not a matter about being prepared, but the need to have the information.

Businesses are already engaged in daily operational activities such as managing orders, invoicing, accounting, and sales. These processes are supported by ERPs of various kinds, which produce reports for each module. However, when it comes to strategic insights - cash flow forecasting, stock provisioning, sales performance analysis, or profitability reports - many companies still rely on Excel.

The problem with Excel is that it requires endless manual effort. Teams spend hours extracting data from various ERP reports and compiling it into spreadsheets. This manual process is not only time-consuming but also costly, and it often leads to outdated information by the time the reports are ready. BI tools automate much of this, saving both time and money.

3. It Takes Too Long to Deliver Results

Thanks to modern BI tools, creating dashboards and reports has become a far quicker and more straightforward process. While you still need to understand the basics of the tool you’re using, today’s solutions are designed for fast deployment and quick results.

The preferred approach today is to create a Minimum Viable Product (MVP) in the form of a basic dashboard or report for specific departments. From there, the system can be refined and expanded incrementally, allowing companies to start seeing results almost immediately. This agile method means businesses don’t have to wait months for a full-scale rollout—they can address pressing issues quickly and add more metrics as needed.

4. It’s Complicated

Many businesses are stuck in a cycle of copying and pasting data from ERP systems into Excel. This manual data handling not only slows things down but also limits what companies can do with their data.

A well-implemented BI solution changes this. Through automation, BI drastically reduces the time spent on data gathering and updating, freeing up employees to focus on analysis and decision-making. The tools available today, like Power BI and those integrated with Microsoft Fabric, are intuitive and user-friendly, designed to simplify rather than complicate processes.

5. It’s Always Outdated

Gone are the days when data updates were restricted to overnight batch processes. Modern BI tools, such as those available through Microsoft Fabric, allow for real-time or near-real-time data updates, enabling companies to track key metrics as they happen.

Processes that once required manual intervention, such as compiling reports on open support tickets, order queues, or cash flow, can now be automated through BI. This means businesses can access fresh, up-to-date data at any time. Integration with external data sources like Google Analytics, MailChimp, and Google BigQuery further enhances the speed and efficiency of these processes, giving SMEs a powerful tool for real-time decision-making.

6. Evolution Over Time - Extra 2024

The development of BI solutions today follows a path of continuous improvement. Instead of waiting months to implement a complete system, businesses can start with an MVP and build on it incrementally. This evolutionary approach delivers faster results, and companies can continually refine their tools based on real-world needs and feedback.

The advantage of this method is that it allows users to request new metrics and functionalities as their most immediate challenges are resolved. This ensures that the system stays relevant and evolves in tandem with the business.

Conclusion

Implementing BI (and AI) today is far simpler and more affordable than it was even a decade ago. The tools are accessible, the infrastructure is scalable, and businesses of all sizes can benefit from data-driven decision-making without the need for a massive upfront investment.

The lack of competitiveness is a direct result of making decisions without reliable information. Companies that base their strategies on outdated data or manual analysis risk missing market opportunities and responding too slowly to changes. An effective dashboard is far more than just a collection of reports - it becomes an essential tool for daily operations. Serving as a support platform for the business, it not only organises information but also provides accurate, real-time insights, enabling the company to make fast, data-driven decisions that enhance efficiency and competitiveness.