“It sounds too complicated.”
“It will be too expensive.”
“We can do it manually.”
Over the years, I’ve heard dozens of excuses from decision-makers who are nervous about taking the dive into Business Intelligence (BI). But as any data scientist will tell you, these fears are almost always overblown, and the benefits of BI far outweigh the challenges.
In this short article I’ll explore some of the most common BI myths.
1. BI is about making reporting more efficient
Reporting is, indeed, a very important aspect of BI. Internal and external reporting requirements for organisations are steadily increasing. But Business Intelligence isn’t about sending reports back and forth.
BI is about giving the users the tools and resources that will enable them to get the right information at the right time.
Even in 2021, there are people who block out their calendars for two weeks or more for “reporting month”. This is a very poor use of time, as these data experts (who no doubt know their organisations very well) could be using their knowledge and skills to do something more valuable such as identifying processes for improvement. Compare the cost of this wasted time and wasted opportunity with the cost of implementing effective BI.
Integrated Business intelligence means having the tools and resources in place so that when reporting day comes, a report can be automatically generated. But BI isn’t just about making reporting more efficient; there are a lot of bonus outcomes such as better insights and becoming a more data-driven organisation in terms of decision-making.
2. We just need better data visualization
Data visualisation is a fantastic tool to help interpret and present data, but in itself it is only a front-end process and will often be less than half of what you actually need. BI is an end-to-end process that involves collecting, processing, storing and interactively presenting data.
A front-end tool is no good without an effective back end, yet many organisations make the mistake of purchasing a front-end tool and expecting insights to magically happen. While the solution may seem fine when they launch, it will not be maintainable over time as holes in the architecture become apparent.
Getting the back-end right first isn’t as scary as it may sound. Noria’s one-stop-BI-box solution has been designed to create a reliable back end that enables valuable front-end insights.
3. Business Intelligence requires expensive datawarehousing
Ten to fifteen years ago, BI and datawarehousing were synonymous. But many modern BI reference architectures skip the datawarehouse completely, or have an altered version of the traditional architecture.
Datawarehouses are commonly used for combining data from several sources, providing a single source of truth, tracking historical changes and optimising end-user query performance. However, modern BI platforms provide solutions for these uses at a much lower cost. Many BI use-cases can operate very well without a datawarehouse.
In short, don’t let the lack of a datawarehouse stop you from pursuing BI.
4. BI is only for large organizations
The rise of hosted BI and SaaS has made BI tools and technology affordable and scalable, and most BI tools today do not require any extensive end-user training or specific skill.
BI is low-effort and high-value, not complicated to use, and does not require a huge budget. This means that even start-ups can start out the right way using BI instead of waiting until they are large enough.
5. BI is an IT job
As with any IT project, a proper BI project requires collaboration between IT and business. However, business knowledge and an understanding of the sector are far more important than programming skills when it comes to implementation. This is why industry knowledge and business understanding are critical factors you need to consider when choosing a BI implementation partner.
Don’t worry too much about end-user training. If your staff can use Excel that’s more than enough – in fact, BI tools are often easier to use than Excel. Business users will see these benefits directly and adapt to this new way of working.
6. More data = better BI
Data quality over data quantity! Make sure it’s accessible, accurate, reliable and interactive – and don’t let a perceived “lack of big data” hold you back from BI.
Most companies don’t need big data; they need the right data. Many companies think they need to
be like Facebook and collect as much data as possible, but this won’t help a small bank operating in a local market. Try rather to identify meaningful data to help your business. What many decision-makers don’t realise is they probably already have most of the data they need. Similarly, don’t be pressured into collecting vast amount of external data simply because your competition is doing so. Collecting big data becomes expensive, complicated, and increases the probability of failure. Instead, focus on quality and your areas of improvement
7. We just need to find the perfect BI tool
Many companies believe that they simply need to purchase the perfect BI tool, then sit back and watch the insights roll in. But the truth is that there’s no such thing as a perfect tool; if there was, we’d currently be living in a golden age of perfect analysis and predictions.
BI isn’t about tools, technology, or data. It’s about culture. This means considering how BI is used, having a willingness to change from manual reporting, and having trust in the data and in Business Intelligence.