What’s the next Big Step with Business Intelligence?
Businesses, for centuries, have always been trying to stay ahead of their competition by acquiring information about their environment before their competitors can. The term ‘business intelligence’ was initially spoken by Richard Miller Devens’ in the later 1800s, where he described how an English banker was able to gain profit by receiving information about his environment and acting upon them - way before his competitors could.
Since then, there has been a constant evolution in technology to make sense of data and better business decisions, spanning across regions and industries. In the mid-1900s, converting data into usable information by storing them in ‘data silos’ helped tremendously in producing divided reports that paves way for various interpretations.
In the 80s, the arrival of data warehouses saw a big adoption across the spectrum, as it helped businesses to make data analysis and reporting easier. Thanks to the ever-growing business intelligence market, strategic decisions reflect to more realistic outcomes as they challenge the ever-growing assumptions – harnessing the power of data.
However, there are still some challenges to present business intelligence tools, mainly as the IT or data team is responsible to uncover insights from data and deliver them to business teams. This in turn creates a barrier between the data and the decision makers, making it a challenge to data democratization and to drive better outcomes.
So, what is the next big step with business intelligence?
A self-service business intelligence.
Effective data-driven decision making - The real power of self-service business intelligence is that it actually helps with the democratization of data. As data tools are becoming no code, business users can now leverage their expertise when exploring data to answer many important questions. The follow up questions that comes up after the initial searches advocate for deeper insights – making a heap of difference when it comes to effective decision making.
Promoting a curious culture - A self-service business intelligence tool paves the way to a culture of curiosity, where business users are encouraged to ask important questions and try to understand why some trends and challenges are happening. When business users can have access to data and obtain answers quickly, it means that they can base decisions on the full picture. With more confidence that they are seeing all the important data, it allows them to move quicker with decision making as well.
Covering time-sensitive needs - The business user can run queries and make reports whenever they need them, rather than having to wait on the data team to get to their request. This ability to move faster allows the businesses to take advantage of time-sensitive opportunities. Looking at the changing business environment with a growing pandemic, COVID-19, impacting almost every aspect of how we do business, this helps tremendously to address issues before they grow too big – ranging from product issues to customer service.
Provides a room for collaboration – Over the centuries, we have learnt different ways to build connectivity with one another for various purposes. There is a big potential to this - as people share ideas and build against one another, the insights become far beyond what is initially expected. With data collaboration, business users can see the big picture, together. Combining their individual pieces gives the context – leading to better accuracy to solving problems.
Utilizing the compounding interests with data – When more insights are built from insights, the collective intelligence can better help the entire organization. When people can do what they do best, businesses can utilize their collective talents towards addressing common solutions.
At Envyi by InfinitiLab, we constantly advocate for harnessing the power of data to the business user. Our first milestone, meet Atlas. Atlas is designed to be a self-service business intelligence platform that can organize and categorize your data through proprietary data abstraction later. This interface provides simple yet faster way for the user to search and use data to its full potential.
Click here for more information on Atlas.