7 February 2023
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Practically all businesses compile statistics, examine competitor data, and conduct market research on their customer base. But, when it comes to formalising business decision-making to make operational improvements an integral part of their company’s development, many firms fall short. That is to say, many organisations lack what is known as ‘Decision Intelligence’ (i.e., creating a framework to apply Business Intelligence findings across their entire enterprise).
With that in mind, this article will look at Decision Intelligence vs. Business Intelligence, explain the differences between the two concepts, and tell you what you need to know to get the most out of your business data analytics.
Business intelligence (BI) refers to both a set of tactics and software tools that analyse company data, publish reports, and act on BI findings. The concept has been around since the late 19th century, but Business Intelligence as both a discipline and a set of data science tools has massively evolved since the days of ‘pen and paper BI.’
Nowadays, Business Intelligence tools analyse numerous organisational data sets to display findings in reports, summaries, dashboards, graphs, charts, maps, and other data visualization formats. BI tools make it easy for decision-makers to digest relevant information from company data and external sources (such as competitor or customer experience information), and act on it.
Traditionally, companies that use BI employ specialist Business Analysts to compile data and present the findings to senior leaders. Business Intelligence professionals are highly skilled in statistical analysis, data modelling, and coding. They also have exemplary communication skills and problem-solving abilities. In short, BI tools and professionals work together to bring company data to life and help guide better decision modelling and making.
However, Self-Service BI is the next-generation tool for better Business Intelligence. With Self-Service BI tools like Vizlib Self-Service for Qlik Sense, companies can reduce the workload of specialist BI professionals and unlock access to data and insight to a wider range of Business Users. Learn more about the benefits of Self-Service analytics in this article.
Like Business Intelligence, Decision Intelligence (DI) uses data analytics tools to create reports and provide recommendations to key stakeholders. However, it differs from BI because it can leverage Artificial Intelligence (AI) and automation software to conduct specific tasks based on data analytics findings. For example, DI can predict future outcomes based on historical data trends (an activity which is also known as ‘predictive analytics’).
Modern BI tools can be used for forecasting, too. However, DI expedites this process, reduces the workload for analysts, and provides more informational context to empower highly-informed and accurate decisions. In short, DI gives stakeholders answers not only to the ‘what’ questions of data analysis but also the ‘why’ questions: As in, ‘why should a business make this operational adjustment to get better results?’
DI tools provide more context to company information and Big Data sourced from third parties. A recent study found that 69% of business leaders believe utilising Big Data in their business model is vital to sustaining growth in the years ahead.
However, Gartner found that only 30% of employees use analytics and business intelligence (BI) tools daily. This may be because conventional BI tools are inaccessible to those who have no formal training or experience in coding or data science.But modern, self-service Decision Intelligence tools and strategies can help make data analysis easier for those who don’t have a technical background in coding or compiling data.
Of course, it’s important to note that setting up a DI framework will likely involve data engineers and scientists for initial system configuration. Still, once a system is in place, any team member can analyse DI findings, disseminate the information, and act upon data-driven insights.
Interactive analytics tools (such as Heatmaps, live commentary tools, and KPI tracking) play a crucial role in the effectiveness of DI, as they make collaborative BI possible.
For instance, if there are conflicting resourcing needs between departments or misalignments on what actions a company needs to take, enhanced collaborative BI features create an open forum to resolve these issues.
In addition, collaborative BI can increase the speed of decision-making across your firm by 46%. This is because collaborative BI reduces the need for back-and-forth communication via email, in-person meetings, etc. All issues can be addressed within one centralised platform.
Establishing a collaborative BI framework can also help team leaders analyse individuals’ contributions to decision-making processes. With this additional analytics layer, organisations can offer rewards and incentives for employees who share their ideas and valuable insight frequently. To learn more about Collaborative Intelligence and how it can help your company facilitate ‘Active Intelligence’ capabilities, please read our previous article.
Currently, only 24% of businesses consider themselves to be data-driven, even though companies deploying data analysis in their firms enjoy an 8% uplift in profitability and can lower their operations costs by 10%.
To illustrate, BI tools that use pre-loaded reporting templates can dramatically reduce the time it takes to create reports back to stakeholders on important profit-boosting insights. For example, the pharmaceutical brand, Phoenix LV, uses Qlik Sense and Vizlib to compile fast and accurate P&L reports. Previously, Phoenix LV Data Engineer, Karel Lebr, used Excel to report profit and loss information, which took hours and posed a number of problems. But now, with the help of Vizlib’s dynamic data visualization tools, P&L reports can be generated quickly and shared instantly with the whole team.
Gartner predicts that by the end of 2023, 33% of large organisations worldwide will deploy Decision Intelligence technologies.
There are many ways to push your Business Intelligence activities forward and transform your organisation into one that deploys effective Decision Intelligence tactics.
For instance, as a starting point, identify where enhanced decision-making techniques and processes can create a positive impact on your operations.
Next, delegate data analysis duties, timeframes, and KPIs you want to track across all relevant departments, from finance to customer experience teams.
Finally, your DI findings need to be replicable and reliable, so seek robust data analytics and data visualization solutions like Vizlib + Qlik Sense to help you tell your data story.
Vizlib builds value-added products for Qlik technologies to help companies boost their analytics and get more from their data insights.
Here, we have compiled a quick rundown of how the Vizlib product suite can transform your BI tools and enhance them with various Decision Intelligence functionalities:
Vizlib for Qlik Sense can supercharge your BI capabilities and transform them into reliable Decision Intelligence systems that all employees can use to help your company grow.
Whether you’re looking to boost productivity, enhance profitability, or increase data literacy company-wide, Vizlib can help you tailor the best solution for your needs.
Best of all, the products operate on a no/low-code framework, which means you don’t need any prior experience to get your team up and running with Decision Intelligence tactics.
So if you want to explore your options for becoming data-driven and confident in your ability to accelerate decision processes as part of your wider digital transformation strategy, start your free trial now.
Unlock the power of Qlik Cloud. Vizlib enhances the capabilities of data visualization and analytics to give you unparalleled insight, so you can know faster and act sooner.
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