Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Why? Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition.
For example, in regards to marketing, traditional advertising methods of spending large amounts of money on TV, radio, and print ads without measuring ROI aren’t working like they used to. Consumers have grown more and more immune to ads that aren’t targeted directly at them.
The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.
Why Is Business Intelligence So Important?
The main use of business intelligence is to help business units, managers, top executives, and other operational workers make better-informed decisions backed up with accurate data. It will ultimately help them spot new business opportunities, cut costs, or identify inefficient processes that need reengineering.
BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. Business intelligence can also be referred to as “descriptive analytics”, as it only shows past and current state: it doesn’t say what to do, but what is or was. The responsibility to take action still lies in the hands of the executives.
This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence. It’s all about using data to get a clearer understanding of reality so that your company can make more strategically sound decisions (instead of relying only on gut instinct or corporate inertia).
Ultimately, business intelligence and analytics are about much more than the technology used to gather and analyze data. They’re about having the mindset of an experimenter and being willing to let data guide a company’s decision-making process.
What Are The Benefits of Business Intelligence?
The benefits of business intelligence and analytics are plentiful and varied, but they all have one thing in common: they bring power. The power of knowledge. Whichever unit they impact, they can transform your organization and way to do business deeply. Here is an overview of 6 main business intelligence benefits:
- Make informed strategic decisions
- Identify trends and patterns
- Drive performance and revenue
- Improve operational efficiency
- Find improvement opportunities through predictions
- Smarter and faster reporting
In this post, you’re going to dive into 6 illustrations of the advantages of business intelligence, backed up with some real-world case studies along the way. By the end of this post, you’ll feel the need to double down on creating a data-driven culture at your company, and you’ll have some hard evidence you can use to persuade skeptical teammates.
Benefits of Business Intelligence: 6 Case-Studies
Here are six use-cases that illustrate different business intelligence benefits.
1) Informed strategic decisions
As the first and most impactful of all benefits of analytics, we have the ability to make informed strategic decisions backed by factual information. Experts say that BI and data analytics makes the decision-making process 5x times faster for businesses. Let’s look at our first use case.
Renowned author Bernard Marr wrote an insightful article about Shell’s journey to become a fully data-driven company. Although the oil company has been producing massive amounts of data for a long time, with the rise of new cloud-based technologies and data becoming more and more relevant in business contexts, they needed a way to manage their information at an enterprise level and keep up with the new skills in the data industry.
In order to do this, they first defined what data was the most relevant for the company. As Dan Jeavons Data Science Manager at Shell stated: “what we try to do is to think about minimal viable products that are going to have a significant business impact immediately and use that to inform the KPIs that really matter to the business”. With this information in hand, the company started to think about how to invest in data quality, data standards, and the required technology to support it.
Skills were a big challenge for Shell, however, the company developed tailored training programs for their employees so that they could learn to use data for their own problem-solving. Additionally, they invested in professionalizing the core work of data scientists for more complex operations.
Shell’s initiatives were successful because they implemented a data-driven culture in their entire organization. Empowering all levels of employees to use data for their decision-making process means extracting relevant insights at every level of the company. Without a doubt, one of the big benefits of data analytics and professional self-service BI tools is the democratization of data.
2) Identify Trends and Patterns
As mentioned above, one of the great benefits of business intelligence and analytics is the ability to make informed data-based decisions. This benefit goes directly in hand with the fact that analytics provide businesses with technologies to spot trends and patterns that will lead to the optimization of resources and processes. Business intelligence and analytics allow users to know their businesses on a deeper level. Let’s see it with a real-world example.
The famous Boston Celtics basketball club hopped on the analytics bandwagon too, so as to understand how their market evolves and also so as to evaluate their players.
Thanks to the data they had collected on their customers, they have been able to analyze who they are, where they sit, and how much they pay. That is precious insight for the sales team who can look into the data in real-time and understand what the leverages beneath it are. It helped them to quickly create promotions to sell more tickets, as well as to conduct revenue analyses based on these trends.
What’s more, visualizing their data helped them see how much revenue a given seat is producing during a season, and compare the different areas of the stadium. Given that the Celtics have a very complex ticket pricing structure (over a hundred different prices depending on the package, section, individuals, students, competitive games, etc), it is all the more important to understand in a glance which seat brings what, so as to make decisions on the fly for promotions.
A simple example is: if there are many low-cost seats still available for an upcoming game, the sales team can send a customized email offer to local students.
Regular “five-figure” returns from promotions based on analytics, according to Morey, senior VP of operation at the Boston Celtics. But it is just the beginning: thanks to the analysis of the fans’ sitting plan, the sales team can redraw the lines for price breaks for the next season.
The purpose is of course to make more money, but it is not just for money’s sake. The finances they get from these analytics will be reinvested in the players and their training, which means that players will get better and so will the games.
3) Drive Performance And Revenue
Driving performance and revenue is one of the relevant benefits of business analytics. McKinsey realized a case study on a fast-food chain restaurant company with thousands of outlets around the world. That company wanted to focus on its personnel and analyze deeper any data concerning their staff, to understand what drives them and what they could do to improve business performance.
After exhausting most of their traditional methods, the company was looking for other ways to improve customer experience, while at the same time tackling their high annual employee turnover, whose figure was above the average of its competitors. The top management believed that tackling this turnover would be key in improving the customer experience and that this would lead to higher revenues.
To do so, the company started by defining the goals, and finding a way to translate employees’ behavior and experience into data, so as to model against actual outcomes. The goals were multiple: revenue growth, customer satisfaction, and speed of service. They then proceeded to analyze three areas: the employee selection and onboarding, the daily staff management, and finally the employees’ behavior and interactions in the restaurants.
They used the data collected to build a logistic-regression and unsupervised learning models, so as to determine the potential relationship between drivers and outcomes. They then started to test over a hundred hypotheses, among which many had been championed by senior managers who strongly believed in these methods after their experience. That was a powerful experience as it confronted senior managers with evidence against what they believed was true and practiced for years.
All the insights they gleaned challenged their beliefs and experience, but the results after implementing new measures according to their findings were indisputable: customer satisfaction scores had increased by more than 100% in four months, the speed of service by 30 seconds, attrition of new hires had decreased considerably, and sales went up by 5%.
4) Improve Operational Efficiency
Technology giant Microsoft was looking for a way to improve productivity and collaboration in the workplace. For this purpose, a senior researcher from the company conducted a study to understand the common problems faced by remote work on Microsoft. The findings showed that the main challenges included “communication in planned meetings, ad-hoc conversations, awareness of teammates and their work, and building trust relationships between teammates”.
These findings validated the theory that awareness of team members degrades with physical distance. The study even showed that employees that are situated on the same building but on different floors are less likely to collaborate. With this issue in mind, Microsoft came up with the idea of moving 1.200 people from 5 buildings to 4 in order to improve collaboration.
As a result of the relocation, the analytics team analyzed metadata attached to employee calendars and found a 46% decrease in meeting travel time which translated into estimated savings of $520,000 per year in employee time. As seen in the chart below, the team found out that “that minutes saved for each employee equates to hundreds of thousands of dollars in cost-savings for an organization over time.”
The analysis also showed that the number of weekly meetings per person increased from 14 to 18. Overall, the use of data analysis in this use case showed a significant increase in employee collaboration and increased operational efficiency for the company. Chantrelle Nielsen director of research and strategy for Workplace analytics said: “companies must take these metrics and direct them thoughtfully towards the design of office spaces that maximize face time over just screen time.” A great way to illustrate the operational benefits of business intelligence.
5) Find improvement opportunities through predictions
The fifth benefit of implementing business intelligence and data analytics into your company is the use of predictive analytics. A great use case of this benefit is Uber. This company was originally founded in 2009 as a black car-hailing service in San Francisco. Although the service costed more money than a regular taxi ride, customers were attracted to the experience of ordering a car from their smartphones.
Now, you might be wondering, how did this small San Francisco start-up turn into the successful global company that it is today? The answer is data analytics and business intelligence.
Uber has an algorithm that takes valuable data from every driver and passenger and uses it to predict supply and demand. The gathered data includes everything from customers’ waiting times, peak demand hours, traffic for each city, a driver’s speed during a trip, and much more. All this data is then used to set pricing fees, meet demand, and ensure an excellent service for both their drivers and clients. For example, by using prediction models, they are able to generate a heatmap to tell drivers where they should place themselves to take advantage of the best demand areas.
According to this case study, one of the most interesting uses of data from Uber is its surge pricing method. It is basically the algorithm that makes an Uber more expensive at peak traffic hours, holidays, rainy days, etc. Uber has made this system by using real-time predictions based on traffic patterns, supply, and demand. While this is a successful pricing system that is praised by other enterprises, the higher fares have brought the company a lot of backlash for trips that are twice as expensive. To avoid this issue, Uber has recently announced that they will use machine learning technologies to predict future demand and make sure that more drivers are redirected to the high-demand areas to avoid surge pricing and offer their clients a fair fee.
This is a clear example of the advantages of business analytics and how the use of predictive analytics can help businesses spot improvement opportunities to optimize their processes and ensure higher customer satisfaction levels.
6) Smart and faster reporting
The last in our rundown of the top benefits of business intelligence and analytics is related to data management and visualization. One of the powers of BI tools is they open the doors to a more efficient reporting process which also makes data analytics accessible for everyone, without the need for prior technical knowledge. Let’s put this into perspective with a success story from datapine.
Lieferando is a European online food-ordering service that was acquired by Just Eat Take Away in 2014. The brand which operates mainly in Germany, the UK, and Sweden, has a clear mission of providing a fast and easy way for its 98 million customers to get food from their favorite restaurants. With millions of consumers and more than 580 thousand partner restaurants within 25 countries, the company was facing issues related to data management and access to massive amounts of enterprise-level information.
Their main challenges were to combine different sources of data in real-time in one central location, optimize their marketing campaigns with data-based insights, and get a comprehensive view of their entire customer lifecycle. Additionally, they needed a tool that allowed all employees in the company to deal with data without the need to involve the IT department.
With the implementation of datapine’s BI reporting tool into their system, the company was able to manage big amounts of data in real-time while significantly cutting the time they spent on report generation. This allowed for a faster decision-making process, streamlining of their marketing and sales activities, and the overall optimization of several processes at an internal and external level.
Team members at Lieferando said that “our new real-time dashboards allow us to monitor all major business operations through customized Key Performance Indicators. We can instantly act on changes and are now able to adapt better to new business challenges right when they occur and not weeks or even months later.”
Business Intelligence And Analytics Lead To ROI
Business intelligence is key to monitoring business trends, detecting significant events, and getting the full picture of what is happening inside your organization thanks to data. It is important to optimize processes, increase operational efficiency, drive new revenue, and improve the decision-making of the company.
We’re living in the most competitive business market in history. Technological advances and a global economy have combined to create a pressure cooker of competition, with weaker companies being swallowed up or broken down. Luckily, business intelligence tools have developed the necessary technology for companies to manage their data efficiently. BI dashboards like the one presented below provide a centralized view of the most important metrics businesses need to stay ahead of their competitors. And not just that, getting a visual overview of the performance of several areas also empowers employees to use data for their decision-making process.
Given the current state of affairs, your company can’t afford not to use BI tools. Especially after we examined 6 case studies that showed the incredible ROI that is possible from using them and the many benefits of business analytics. Such business intelligence ROI can come in many forms. You need to know what’s going on in the minds of your customers, who your next best customers will be, and how to serve them in the most effective ways. All of these areas can be answered with data – which you need BI and analytics tools to process. However be aware of any faux-pas and remember: there are some business intelligence best practices to know – and some worst practices to stay away from!
When your company has to rely on internal or external IT staff to generate data reports, it creates a huge barrier to what is most needed: a data-driven corporate culture, where decisions are validated through seeing reality clearly.
If you’d like to take your first step towards using an intuitive self-service business analytics tool, you can try our 14-day free trial and test what datapine can do for you.