Four major challenges of adopting cloud business intelligence – and how to overcome them
With nine in 10 sales and marketing teams insisting that cloud-based business intelligence (BI) technology is necessary to the management of their strategies, it’s no wonder that the adoption has exploded in recent years. However, many businesses, especially small to medium sized enterprises (SMEs) are still lagging behind.
BARC’s research study on BI and data management found that 45% of businesses had not adopted this technology yet, with 6% stating they were opposed to it altogether. Over half of SMEs rated their strategy usage as “low”, and the majority were still not using the cloud for any of their BI and data management programs.
Cloud-based BI can solve many data management issues that businesses face today. If used correctly, it can foster seamless and continuous utilization of information crucial to business growth. So why are so many companies still averse to it?
It’s fair to say that no company can survive for long in the modern world without some form of business intelligence program, whether it be a simple database or a complex data library. As companies become more reliant on large sums of data to manage their sales and marketing strategies, the need for larger storage capacities and immediate access to information becomes an absolute.
However, switching up an operation to run on a cloud-based business intelligence system can be a cumbersome process. Since these systems have the capability to draw from a wide range of datasets, getting everyone in the company up to speed during the implementation phase takes time. The hours spent in training eat into company profits, yet it is necessary for all employees to get onboard if the system is going to be used to its fullest potential. Unfortunately, most businesses that use BI systems fail in this regard, as 49% of employees report that they use less than half of the system’s features due to improper training.
Obviously, failing to properly onboard your team to a cloud-based system could lead to disaster, including decreased profits, longer sales cycles, and copious amounts of employee frustration. For example, say your company switches to a cloud CRM system so your sales associates have access to customer data at all times. If they are not properly trained, they could miss important consumer tidbits, such as the customer’s position along the sales funnel or previous encounters with other representatives. However, with proper training, they can gather important insights from the program to create more seamless experiences. To give you an idea, reps could use the information from POS data points to create more personalized sales strategies based on customers’ past purchases and preferences.
Unless your employees are tech wizards who happen to be experts in cloud-based BI systems, thorough onboarding will be necessary to get them comfortable with the technology. Of the companies that were able to successfully integrate BI into their sales and marketing practices, 86% claimed to have more accurate reporting and analysis, 84% improved their business decision making process, and 79% saw an enhancement in employee satisfaction.
Additionally, operational efficiency increased, as did customer satisfaction and revenues. Numbers like this clearly show the benefits of proper training and how it can create a more competent and productive company.
The mass amount of data that companies have access to in today’s business landscape has created all kinds of gray areas in terms of data governance. Of course, there are many legal issues that come with the hierarchy of data access. For example, should every department within a business have access to sensitive and private information like financial or customer data? Perhaps not. But if every person needs to request permission to access necessary information, it could lead to an immense backlog and wait time to gather specific data points, which completely defeats the purpose of cloud-based BI.
There are some key guidelines companies should follow when setting up internal governance for data.
First of all, teams must recognize that not all data is created equal, and therefore, no single level of access can be used for every dataset all the time. There must be a chain of command in place and a series of checks and balances to ensure that data is being used correctly.
The second rule of thumb is to understand how linking data will create stronger strategies. However, this must be done wisely without using unnecessary datasets. Many sales teams will have their own sets of stored data from experiences and interactions with customers. Similarly, financial departments, customer service representatives, and marketing teams will have their own information as well. By combining these data points into a unified system (like a cloud-based BI program), every department can harness the power of this information to create better customer experiences.
Companies that understand the importance of a unified system for proper governance report remarkably higher success rates than businesses with multiple, inconsistent data sources. Additionally, failure to put a system in place leads to unreliable data that cannot be trusted, which creates confusion, and ultimately, failure.
There is no “one size fits all” rule that can be applied to data governance, at least not yet. The technology is changing very rapidly, and it may take time for legal restrictions to catch up. However, in the meantime, it is vital that businesses set their own standards and rules for proper lineage and chain of custody when it comes to data management.
Security is the number one issue that businesses have with implementing cloud-based BI systems - with 45% listing it as their top concern.
In the process of moving data to the cloud, security risks can increase significantly. Cloud-based data can sometimes be more prone to hackers and system attacks, so this objection is certainly viable.
These days, data security is at the very top of most priority lists, and if it isn’t, it needs to be. However, it is not impossible to guarantee data security with cloud-based systems if the proper precautions and measures are taken.
In order to ensure that data points are safe and secure (especially during transfer), businesses must use cloud providers with network segmentation, strong password requirements, and heavy encryption for maximum protection. Machine learning systems can be a powerful weapon of defense when it comes to data security. This is because of its ability to mold and adapt as threats grow and system needs change. In fact, machine learning-powered security systems are able to identify and combat credential attacks, which make up over 80% of hacking-related data breaches.
BI solutions are in a fast, perpetual state of advancement. If a solution goes obsolete, businesses need to be able to change their system with very short adjustment times. This is, of course, a major concern for companies who equate technology changes with higher costs.
In order to diminish the feeling of being overwhelmed with the power and complexity of cloud BI systems, it is best to only focus on the features that will best support your specific industry. Different businesses will require different focuses, depending on their key areas of service. For example, financial services would benefit greatly from end-user self service programs, but have little need for deep data mining. On the other hand, healthcare companies need more data discovery capabilities, along with in-memory support and data cataloging.
Businesses that are considering adopting this type of technology-forward BI system must be prepared to keep up with the changes. This will require constant re-evaluation of systems and comparing old strategies with new and emerging ones. By narrowing your company’s focus to only the most important features, the task of keeping up with the changes will be easier and narrower than trying to keep up with cloud-based advancement as a whole.
Adopting cloud-based systems are rarely easy, but they are necessary in order to keep up with the advancing tech world, especially in regards to BI. Of course, no technology is without its weaknesses or challenges. And in the case of cloud-based BI programs, these obstacles can often seem insurmountable. Fortunately, the top four objections against the implementation of this technology are not without solutions.
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