Many companies are implementing business intelligence (BI) software for smarter data use, but few are achieving the desired ROI results. Why? Because the organizations hardly understand the actual costs of BI. They are focusing primarily on license metrics while comparing BI analytics tool and platform vendor expenses, not realizing that it’s only a fraction of the total ownership costs.
So, failure comes from evaluating the “sticker price” of the BI solution and comparing it with direct returns from data analysis. The cost of the BI tool or that of the present situation is underestimated. To know more about the hidden expenses of business intelligence, read below:
Businesses cut corners wherever they can, often buying low-end data tools that work fine for a year or two, but then fall short while handling the growing data quantity. Moreover, new IoT devices and other new technology increase the complexity and number of data sources.
Thus, the cheap tool you bought earlier is a short-term solution; it is not a permanent answer to your data requirements. However, by the time you realize this, you’ve already wasted considerable resources purchasing licenses, allotting training hours, and making your employees reliant on this tool.
No wonder they have zero interest in knowing more about the use of a different software tool. As a result, companies must grudgingly spend their extra resources for implementing a new, full-fledged business tool. The alternative would be to keep on working with a subpar tool that does not fulfil all their requirements.
Buying Into the Hype
A big mistake that organizations make early on is buying into the business intelligence hype – investing in the latest, most advanced BI tool just because they’ve been told they need one, rather than choosing one on the basis of its problem-solving capabilities. There’s no doubt that business intelligence is of value to companies, but spending money on a BI tool arbitrarily doesn’t do any good. You must first identify the issue you’re outlining or hoping to solve; otherwise, you will never achieve the desired results.
First, think about your business problem along with what your company hopes to achieve. Have a clear idea of the capabilities required to solve those issues or fulfil that goal. Select a BI tool that adheres to those requirements. This way, you will avoid spending money on something that has no place in your organization.
One of the key considerations in a cost-benefit estimation of BI tools is whether the current ecosystem can support the software. Another is, whether it can serve as a standalone solution for data analytics or join the cluster of other programs to be of any real value to the company. What’s important is that you understand the number of moving parts the analytical value chain contains. First, you’ve got to connect the raw sources of data and then perform ETL and data cleanse before analysis.
Most market BI tools perform only the last stage, using flashy dashboards and graphics to hide how every important backend task is delegated to an IT professional or a separate tool. Thus, you need to carefully understand the functionality you’re going to get from the desired software. Tools – both the single and full-stack varieties – serve well as platforms for handling various activities, from data modelling to preparation to the development and sharing of dashboards.
While using proprietary database tools and ETL with data visualization software is not wrong, you must figure out how all this changes the final price, and whether you’re willing to foot the bill for the perfect analytic solution.
You must also think about the price being paid for by your company as your precious employees spend more time preparing reports instead of focusing on different mission-critical activities. While this applies to the first scenario, where everything’s done through spreadsheets, when you’re getting a modern business intelligence tool, you need to ensure it upholds the standards of self-service expected by business users.
Regular enterprises sought help from qualified data analysts and IT professionals, to build BI. They needed somebody who was perfect for coding and scripting for the purpose of a different query. Though modern tools neglect this, with back-end functionality being absent means that coding and scripting happen in the initial data preparation phase. Businesses users within the company will no longer have to struggle with countless spreadsheets; they can assign the task to technical workers instead, who must operate IT-focused systems for producing reports. To avoid this, business users in your company should consider the tool and answer personal data questions, rather than relying constantly on external or internal tech support.
When you’re unable to do something because you decided on something else, the cost incurred by the company is the opportunity cost. It’s one of the most hidden and overlooked BI expense, and you need to consider what you’ll do during that time with those resources. Although this is difficult to measure in projects, it becomes easier to find the similarities between projects and assign a value to any missed opportunity.
Companies often buy business intelligence upfront due to a combination of factors, from high pressured sales strategies to promises of big discounts, to decision makers failing to realize the best course of action. This can significantly add to your BI program expenses and also lead to shelfware if your employees fail to receive proper tool training or remain clueless about the positive impact of the tool and refrain from implementing and using it within the organization. To prevent wasting the company money, you should seek out a BI tool vendor that gives you the opportunity to begin small, prove that the concept is useful to your business, and then scale as required.
Successful BI depends on people in various roles, and even when the project is deployed, many of those roles continue to play a vital part. However, end users will only enter into the process if they think the question they want to answer is worth their effort and time. We automatically assume that a new BI solution is going to be better, which is precisely why we invest resources and time into implementing it. But does it answer the questions of the end users? Think about the questions not asked because they weren’t worth the effort. Or worse, if they were worth it, but the user refused to wait due to lack of time, and so, made an instinctive decision.
Businesses thinking about BI will rarely have the necessary visibility into these missed questions until they discuss the situation with end users. The price of an unasked question may be considerable, for example when you’re deciding if you want to pull or extend a specific marketing campaign.
Rather than look at BI from a tech perspective, you need to consider it also from an end user’s workflow perspective. These costs are recurring, and directly affect the other indirect expenses discussed earlier. While we’ve discussed the price of not asking a specific question above, what price do you have to pay when you do ask and receive a response? If you’re lucky, you won’t have another business intelligence platform decision on your hands for several years, but the workflow to get new answers will keep on repeating itself.
So, it becomes evident that several sources of cost exist outside the upfront expenses of procuring and managing a solution. If you think that offering data-driven insights is a valuable function, you must try and appreciate the actual cost of your company’s BI solution.