The value of business intelligence can be measured as much in increased quality of working life as it can in hours saved, opportunities gained, processes streamlined, and better decisions made. But each of those comes with a price tag. And in the world of BI, that price tag can vary wildly from solution to solution, and isn’t necessarily in accordance with the value it brings.
Total Cost of Ownership (TCO) for a business intelligence and analytics platform has a pretty straight forward formula: infrastructure + people = TCO. But in reality, there are so many asterisks added to both the technology and the people who implement it that companies are often left writing out checks for up to hundreds of thousands of dollars more than what they had originally budgeted for on a system and processes that are a far cry from what was promised them.
According to Gartner, software license and maintenance only accounts for, at the very most, less than 15 percent of the total cost of a business intelligence project. In reality, there is a laundry list of direct and indirect costs that rise steadily up front and over time.
Of course there are both one-time and recurring costs for data, software, hardware, and people. Those include everything from data integration, security, and software subscriptions to hardware storage, infrastructure upgrades, and ongoing development.
But you also must consider the other costs that are tied to a new analytics process such as the time it takes to learn, loss of motivation, employees’ resistance, lower performance due to improperly performing the new process, and lost opportunities to do something better.
These are the four most common costly pitfalls.
1. Pitfall: Poor data quality
The first step in implementing a business intelligence project is pulling data into the data warehouse from the various other company systems such as the CRM, HR systems, and finance systems. But first, data must be cleansed, which is time consuming and costly.
Solution: Aim for the MVP
When it comes to the data you should be integrating into your data warehouse, think big, but start small to minimize the up-front consultancy hours for data you aren’t even sure you need or want to begin with. Aim for the MVP, the Minimal Viable Product. This is the data that’s going to give you the biggest turn on investment quickly.
A clear strategy must come before implementation. This guide helps you map out how to design the decision-making process that works best for your organization: “The Better BI Strategy.”
2. Pitfall: The never ending project
Otherwise known as “scope creep,” long stretch projects plague companies who struggle to select the most important data to bring into their business intelligence project. As a result, they overdo it, raking in scores of data that ultimately muddies the pond. This leads to the data quality problems I’ve already mentioned. All too often we have seen companies pull data into the data warehouse, clean it, and then decide that they don’t actually want or need those data sets.
This results in a seemingly never-ending process of starting, stopping, starting, and stopping the BI project. Worse, it’s not uncommon to see company priorities change in this time before any analytics objectives can be obtained, rendering everything already done up until that point useless. The business world is changing so rapidly that a slow business intelligence implementation can mean no business intelligence at all.
Solution: Understand your business objectives
Know your business objectives from day one and build an action plan. Continuously re-evaluate this plan. Real world problems commonly move the burning platform, so to speak. Your action plan should be flexible enough to move with it. Don’t think of business intelligence as one set project, rather a continuous strategy towards data-driven excellence.
Instead of pulling in data across the board because it might be useful, establish the metrics that matter most and focus only on those. This prevents information overload and ensures employees are focused on the most important KPIs. This guide will help you determine which KPIs are most important for your company: “The Metrics that Matter.”
3. Pitfall: License creep
License creep is the uncontrolled growth in software licenses within a company. Of course, the ultimate goal of any successful BI implementation is to spread the power of analytics to as many users as possible throughout the company.
Many vendors charge a fixed price per user and don’t offer bulk pricing. As new users are added over time as the project grows, that price doesn’t flex. BI buyers also often overlook the fact that once their business intelligence project evolves to a more collaborative, unifying strategy, there is a high price tag for the additional servers needed for an enterprise-wide roll out.
Solution: Plan for a BI roll out
Long-term strategic thinking is particularly important for avoiding a surprising license creep. It’s important not only to consider what objectives your company wants to achieve to start a new business intelligence project, but also what the long term goals should be and who should be involved in their execution. Grow you license with the BI roll out over time. Start with key users and buy licenses as you need them. Get professional help to initiate your BI roll out and ensure internal staff is trained to further develop and support the solution.
A large part of this plan is mapping out who in particular will be utilizing analytics, their roles and functions within the organization, and how they best consume data. We call these the BI personas. This guide will help you define the BI personas at your organization to facilitate and embrace high user adoption: “How to Ensure the Highest User Adoption Rates for your BI Project.”
4. Pitfall: The under-utilization obstacle
So you’ve purchased and implemented a business intelligence solution, now you need to learn how to use it. A powerful BI and analytics solution isn’t worth anything if users aren’t armed with the know-how they need to take advantage of the various levels of tools.
Companies are often won over with the words “self-service” only to discover that quite a bit of technical expertise is needed. What might look simple and user-friendly in a demo by a sales professional can be an overwhelming task for a business user in the real world. Companies are often won over with flashy data visualizations and dashboard software, but when business decision makers need to dig in to further details, they need expensive consultants to help.
Solution: The right tool for the right job
Users should receive the business intelligence training classes designed specifically for their BI needs within the organization. Like licensing, training is not one-size-fits-all. Go with the business intelligence vendor that has an array of different classes for a variety of different skill levels—from basic dashboards and data visualization to advanced real-time analytics and everything in between. And training shouldn’t break the bank. A business intelligence provider that charges an arm and a leg for training is missing the point of BI for everyone.
This guide will help you plan for the steps that need to be taken on each stage of the journey to becoming a data-driven organization and: “Three Stages of Becoming a Data-Driven Organization.”
The BI partnership
Don’t fall victim to these common TCO pitfalls. Enter the buying process informed about what should – and what shouldn’t—lie ahead in a successful business intelligence implementation and strategy. Knowing what’s coming is half the battle. The rest lies in aligning your company with a BI partner who is upfront with all of the potential direct and indirect costs of business intelligence and analytics.
Download the full guide with our detailed look at the hidden costs of BI and the steps you should take to avoid them. We have an action plan mapped out for you here: "Taking Control of BI’s Total Cost of Ownership."