“Knowledge has become the key economic resource and the dominant, if not the only, source of competitive advantage.” – Peter F. Drucker
I share that quote because it applies perfectly to the current business world. We’re in the middle of a data explosion. We have more data from more sources than ever before. Those who can turn this data avalanche into easily accessible knowledge will hold a true competitive advantage. But, if left uncontrolled, this data overload can have the opposite effect.
According to Reuters “Dying for Business” report, “One-third of managers are victims of ‘Information Fatigue Syndrome.’ 49% said they are unable to handle the vast amounts of information received. 43% think that important decisions are delayed and their abilities to make decisions are affected as a result of having too much information.”
To combat these data challenges, more organizations are turning to Business Intelligence. According to growth statistics, BI adoption has exploded over the past few years and isn’t slowing down. It’s estimated that the BI market will grow by an additional 5.2% in this year alone.
So, with all of this BI growth, you’d assume that organizations are starting to get a handle on their data…right?
The answer is “yes and no.” Sure, many businesses do see great returns from their BI investments. They’re capitalizing on BI and turning their data into meaningful management information.
The problem is, most BI projects still fail. Depending on the survey you read, the BI failure rate is anywhere from 50 – 80%.
Why? Businesses are quickly realizing that BI isn’t simply a software issue. They can’t just throw software at their data, and expect to solve their problems.
The fact is, CIOs and IT leaders will face a number of challenges in any BI implementation. These challenges can do anything from slow down the project to cause outright failure. You must plan for these challenges before you start the project.
What are these challenges, and how can CIOs and IT leaders address them? Today, let’s focus on that topic. Here are 4 of the biggest BI challenges facing CIOs and IT leaders.
1. Getting full executive buy-in
One of the biggest (yet most important) challenges occurs before you even start the project. You must get the C-suite fully onboard before moving forward.
Why is this so important? Like any project, BI projects don’t always go according to plan. You’ll likely run into unplanned hurdles that push the delivery date back or bump up the cost.
When these problems arise, executives who aren’t fully committed to the project will start complaining. They might even pull support or funding–derailing the project altogether.
The challenge: Secure full buy-in before you start. How can you accomplish this? Sell the C-Suite on the benefits of the project, highlighting specific ways it will help their department.
Then, during the implementation phase, don’t go for a big bang approach. Start small, and aim for easy wins. Look for problems that you can easily solve with the BI solution, and roll those out first. These little wins will help drive excitement in the business, and push the project forward.
2. Staying on schedule despite incomplete requirements
It’s a common problem. The business requests a solution (like Business Intelligence), but then can’t agree on exactly what they need in that solution. Or, their requirements change many times throughout the project. Then, they get mad when these changing requirements push the delivery schedule back.
“Coming from a consulting background having lead multiple BI implementations and projects for fortune 500′s, I can say without a doubt the biggest hurdle for any CIO and IT leader will be managing the speed of delivery needed with minimal requirements by the business provided,” says Ty Tucker, CEO of REV Acceleration. “Many organizations simply haven’t thought about or can’t agree upon basic things like KPI definitions or what should be in a report. In turn, since requirements are needed to determine where to pull data from and how it will be used, timelines can drag which at times may result in the business looking for alternative methods around IT (shadow IT) bringing in new tools that create inefficiency throughout and minimize any chance at data governance.”
How can you keep the project on schedule, despite these incomplete (and changing) requirements? The obvious first step is mapping out clear requirements from the users before starting the project. But, what can you do when the requirements change?
“IT leaders need to work better with the business, focusing on collaborative iteration that may not always result in a release that is 100% perfect, but is released months quicker which can then be tweaked as needs be,” explains Tucker. “Managing this dynamic of give and take between business and IT is paramount to staying at/under budget, delivering success while the solution still has relevance instead of months late once initial requirements have changed completely.”
3. Managing the volume and variety of data
Data exists in more formats than ever before. From social media data to “smart” things to your enterprise systems, you must tie a wide variety of data together.
“The #1 challenge facing anyone looking down the barrel of implementing BI is the volume and variety of their data,” says Justin Davis, Director of Enterprise Sales, CenturyLink. “Big Data has been a buzz word the last few years, but more accurately it should be known as Big Dumb Data. For any measure of actionable intelligence a team wishes to uncover, there are potentially exponentially more pieces of data that will need to be identified, analyzed and understood in order to create that actionable intelligence. This is especially a problem for Enterprise Businesses as the complexity of their systems grows both organically and through M&A. With M&A comes different systems and even different terms for the same items. Add in the ever growing amounts of data gathered through legacy systems, new systems and smart devices with multiple sensors and the complexity of the task begins to present itself.”
Now, I’ve seen a growing misconception about modern BI solutions. Some businesses assume they can put a BI tool over their existing systems, and start creating the reports and dashboards they need. Or, they assume the BI tool will automatically pull data together from multiple sources.
The fact is, it’s not that simple. Business Intelligence will provide insight into your data–provided that data is in a location and format that it understands. The problem is, data rarely exists in a single location or format. Chances are, you’ll need to invest in ETL and data warehousing (unless the BI tool provides these features) before you even start the project. Understand what data you need to have analyzed, and set up an automated method to put that data into the right format.
4. Delivering true self-service BI solution that users will actually use
There’s an old saying: You can lead a horse to water, but you can’t make him drink. The same goes for BI. You can deploy the perfect BI solution, but you can’t force users to adopt the tool.
One study found that BI adoption among employees was only at a measly 22%. This creates problems for all involved. If users aren’t using the self-service tools provided, it places more pressure on the IT department. They go back to the old reporting methods–where all reporting goes through IT.
So, why is BI adoption so low among employees? There are a few reasons. First, as explained below, many of these “self-service” tools are too technical for the common user.
“Non-technical business users are just not comfortable with complex IT implementation requirements for BI infrastructure such as Data Warehouse, and are not interested in learning advanced technical skills such as programming in order to build their analysis,” says Ben Tai, CEO of DrivenBI. “Meanwhile, IT and line of business users do need to overcome data silos formed as a result of static data warehousing and data modeling structures. All of these issues make it more difficult to have the right information available to right business user at the right time. IT wants to ensure that business users are able to have timely access to data when they need it. IT also is aware the if they are not getting the right tool for doing so, they will keep going back to demanding heavy IT support which often times causes delays on the delivery of more mission critical analysis and also creates tension between business users and IT.”
What other problems create low adoption, and how can you fix them? It’s a topic I’ve covered in a past article, which you can find right here.
Summary
These are just 4 BI challenges facing CIOs and IT leaders, but the list could certainly be longer. Would you add anything to this list? If you would like to add anything to this list, I’d love to hear it. Feel free to share in the comments.
