WHY VIZ TOOL IMPLEMENTATIONS FAIL
You know the importance of Business Intelligence – the data and analytics that help you make more profitable decisions. Like other smart, ambitious, data-driven people, you probably went out and purchased a data visualization tool like Power BI, Tableau, Domo, or Grow.
You were promised a simple, easy-to-use, complete-package, profit-driving, Business Intelligence machine. But you quickly discovered your “viz tool” wasn’t all it was cracked up to be in the sales pitch.
Turns out, implementing your viz tool and getting it to do what you want it to do is a serious challenge.
Where did you go wrong? In the years we’ve spent working as report writing specialists, we’ve found there are six reasons businesses struggle to implement viz tools:
- Data Integration
- Data Modeling
- Coding Languages
- Steep Learning Curves
- Adoption Troubles
1. DATA INTEGRATION
Standard business tools often don’t connect effectively or directly with your data sources. Your viz tool can connect to mature APIs like Google Analytics, but when it comes to your more obscure or specialized sources, you’re left hanging.
Not all APIs are created equal. Often sources will technically connect, but you can’t get everything you need. Common issues include…
- No access to historical data
- Key company metrics not being supported
- Limits on how often you can update data
- Limits on how much data you can pull
The results aren’t pretty. You’re still blind to your business’s activities and processes, including sales, revenues, ROI for your marketing efforts, and other important metrics.
If you don’t get this sorted out soon, you’ll continue to be stuck making your “best guess” on important business decisions.
2. DATA MODELING
There is a significant amount of data modeling that needs to be done when creating reports. The data needs to be organized and cleaned before it’s ready for your viz tool.
For example, Domo and Tableau like big, flat tables. What if you have data coming in from three different systems to one dashboard? To make it work, you’ll have to present one data set with all three sources included. If you don’t know how to make this happen with code, you’re in trouble.
The best place to perform data modeling/cleaning is down at the database level. The good news is this means you only need to create your business logic once in a centralized location. The bad news: this again requires coding skills.
3. CODING LANGUAGES
To really leverage the power of your viz tool, you need a developer who can work with its specific coding language (SQL, MDX, DAX, etc.).
Sales reps love to brag that their viz tools require no coding skills to use… But if any of your KPIs require custom calculations or complex joins, DOMO, Tableau, Power BI, and Grow are definitely not no-code solutions.
The drag-and-drop simplicity only happens in demos.
To make your viz tool work, you need to know how to customize it to meet your unique business needs. And that takes coding skills. It’s just the way it is.
4. STEEP LEARNING CURVES
Today’s reporting software is super powerful. But with great power comes steep learning curves. You can’t expect to be able to take advantage of the full functionality of your viz tool without spending some quality time with the user manual first.
It’s worth exploring the wide range of features your chosen viz tool offers. Most viz tools provide free training and have online communities where you can go with questions. Use these resources!
Be sure to consider if the time required to master your viz tool is worth it. A better option for you may be outsourcing to a specialist who already has the skills and expertise you need.
The lesson here is that you shouldn’t “park” your expensive viz tool when you can’t figure out an issue on your own. Plan on putting in serious amounts of time learning the ropes of your viz tool, or pay someone else to help.
5. ADOPTION TROUBLES
Getting your dashboards and reports up and running the way you want them doesn’t matter if no one uses them.
Sometimes skilled analysts and coders get so excited about the solutions they’re building that they lose touch with actual business needs.
They end up building amazing reports/dashboards that don’t get used.
The key is to make sure you keep end users close as you go through the process of choosing and implementing your viz tool. Make sure everyone involved understands how the reports you’re building will add value.
Get buy-in early on by asking for feedback and continuously updating your plan to best meet the Business Intelligence needs of the people in your business.
As people adopt and use your chosen viz tool, you’re going to have growing pains.
Every viz tool has a land-and-expand model. They sneak in a desktop license to one developer for free, then the price starts to grow as you expand to other departments.
Pricing structures for viz tools are often complicated. As a result, businesses don’t always have a clear picture of what their viz tool will actually cost.
Miscalculating the cost vs. benefits of your viz tool can severally damage company buy-in so do your homework and get it right!
We often see people use one viz tool and have problems, then switch to another tool expecting different results. But the underlying problems remain the same, so they continue to struggle. It’s a huge waste of time and money.
More often than not, the problem usually isn’t tool-based.
So before you jump ship again on your current viz tool, try talking with an expert first.
If any of these 6 roadblocks are tripping you up and you can’t do the coding and development work yourself, Xerva has an affordable done-for-you report writing solution.
Think of it like us holding your bike until you’re ready to peddle on your own.
The service is just $50/hour – much more cost-effective than the consulting offered by the viz tool companies. We keep our rate low so you can have a long-term relationship with us. You can come to us for help whenever you need it without going broke!
Nate McMurtrey loves using data to solve business problems. He is a Business Intelligence expert, data warehouse wizard, and pioneer in Done-For-You data warehouse solutions. He has worked as a BI manager and freelance BI consultant. In 2014, he co-founded Xerva with Nate Allphin.