Are you looking to make your business more efficient and profitable? Business intelligence (BI) is a powerful tool for achieving this goal, but it can easily fall into bad habits that can hinder your success. To ensure your BI project is a success, you must pay attention to data quality, use the right BI tools and avoid common pitfalls.
As technology continues to advance exponentially, businesses are looking deeper at how they should treat ever-evolving forms of BI.
Here are some of the biggest mistakes to avoid when it comes to generating, using and handling BI today. Many of these have to do with two overarching things:
- Managing the big data that is now common in business systems.
- Working with new forms of artificial intelligence (AI) and machine learning (ML) that are revolutionizing the kinds of BI that businesses are able to obtain. (Also read: The Ultimate Guide to Applying AI in Business.)
Considering these best practices will help a company make sure it is getting the best insights possible from its data assets. Many of these ideas contemplate the “big picture” of handling data in a complex architecture, where things can sometimes fall through the cracks.
The most important step in using BI effectively is ensuring the data you are working with is of the highest quality. Poor quality data can lead to inaccurate insights, which can ultimately damage your business. Make sure you have a process in place to regularly audit and test your data for accuracy and completeness.
Here are five bad business intelligence habits to avoid at all costs:
1. Ignoring Silos
With that in mind, there’s no reason why businesses should still have important data sitting in outdated legacy silos. So, the best practice for business intelligence is to connect everything well, to set up the system so data can flow to where it’s most useful. If that’s not intuitive, given a company’s organizational chart, leaders should change that. Setting up a point person to handle data flow can produce amazing results! (Also read: Data Silos: What They Are and How to Deal With Them.)
One excellent tip comes from a Forbes piece wherein writer Christian Ofori-Boateng recommends having a business intelligence blueprint that includes things like historical data and organization and industry KPIs.
This resource will show how data will move to the point where it can be useful in generating insights decision-makers will use.
Communication is important, too.
“It is crucial that at least one upper management executive is on the business intelligence team,” writes Ofori-Boateng. “Too often, communication fails between the business intelligence department and upper management when a key executive is excluded from the business intelligence division.”
With the right staffing and approach, firms can ensure that data is ready to go to where it can be made into key BI. Otherwise, that asset is just sitting in a dead terminal, in limbo, and not able to contribute to better business.
2. Failing at Data Governance
Data governance is similar to minimizing silos in the realm of modern business intelligence, but it’s more focused on across-the-board standards. Does your company have any kind of data governance plan in place at a comprehensive level? (Also read: What are some core principles of data governance?)
Data governance has a lot to do with managing compliance to rules like the GDPR — and making sure that data handling standards are consistent and universal. But it also has to do with business intelligence: Better data governance protocols and standards are going to improve how the business handles its BI assets.
3. Leaving Data Unmarked
We now have all sorts of neat new AI tools to address unstructured data and make it structured. Businesses can also use modern concepts like a data catalog for annotating and describing different data assets that may be held in databases, middleware systems or elsewhere in a network.
Some people talk about a data catalog as “metadata about metadata.” Whether you have one or two layers of metadata is less of an issue than whether the business has moved to create labeling and tags for data that will let everybody know what data is in what bucket!
As businesses move toward an “itemized” understanding of what data they have, it helps them conceive of how critically important that data is to their operations. That, plus good categorization, promotes an organized effort to use BI constructively.
4. Skipping Failover and Redundant Systems
In terms of maintaining access to data, failover systems are paramount.
Now that most businesses have some kind of elegant BI infrastructure, they want to maintain and guard it. Redundant systems can help with disaster recovery or even ransomware attacks by making sure that, if something happens to data set number one, data set number two gets routed from a remote location, and everything keeps humming away. (Also read: 5 Benefits of Hyperconverged Systems for Your IT Strategy.)
5. Poorly Targeted Dashboard Design
What about separating the signal from the noise?
Consulting firms operating in today’s business environment suggest that, with so much data floating around, and so much architecture complexity, businesses can suffer from having unnecessary items in a report or a visualization.
Data visualization is, in itself, a best practice. But cynics would say it depends on what you are looking at. Taking the extra time to target the dashboard and reporting tools correctly can pay big dividends.
Think about how these important warnings apply to your business. (Also read: Is Your Organization Aware of These 6 Key Public Cloud Risks?)
By investing in these five pillars of modern business intelligence, companies will avoid the pitfalls that can compromise what they have at the ready to compete and serve customers every day.
Companies need to stay ahead of competition and deliver the best customer service. But without modern business intelligence, they risk making decisions based on outdated information and missing out on opportunities. Investing in the five pillars of modern business intelligence is essential for staying competitive and providing customers with the best experience possible.