6 Data Productivity Questions to Ask Your Enterprise

BI tools from a decade ago are complex solutions that would only be approached by skilled professionals, set up by IT, and of use only to the C-suite. These solutions created data silos within organizations, slowed down operations, and were expensive to set up and maintain. As we enter a new world of cloud-based purposeful BI tools, it’s time to put every BI solution under the scanner and reassess what is expected of them. Let’s look at 6 ways every organization can use to drive org-wide adoption of their BI tool.

1. How quickly can you do ad hoc analysis?

Traditional BI tools were most widely used to create dashboards to track the frequently accessed data and the most important KPIs of the organization. This is essential and still required. However, when it comes to ad hoc analysis and looking for a specific piece of data to make a day-to-day operational decision, these tools fall short. You need to jump through hoops, type in complex queries, tweak results indefinitely, and navigate through a clunky interface all the while. By the time the user finds their answer, they’ve forgotten why they needed the data in the first place. This is counterintuitive. If you rely on a business analyst, the response can take days to come depending on how busy the analyst is, and your seniority in the organization. 

Today’s BI tools need to be fast and deliver ad hoc insights in 1 minute. This requires the tool to understand what the user is looking for and be able to deliver a result immediately. It makes the tool sound almost human-like, and that’s what is possible if technologies like artificial intelligence and machine learning are employed by BI tools. A BI tool that can understand natural human language are new to the world of BI, but can get ad hoc analysis done in a matter of minutes.

2. Is your data speaking your business reality?

Every organization has its own unique jargon when it comes to data. One organization may call it ‘tickets’ and another calls it ‘issues,’ one organization calls it ‘leads’ and another calls it ‘contacts.’ Similarly, when you use the word ‘sales’ does it include data from all sales channels such as online, retail, partners, etc. Sometimes a single word can have more than one meaning, and many different words can mean the same thing. The BI tool needs to understand your company’s unique jargon.

In the past, BI tool users would get lost in translation trying to keep up with organizational lingo and the inflexibility of the BI tool they use. Not anymore. BI tools of today need to be nimble and perceptive enough to understand and adapt to the jargon of the organization. 

Modern BI tools need to have the ability to customize the labels and categories used to identify data. BI tool users should feel free to use the exact jargon they use internally when talking to their BI tool. The tool should adapt to the user, not the other way around.

3. Is your BI tool flexible and scalable?

BI tools typically focus on connecting to a data source, supporting complex queries, and enabling some visualization via the user interface. It’s up to the BI personnel to run complex queries that wield the full power of the BI tool and find their answer. This puts all the burden on the BI tool user. 

A BI tool for today should do the heavy lifting of capturing and organizing data and keeping it ready for analysis. The way this is done is by using metadata. There are many advantages of having a metadata layer – it is much smaller than the original data set, it acts as a map to quickly find the needle in the haystack, and it protects the original data from getting tampered with. The biggest benefit of having a metadata layer is that it speeds up analysis by enabling shortcuts to the data.

4. How easy is it to deep dive into data?

BI tools have static dashboards that present data in just one way. If you want to view the same data in a different way, you’d be scared to mess with the settings of the dashboard. Only the most skilled BI folk would dare to venture away from the pre-set dashboards and create a different view of the same data. 

A modern BI tool should invite users to play with the data they’re viewing and discover new insights easily. This means they should be able to change the chart type from a line chart to a bubble chart with just one click. Further, the BI tool should be intelligent enough to allow only those changes that the data itself supports, and hide those views that aren’t conducive to the present data. Every chart should be interactive, and enable drilling down into the data for deeper analysis. 

Rather than snoozing on a decision till the next meeting when the analyst gets the required data, you should be able to quickly pull up the required numbers yourself. If it takes you a couple of clicks and around a minute to pull up the data, you’d gladly do it. However, this is a tall ask and most traditional BI tools would fail this test of agility.

5. Is your BI enabling seamless collaboration?

The problem with complex BI tools of the past is that they limit the power of data within an organization. If only IT can customize the tool, and only trained BI professionals can run queries on the tool, the tool is out of reach of executives, middle managers, and frontline operational staff – that’s more than 95% of the organization. 

Today, organizations should demand that their BI tool allows non-BI folk to be able to use it too. This means a CFO who wants to know how many orders came in from tier-2 cities for the past 6 months and the 6 months prior to that should be able to log into the tool and find the answer themselves in under five minutes. A manager who wants to see how many tickets were closed by their team before and after a product release should have that information in under five minutes without having to contact BI. A frontline staff who needs to view a specific metric should be able to create a dashboard on their own within five minutes without contacting IT. 

This doesn’t mean that the BI tool should be dumbed down for lay users and be of no use to BI professionals. Rather, BI experts would also benefit from these improvements as they can expect executives and others to find answers to most data questions on their own, and rely on the BI team only for the most complex analysis. The BI team can avoid the mundane sweat work and focus on high-value contributions to the organization.

6. Is BI welcoming for new users, teams & business units?

Last but not least, BI tools should enable collaboration. In the past, BI tools were good for generating static reports that were emailed as attachments, and the discussions would happen over email. This is a compartmentalized experience for users. 

In a world of social media and commenting, BI tools should allow for collaboration around reports via comments. This would be more engaging for users. It would make the data more effective, and encourage deeper analysis of the data that’s being discussed. Further, scheduling and sharing reports shouldn’t be possible from the frontend interface for all users and not hidden for administrators alone. 

Further there should be support for new users who are learning to use the BI tool. This would include a knowledge base, onboarding documentation, webinars, office hours with experts, and even internal buddies who can help newbies get up to speed with the BI tool. Most BI tools leave you orphaned to figure out their complex interface on your own.

A handy scorecard

Here is a useful scorecard to help you rate your BI tool today:

If you’ve answered ‘No’ to more than two of these questions, it’s time you took a long hard look at your existing BI tool, and consider a change.

Wrapping it up

In conclusion, BI tools are set to be disrupted in a modern cloud-native world. Expensive and elitist platforms that keep data analysis out of reach will be passé. They will be replaced by more nimble agile alternatives that democratize data, break down walls between teams, get non-BI folk interested and talking about data in the hallways, and greatly quicken the time from data to insight.

Orcablue – An enterprise-ready data assistant for everyone

At Orcablue, we’re building a modern BI solution that follows these principles and liberates data from the confines of traditional BI tools. Orcablue is a data assistant that can understand queries such as ‘how many sales did we have from New York in 2019 QoQ.’. It can understand all your data sources, metrics, business rules and more with effortless automation offered as an agile subscription for businesses. Further, with mature visualization and collaboration capabilities built-in, makes working with data intuitive and effortless for your entire organization at 90% lower costs and efforts. Get a demo of Orcablue today and put the intelligence back into BI.

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