Q&A: Is it time to step away from self-service analytics?

We discussed the discrepancy between IT and end-users’ perceptions of how BI tools are being used.

Logi Analytics helps companies embed analytics into their applications. The company’s recent research into the state of analytics adoption found that there is a discrepancy between IT and end-users’ perceptions of how BI tools are being used. 

We recently spoke to Tom Cahill, VP EMEA at Logi Analytics to discuss why these discrepancies exist and how self-service analytics can still have a place within organisations without causing disengagement amongst IT and users.  

What are the biggest challenges both IT and end-users are facing when it comes to analytics? The biggest analytics challenge for IT right now is that users are not adopting the analytics solutions they are providing. End users don’t want to adopt these tools because they find them difficult to use, they don’t like switching over from their usual applications to separate analytics tools, and don’t have easy access to analytics tools in their daily workflows.   That means IT is continuing to be bombarded with ad hoc report requests, and/or needs to regularly educate users on the tools – taking time away from other projects they need to complete.   

Why do you think there has been a drop in end-user adoption of self-service analytics over recent years? And why do these discrepancies exist?
For more than a decade, traditional business intelligence adoption has hit a ceiling of about 20 to 30 per cent. So over the past few years, we’ve seen data discovery vendors spending millions to reduce end-user friction and make those tools easier for everyone, regardless of skillset, to use. Yet, our research shows adoption continues to decline – down 20 per cent since 2014.   

What this tells us is that those savvy data analysts who want and use data discovery tools have already adopted these solutions. And the broader market either does not see the value these tools offer or has tried them and disliked them—in large part because users don’t like being forced to open standalone applications to analyse their data. It inhibits their ability to readily see strategic business insights, which is why more and more knowledge workers are actively stopping use of these solutions.   

Business users want to stay in one place, not jump from application to application to get what they need. But so many analytics tools fail to meet this need.    

What are the outcomes of end-user disengagement? And what are the key things organisations need to change in order to stop these discrepancies happening?  
Leaving current workflows and opening standalone applications to analyse data is inefficient and outdated. According to our 2017 State of Analytics Adoption report, 84 per cent of business users agree, saying it’s important for them to be able to access analytics embedded within the applications they’re already using.    What that tells me is that organisations need to stop making their users work with tools and have the tools work for the people. In other words, it doesn’t matter how simple the tool is, if a user has to go outside their usual workflow to use it, there is going to be friction.   

All application owners, including product managers at software companies and IT leaders in enterprises, need to look into embedding analytics into users’ workflows.   

Today, embedded analytics can be interactive, offer drill-down and drill-through capabilities and even provide self-service to end users that need to answer questions they haven’t yet thought of. The future of embedded analytics goes beyond these capabilities – ultimately allowing for the analytics and the application to talk to each other and kick off workflows, further reducing the need for users to ever leave the apps they use daily.   

How can self-service analytics still have a place within organisations without causing disengagement amongst end users?
Self-service is still very important for all organisations to consider. But it’s how those capabilities are delivered that can be the difference between an application being adopted or ignored.   

Data analysis is no longer relegated to a few highly trained, technical people. Today, everyone is expected to be a “data expert” in their own domain so they can make intelligent decisions that drive business forward. But every user is different – in role, skills and analytical needs. That’s why it’s important to tailor your analytics application to those users, so they can access and analyse data how they want to, in the moment they need it. Some users may prefer basic reports, but other users will demand the flexibility to visualise data on their own and create formatted output such as dashboards and reports.    

Organisations need to focus on delivering those tailored insights in the moment that users need to make a decision – and that means embedding analytics within the applications they use every day. When users can simply view insights the way they want, and take action within the applications they already use, they are much more likely to adopt the analytics tool.   

What is embedded analytics and how does it differ from traditional BI and analytics tools?
Embedded analytics is the integration of analytic content and capabilities within the applications people are already using on a daily basis, such as their EHR, CRM, or marketing automation apps.   

The goal is to help users work smarter and more efficiently by incorporating relevant data and analytics in context of their workflow. This is in contrast to traditional BI, which focuses on extracting insight from data within the silo of analysis.   

Traditionally, BI is a set of independent systems (technologies, processes, people, etc.) that aggregate data from multiple sources, prepare the data for analysis, and then provide reporting and analysis on that data from a central view point. It is most optimised for supporting management-level decisions that require highly aggregated views of information from across a department, function, or entire organisation. These systems are specifically designed for people whose sole responsibility is to perform data analysis.   

Embedded analytics on the other hand can be tightly integrated into existing applications and bring additional awareness, context, or analytic capability to support decision-making related to a variety of tasks. These tasks may require data from multiple systems or aggregated views, but the output is more than a centralised overview of information. It is targeted information to support a decision or action in the context in which that decision or action takes place.   

What are the main advantages of using embedded analytics within an organisation?
While traditional BI has its place, the fact that BI applications and business process applications have entirely separate interfaces forces users to switch between multiple applications to derive insights and take action.    

Our 2017 State of Analytics Adoption report found that 67 per cent of business users say they have to switch to separate analytics tools to get the data or analysis that they need – something that analysts have said can waste users one to two hours a week.   

Embedded analytics puts intelligence inside the applications people use every day to improve the analytics experience and make users more productive by combining insight and action in the same application. According to our 2016 State of Embedded Analytics report, 94 per cent of independent software vendors (ISVs) and 80 per cent of non-commercial application providers said embedded analytics is important to their users. And application providers stated that 43 per cent of their users use embedded analytics on a regular basis. That’s double the adoption rate of traditional analytics tools mentioned previously.   

Business users want streamlined tools that help them work efficiently. Standalone analytics tools fail to meet this demand, but embedded analytics addresses this demand by injecting analytics right where people are already working.   

What is the future of user adoption?  
Although the availability of self-service offerings will likely continue to grow due to current momentum, the 24 per cent drop in end-user adoption we’ve seen over the past two years is likely just the beginning. As IT teams continue to force self-service solutions on their users, the backlash and user rejection of these tools will continue.    

Historically, commercial ISVs and SaaS providers have embedded analytics in their applications as a way to boost revenue, drive user adoption, and improve customer satisfaction. But over the past few years, non-commercial app providers have also started to see the benefits of embedded analytics for themselves. Their reasons are essentially the same, internal IT teams are able to see huge boosts in user adoption and satisfaction by providing more robust applications.    

At the end of the day, IT teams that provide applications to users within their organisations need to make sure those applications and portals are actually being used. Because when they are, IT teams will be freed up for more important work. 

Image source: Shutterstock/ESB Professional
Tom Cahill, VP EMEA
Logi Analytics