One of the most powerful ways for your organization to get a competitive edge is to embed analytics, because it enables you to go beyond improving internal efficiencies with data. With embedded analytics, you can build strong differentiation, improve customer satisfaction, and drive new revenue streams, by delivering intelligence to your teams and your customers when and where they need it. Nevertheless, it’s often still a big challenge to get the buy-in to fund it and deploy it.

“Transformational, data-driven applications . . . are only being built by innovators and fast followers—the leading 20% to 25% of organizations that are trying to differentiate and transform their organizations. Embedded analytics are often the centerpiece of such applications and services, and . . . the state of the art in terms of analytical functionality [that] will continue to evolve.”

— “Next-Generation Embedded Analytics Spark Digital Transformation,” Constellation Research

That leaves at least 75% of organizations that aren’t embracing the benefits of embedded analytics that could significantly add value to their business and drive growth. Why does this happen, and how can you overcome obstacles to adoption?

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Why is it so hard to get buy-in, and what to do about it?

Gartner’s survey “The Rise of Business-Domain-Led Data & Analytics” indicates that lines of business (LOBs) will become the primary driver of analytics adoption, because business domains are bigger spenders on data and analytics.

So, in addition to IT managers, advanced end users in LOBs are the most important stakeholders for apportioning spend on analytics. However, data isn’t always at the center of their world, so they need to be convinced about the value of embedded analytics. This requires a robust business case for committing their budget to it. So, how do you build a successful case? 

The answer is to understand and respond to the constraints they experience with their current BI and analytics solutions, the challenges they face when seeking to secure budget for embedded analytics, the concerns they have about embedded analytics, and their need for proof points to show their value. 

Current analytics solutions aren’t user-friendly

A common objection that we encounter is that companies experience disjointed workflows with their analytics solutions, because analytics reports are in a different place than where users are working. Users must pause their work, toggle between systems, log in, find the information they want, export it, and then return to their main tasks. Such interruptions to workflow cause understandable reluctance to engage with data and use analytics. 

Plus, each user needs their own account and login credentials to gain access, and there’s often a lack of mobile access, which hinders the availability of analytics to the widest possible audience. In short, access is clunky. 

And this is when you have a good data visualization solution to encourage more self-service analytics. Getting intelligence from data is often even slower, because users must request and wait for reports from their IT or data teams and hope they’re still relevant when they arrive. It’s an unwieldy process.

A serious drawback of existing analytics solutions is an inability to associate outcomes with action. Users want to see how the intelligence from their analytics adds value, and they want to act on the analytics quickly and directly to achieve desired outcomes.

Embedded analytics are the answer to these problems. They infuse intelligence into apps, enabling users to access analytics and gain insights within their workflow, in real time, with no awkward interruptions. The intelligence they receive is immediately actionable and easily available for everyone. The end user experience is smooth. Single sign-on integration and no multiple logins make sure of that. And robust APIs help ensure that workflows are enabled. For example, if data shows a customer a new prospect, an automatic ticket in Salesforce or another tool gets generated, making the actionable analytics process a seamless experience.

Why not upgrade existing platforms instead of buying new ones?

This is a persuasive argument from a functional perspective, and it’s an approach that should extend to further objections about spend. Stakeholders may ask whether there are any existing substitutes to buying a new embedded analytics solution or whether their current platform can’t simply be upgraded. Technical folk might ask whether they can use Angular or React tools, or open-source software such as D3 to produce dynamic, interactive data visualizations.

The main considerations here are scale, volume, and future-proofing. Such tools don’t necessarily scale with a rising number of users and the rapidly increasing volume of data. They can be expensive to maintain and require significant upfront development investment. 

The new generation of embedded analytics has no such capacity issues. You can manage data at scale, deliver real-time insights with live or cached data for rapid prototyping and minimized query costs, and stay ahead of rapid innovation cycles. Infusing embedded analytics enables you to get to market fast, with no or low code. Adopting self-service analytics optimizes and democratizes access and use of analytics, whatever the scale, without compromising performance or agility.

Loosening the purse strings

Of course, there’s always the issue of where and when to get the money. Those holding the purse strings regularly say that budgets are tight, and they ask whether any purchase of a new embedded analytics solution could wait until the next budget cycle.

That’s always a possibility. But delaying means slowing down access to valuable intelligence and overlooking potential growth opportunities. So, it’s important to communicate why you should embed analytics now instead of later. Some tips on how:

  • Create a sense of urgency by showing that competitors are doing it 
  • Calculate how much time, resources, and money could be saved by streamlining your current processes with new analytics
  • Show the shortfall between the modest usage levels of your current analytics solution and the widespread use of an embedded analytics solution, to demonstrate that a new solution would probably be more cost-effective per user than your existing platform 
  • Anticipate how embedded analytics will differentiate your products and improve your customers’ experience, to make your company stand out from the competition 
  • Outline what further opportunities and revenue you could capture for you and your customers
  • Ask your decision-makers how valuable it would be to improve customer retention, profits, and efficiency by 15% now, or wait until the next budget cycle 

Paint a picture of success

Perhaps the toughest challenge to get buy-in is the difficulty in communicating your pain points to leadership if they don’t understand use cases for which embedded analytics are important.

To meet this challenge, you need to show that the advantages of embedded analytics are real and achievable. Making a compelling case requires solid examples of how value is delivered to end users. These come in three ways:  

  • Highlight powerful benefits that embedded analytics deliver
  • Use competitive information, which could be a huge driver for your leadership
  • Illustrate the power of embedded analytics in action, using case studies and customer stories

Persuade with power

These actions can have a big impact on decision-makers who hold the budget: 

  • Demonstrate how users can get insights at the point of use, rather than in a separate, disjointed application. 
  • Show them analytics in action when the user is engaging in important or typical activities. Present to them how embedded analytics integrate workflows with analytics for intuitive application activity. For instance, paying a bill should simultaneously update cash flow, accounts receivable, and any other related information. This highlights how embedded analytics streamlines the process of gathering and sharing insights versus navigating to a new page with reports and dashboards. 
  • Show the simplicity of use and scalability of the analytics solution — the fact that you can extend the reach of your analytics to new users without IT involvement. Explain how it’s possible to cheaply, quickly, and securely embed analytics into any application that’s either proprietary or technology using a platform such as the Salesforce Lightning platform (also known as Force.com).
  • Show users how they can view dashboards and charts on mobile devices. This is particularly persuasive for users in sales and service representatives, who benefit from working with analytics on the go.
  • Find both general and specific examples to illustrate these points, either through your own research, or if you have a preferred embedded analytics provider in mind, work with them to get proof points and case studies. 

And don’t forget perhaps the two most potent tools at your disposal: a demo or an active trial using a sample of your prospect’s own data to see how embedded analytics can be customized for them.

The winning combo to get buy-in

There’s no magic wand you can wave to get buy-in for your embedded analytics deployment, but a combination of understanding concerns, and addressing them with a mix of proof points, examples of general benefits and specific case studies, will help you build your case and put you on the road to success. 

Excited to transform your business with embedded analytics? Check out this special report from Constellation about the next generation of embedded analytics.

Pat Bhatt is Director of Product Management, Cloud Analytics, at Sisense. He has over 20 years of experience in product management and innovation in the tech space, having led product management at Model N, SkyNovus, Intuit, and Silicon Valley Bank.