Newly published research shows that companies aren’t getting the most out of their analytics. Companies surveyed by Harvard Business Review Analytic Services (HBR) report that two of the most important strategic benefits of using data analytics are (1) identifying new revenue and business models and (2) becoming more innovative. But there’s a gap between expectations and reality, and companies are falling short of their aspirations.
“39% of companies want to identify new revenue and business opportunities with data analytics. Only 23% can. 30% want to be more innovative. Only 14% are.”Harvard Business Review Analytics Services Pulse Report for Sisense, March 2021
Infusing analytics everywhere and building analytics experiences for everyone are the future of data and business. With that in mind, we asked some of our leading thinkers why so many companies aren’t getting what they want from their analytics and how the right analytics platform can help them do so.
Why don’t companies get what they want from their data?
Companies have big dreams of making every decision data-driven, but there are many obstacles to making this vision a reality.
First, there’s the issue of user adoption rates. The HBR study states:
“Just 16% of respondents said their organization’s rank-and-file employees have access to analyzed data. And less than a quarter (24%) of respondents rate their organization’s effectiveness in using analyzed data above seven on a 10-point scale.”Harvard Business Review Analytics Services Pulse Report for Sisense, March 2021
“Analytics doesn’t deliver value when it isn’t tied to a business outcome or to the ecosystem of internal stakeholders, customers, and partners,” says Charles Holive, Sisense Chief Monetization Strategist. “The primary focus should be adoption, which only comes from furnishing users with actionable intelligence that delivers quantifiable business outcomes.”
But there are practical challenges behind the issue of adoption that make getting these actionable insights complicated, slow, and unwieldy. The biggest of these is access to data. Scott Castle, Sisense VP and General Manager, Internal Analytics Products, pointed out that often even when the data is there, either you can’t get access to it or it’s not easy to find and analyze. Even if the data’s available, it can take days to get it from an IT gatekeeper, and once people do get access to data, they often don’t know what to do with it.
As the HBR report concludes,
“Even when employees have access, it’s often too slow to be useful. A majority (57%) of respondents say non-IT/data analyst employees are occasionally, rarely, or never able to quickly access the data they need. Only 9% say employees are always able to access the data needed to accomplish a task quickly.”Harvard Business Review Analytics Services Pulse Report for Sisense, March 2021
The technical challenge
From a technical perspective, it’s often challenging to connect all the sources of data needed in order to get a complete answer, and the time and expense of wrangling these data sources can be prohibitive, despite the possible benefits.
“If I want to know whether my spend on specific marketing programs has an effect on product usage and long-term retention, I have to get data from my website, campaigns, an attribution funnel, product analytics, and my customer success CRM data, and I need to connect all those elements together,” Scott says. “This usually requires time from data engineering, data analytics, marketing ops, and sales ops — more than I’m usually willing to spend — but the answer might really transform my business if I could afford it!”
Some of those hurdles are overcome via dashboards, but they sit in a system several layers removed from anything that many people normally interact with. So, when organizations expect people to make data-driven decisions, they have to go through multiple steps to find the data — and hope that the right insight is even there. Once users have navigated to a dashboard, they need to distinguish their desired data point from within a lot of noise. Thereafter, they have to go back to whatever they were doing in the first place and use that data. It’s an inefficient and unwieldy process.
Why do efforts to find new revenue streams and increase innovation with data fail?
Our experts identify two primary routes to success when it comes to increasing innovation or finding new revenue streams. The first is data utilization: properly leveraging customer, product, and market data to understand how to drive product development. Good data utilization can simply be described as using your data on your customers to know them well and understand their needs, and then creating something of value for them. This is in line with the HBR survey results that indicate the broader the access to data within an organization, the more strategic the benefit. The survey observes:
“Companies where 40% or more of the workforce has data access were 19 percentage points higher in reporting new revenue streams as a top benefit from data analytics investments.”Harvard Business Review Analytics Services Pulse Report for Sisense, March 2021
The second route to success is innovation to stay one step ahead of the competition. This could involve building a new product line or a new feature, such as infusing analytics into an existing software product. Data can also help uncover insights from your customers; for example, maybe there is a small segment that is loyal yet underserved by your products or services that could allow you to enter a new market.
When it comes to using data to increase innovation, Charles is a proponent of making organizations into what he calls “revenue stream innovation factories.” To achieve this, he says, companies should find ways to lower the cost of experimentation, decrease the time to value, and scale successful experimentation into products quickly. To build new revenue streams, the end user is the customer or the partner, so innovation must be initiated within the customer-facing teams of customer success, sales marketing, or externally focused product teams.
One note of caution, however: Data utilization and innovation are areas where businesses often fall short. According to the HBR report, less than 49% of respondents say they are driving innovation with data, partly because data must be brought together in a usable format and often it doesn’t happen. If you don’t achieve this, you can’t drive market disruption. Businesses need to think beyond the dashboard and bring intelligence to their teams. Embedding dashboards into top business applications is one way to start, but to drive full data adoption, data needs to be infused into processes and workflows as well.
What are examples of companies that have done these things well?
In the healthcare sector, Billing Savi has done a great job of monetizing data to drive revenue, partnering with customers in the sector to improve patient care and creating new opportunities for its customers. Luma Health has leveraged analytics to help fight the COVID-19 pandemic, using machine learning and AI to enable healthcare providers and their staff to better communicate with and listen to patients, improve appointment scheduling, and implement screening solutions to patients.
UiPath, the pioneer in robotic process automation, has used data and analytics to better understand customer needs, learn how data could empower them, and increase the stickiness of its products. As a result, it has been able to unlock the opportunities of enterprise-grade automation and worker productivity and creativity while embracing the digital transformation process.
Personal audio powerhouse Skullcandy illustrates how analytics can drive product innovation, using predictive and sentiment analysis to better understand how customers behave, as well as likes and dislikes. Then the company uses intelligence from a huge well of structured and unstructured data to modify the design of new products before going to market, in order to enhance product offerings and the customer experience.
Mastering fundamentals today to thrive tomorrow
These examples illustrate why harnessing data and maximizing its accessibility is so critical for businesses. Achieving this effectively requires every business and business team to clearly answer four questions:
- What are your objectives/goals?
- How do you get to your targets?
- What data helps with that?
- What actions do you take with that data?
With definitive answers to these four questions, you can find the right tools and strategies to help you achieve your business goals.
Charles said companies must evolve from data-driven to value-driven: “On the go-to-market side, focus on outcome selling, and more specifically financial outcome selling. That means that you must infuse analytics into your solutions or as new standalone commercial offerings, in order to expose the financial outcome of working with you [top-line and bottom-line impacts].”
Guy Levy-Yurista, Sisense Chief Strategy Officer, expresses it even more plainly.
“Companies must infuse data into their strategies, services, and products if they want to thrive and survive.”
Infusion is the way forward, but why?
We learn from the HBR survey that companies are missing huge data-driven opportunities and significant intelligence by not making analytics an integral part of the way they work.
“Only 14% [of respondents] report that data analytics are built into nearly all employee tools/workflows. While 17% say data analytics are built into few or no workflows, most responses fell somewhere in the middle: 35% say analytics are in over half but not all workflows; another 35% say analytics are in less than half but not zero workflows.”Harvard Business Review Analytics Services Pulse Report for Sisense, March 2021
Yet infusing analytics into your regular workflow is the way to get more from your data and get ahead of your competition because it breaks typical barriers to analytics adoption and provides a more natural way to think about and consume analytics. “It’s the one that hits the easy button for people,” says Mindi Grissom, Sisense Director of Product Marketing.
“Years ago, they put calorie counts on menus. I really see this as one of the first data-driven infusion points. Now, if you go to Starbucks, you make a data-driven decision without even knowing it. You see that your choice has 400 calories, and maybe you skip the whipped cream to get it lower. It’s small changes like this that add up, and when intelligence-informed decisions are naturally infused into a process, it no longer becomes a ‘thing’ you have to solve. You just are data-driven.”
Infusion also overcomes the skills gap. It’s already clear that the companies that best use their data will be the ones to disrupt their markets. And the ones that overcome the people and process challenges of data adoption will do so first.
Charles articulated this in a 2019 article in which he considered invisible analytics and embedded insights to be the future of business intelligence. He wrote that analytics, infused into your regular workflow, goes beyond dashboards because it delivers what we really want — an answer, right when we need it, where we need it, that we can act upon immediately. No more time-consuming interpretation nor the involvement of data teams. No more distractions of switching away from your core work to use analytics and dashboards. Infused analytics can become a seamless part of your workflow, and that of your customers, revolutionizing our ways of working and our decision-making. In short, if you want your organization to flourish now and in the data-driven future, infused analytics is unavoidable. Guy concludes:
“Consider how, at the start of the dot-com era, if a company hadn’t got a domain and a website, they would have been out of business by 2005. Presently, we’re in a similar place with data and analytics. If companies don’t infuse analytics in their operations and their offerings now, then I predict that they’ll be out of business in five years. It’s all about the data, and it’s do or die.”
Adam Murray began his career in corporate communications and public relations in London and New York before moving to Tel Aviv. He’s spent the last 10 years working with tech companies like Amdocs, Gilat Satellite Systems, and Allot Communications. He holds a doctorate in English literature. When he’s not spending time with his wife and son, he’s preoccupied with his beloved football team, Tottenham Hotspur.