The hype around process intelligence kicked into overdrive in 2020. From investments to acquisitions to products, it was an exciting year by any measure. But 2021 promises to be filled with even more hype – and confusion – in the market as vendors look to capitalize on the growing interest from major companies.
Fueling this interest in enterprise process intelligence is the continuing focus on digital transformations. The COVID-19 pandemic forced companies to rapidly modernize how their businesses operated. As early as April, the massive shift to remote work and education turned previously manual processes into digital efforts. Microsoft’s CEO Satya Nadella said that the company saw “two years’ worth of digital transformation in two months.” But that transformation obviously didn’t end in April. And, now that managers and executives have experienced this level of speed and flexibility from their teams, there is no way they’ll move backwards once offices reopen in 2021.
But it’s not just digital transformation that’s going to drive process intelligence in the new year. Enterprises are finding more process automation opportunities to accelerate the shift from low- to high-value tasks for their workforce. Cybersecurity teams are putting suppliers under the microscope, especially as the number of vendors claiming process intelligence capabilities continues to grow and data privacy concerns increase. That growth is driven by market demand too, as more business functions seek process automation solutions and more innovative technologies are appearing in the market.
To help distinguish the 2021 signals from the noise, here are five predictions for process intelligence in the coming year.
Process intelligence growth rate will exceed that of RPA. For the past three years, RPA has been the fastest growing software category in the enterprise market. It exploded from $518M in 2017 to $1.6B in 2020, and is expected to hit $1.9 billion next year, according to Gartner. While the spending arrow will continue to trend upward and the overall market size will dwarf process intelligence, the new king of enterprise software growth in 2021 promises to be process intelligence. Companies are quickly realizing that RPA without process intelligence limits the value, blocks sustainable benefits, and typically requires rework. Process intelligence will become the natural prerequisite to RPA, and the annual growth rate will approach 50% next year with the overall market size exceeding RPA in 2025.
Data privacy concerns will influence vendor selection. As the market transitions from point process intelligence deployments within a specific business unit to wider adoption across an enterprise, the issue of data security and privacy will become a bigger issue. CISOs and security teams will be involved in more evaluations and suppliers will face greater scrutiny. It will not be enough to simply offer allow and deny lists of applications. Suppliers will be required to mask sensitive corporate data and personally identifiable information (PII) to meet requirements.
Big enterprise software vendors will jump into the process intelligence market. One of the major enterprise software leaders, such as Oracle, SAP, Microsoft or Salesforce, will begin adding process intelligence technology natively into their platforms. This past year witnessed substantial interest from these companies in RPA technology, and 2021 promises a similar response in process intelligence. Their major customers are looking to address the process gap that exists in their own organizations, and the leading software vendors will look to fill the need as they have done in the past with ERP, CRM and RPA.
Process intelligence will converge with complementary tools. As process intelligence is essentially a diagnostic solution, it requires connections to other solutions to deliver the expected outcomes. Companies are looking to piggyback on the excitement in the software category with complementary solutions to drive exponential results. Each product can deliver value, but more total value is achieved when the solutions are used together. Workflow and AI/ML providers are the most logical partners as companies look to accelerate strategic initiatives with process intelligence. RPA is the most logical connection, and we already see solutions like Power Automate and Blue Prism establish connections. Valuable integrations will be made with customer experience and compliance technologies as well starting in 2021. Companies now have a unique and previously inaccessible data set of operational activity to search for patterns and streamline tasks across a variety of initiatives.
Enterprises will move beyond financial and accounting opportunities. Nearly every process mining demonstration or case study available is centered around financial and accounting services. Whether it is Order to Case (O2C), Procure to Pay (P2P) or Record to Report (R2R), process intelligence vendors seem unable or unwilling to expand their vision. What’s more likely is their technology struggles to address less structured business activities. To truly support the enterprise and grow the market, vendors will need to provide benefits for both front-office and back-office activities. This coming year will see more examples of process intelligence in new and novel areas of the business, such as talent management and data analytics.
What Do You Think?
That’s what we think is going to happen in the new year. We’ve put a lot of thought into these but would love to hear what you think. Do you disagree with any of our predictions? Are there others we missed? Don’t be afraid to let us know what you think 2021 has in store for process intelligence. Share your thoughts with us on Twitter and we’ll be sure to respond, or send us a note at firstname.lastname@example.org.
Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we investigate how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We strive to make each episode intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world.
In episode #3, my guest was Doug Henschen, Vice President and Principal Analyst at Constellation Research. Doug has a unique view of the business world, since his firm is focused on helping early adopters leverage disruptive technology. The top 5%, as he puts it. In our conversation, he shared what those pioneers are doing in process orchestration, how it helps companies manage new information, and how AI can elevate the customer experience. And, believe it or not, we talked about Domino’s Pizza. But we started with a look at the digital transformation acceleration that’s happened across 2020.
“We often hear that in the last six months, companies have done more digital transformation than they did in the past six years,” said Doug. “It’s all about getting more agile, getting more data-driven. It’s put the move into the cloud on steroids. The companies that are ahead of the curve are in a good position.”
But being ahead of the curve takes more than just moving to the cloud, according to Doug. Every company is swimming in data these days. So there’s a dire need to manage that data, understand it, and put it to use in valuable, impactful ways. But it’s going to take a mix of technologies and humans to do it well, and the approach has to be unique to each enterprise.
“I think we’re going to see platforms on which people will start to build very custom applications,” Doug explained. “Instead of these standardized enterprise applications, they’re going to build more and more. (Their needs are) just too unique to the organization to have a commercial software vendor provide that application. Companies are going to be using this mix of technologies to build their own applications and experiences on top of what I’d call intelligent orchestration platforms.”
Of course, humans will lead the orchestration, but it’s becoming more and more clear that machines will be part of the decision-making process. Doug noted that it’s been almost a decade since IBM’s Watson won on Jeopardy. But the promise back then of artificial intelligence (AI) leading us to huge advancements has yet to materialize. Instead, much of the context behind the data or alongside the decision remains understandable only to humans. So AI might make a recommendation that humans then use to make a better decision. But that then invites human bias, errors, and inconsistencies.
“It’s not just about the data; you really have to know something about it,” added Doug. “It’s the metadata around that data. Who is this customer? What is their history? What is the stage of the process they’re in? When did we talk to them last? Do they have a service issue that’s unresolved? Are they near the end of their contract? It’s not just data, it’s the context around the data.”
“That’s one reason I’ve been doing a lot of research and been advocating embedded approaches of next-generation applications that bring the data and the context right into the context of the application. You have both a human understanding and machine understanding, and you can drive better actions, whether those actions are carried out and executed by a machine or by a human.”
Doug gave a great example of this type of contextual understanding using Domino’s Pizza. They’re taking an innovative, data-driven approach to not just back-end ordering, inventory, and operations, but also using those same insights to elevate the customer experience with increased visibility and interactivity. Progressive financial services institutions, such as Capital One and Rocket Mortgage, are doing the same, and crushing the competition with a stellar customer experience based on data and context.
Again and again, we’re seeing that AI is at its best when used to augment human abilities, especially in human-to-human interactions like customer service. Technology is a huge help, and it takes much of the burden off of workers, making them more efficient and productive. But, in the right context, there’s not yet a match for putting a real human on the line with a customer in need.
“Sometimes you might have to take the (digital) agent offline and switch in the human because something is happening dynamically in the business environment,” said Doug. “That’s what we see ahead. The progress is now happening, where it’s overall monitoring of the process, not just adding more and more bots to have silos of automation.”
There’s much more to my conversation with Doug on the hello, Human podcast. You’ll also hear his favorite resources for staying current on the latest technologies. Or, you can read the full podcast transcript here.
Our podcast, hello, Human, features the leading builders, explorers, and warriors of AI. Together, we explore how they’re putting AI to work to transform enterprises and make sustainable progress on automation, privacy, business disruption, human-bot teaming, and much more. We want each episode to be intelligent and engaging, with the ultimate goal of improving your understanding of the opportunities AI can bring to your business and our world.
Episode 2 – Turning Talent into Competitive Advantage
In this episode, I welcomed Kamal Ahluwalia, President of Eightfold AI. The company’s Talent Intelligence Platform helps organizations retain top performers, upskill and reskill their workforce, recruit top talent, and reach diversity goals. But what makes their solution different is the use of deep learning artificial intelligence. The company’s technology scours publicly available information from around the globe to understand what people are truly capable of doing, which enables companies to then hire, promote, or reassign based on potential.
“Resumes are all backward-looking,” said Kamal. “What people are looking to do, and how we want to use our AI expertise, is to allow the hiring companies to hire for potential. What we have done with our data-driven platform is that we should be learning from all the skills and capabilities that are out there.”
As Kamal explained, the past work of any individual needs context, but also doesn’t necessarily dictate what you can or can’t do in the future. Determining that context is important, but first they need to understand what defines the context. And, even in that same context, different people have different career goals and aspirations. Eightfold’s technology works to understand all of these combinations, and adds intelligence to help reach diversity and inclusion goals, too.
“If we keep looking for people who have already done it before, clearly, we haven’t given enough opportunities to people of diverse backgrounds and people who don’t have the same privileges we have had,” said Kamal. “This applies to pretty much every segment. The way to get out of that is to look at the whole thing holistically. Our algorithms don’t take anything into account, whether it’s sex, background, ethnicity, pedigree, any of those things when an individual is being compared to a particular job. So when we are presenting these few people who are a great fit for a role, it is only based on what they’re capable of doing.”
Eightfold’s technology further helps companies create job descriptions that eliminate bias and focus on getting the right person in the right role. But it also helps identify current employees who would fit that profile, are likely to want to make a move, are in diversity segments, and more. It all helps companies course correct as they fill open roles.
“Our customers have improved the diversity from 18% to 33% for women,” added Kamal. “Other customers have seen a 90% reduction in time to discover and engage with underrepresented candidates. In all aspects, the number one excuse that is often used is, ‘We looked, but we couldn’t find enough capable people of diverse backgrounds’. We want to use our AI to show that no, you didn’t know how to detect the potential, and we are here to help you.”
The technology created by Eightfold works for job seekers just as well. Applicants can be shown open roles for which they’d be a great fit, whether they’ve considered them or not. And that helps them apply with confidence while increasing diversity applications.
Kamal and I also discussed the impact of remote work on future recruiting trends. Now that companies are going to be more open to hiring remote workers, it’s going to allow them to increase the size of their talent pool. Naturally, that also increases the number of potential candidates with diverse backgrounds.
Using AI to help improve how HR works is another area where Eightfold adds value. And a large part of HR’s job is to focus on culture, employee satisfaction and wellbeing, and more. It also helps identify a company’s internal influencers.
“More and more people are being forced to rethink their business, and there is more need for digital sales, data scientists,” Kamal explained. “People are realizing that it’s not like all these markets are littered with that talent, so let’s focus more on the employees. What we are doing with our AI platform is we provide a talent marketplace or a project marketplace where the company can post projects. The important part is how do we get some of the rockstars to participate, and how do we find the experts so that we start building this self-service environment where people want to be appreciated, they want to learn more, or they want to learn from others who are recognized in the companies as being experts?”
The need for specialized talent continues to grow, but the pace of change in the workplace and in technology seems to be in constant acceleration. The situation becomes even more complicated when you factor in the shift to more remote work. Eightfold is taking a unique approach to helping companies fill roles faster with the most qualified candidates. That’s good for everyone, and we’re excited to see how their AI will continue transforming the ways companies attract and manage talent as a competitive differentiator.
Hear the entire conversation with Kamal on the hello, Human podcast, and learn his favorite resources for staying current on the latest technologies. Or, you can read the full podcast transcript here.