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Build a digital ops toolbox to streamline business processes with hyperautomation
Reliance on a single technology as a lifeline is a futile battle now. When simple automation no longer does the trick, delivering end-to-end automation needs a combination of complementary technologies that can give a facelift to business processes: the digital operations toolbox.
According to a McKinsey survey, enterprises that have likely been successful with digital transformation efforts adopted sophisticated technologies such as artificial intelligence, Internet of Things or machine learning. Enterprises can achieve hyperautomation with the digital ops toolbox, the hub for your digital operations.
The hyperautomation market is burgeoning: Analysts predict that by 2025, it will reach around $860 billion.
The toolbox is a synchronous medley of intelligent business process management (iBPM), robotic process automation (RPA), process mining, low code, artificial intelligence (AI), machine learning (ML) and a rules engine. The technologies can be optimally combined to achieve the organization’s key performance indicator (KPI) through hyperautomation.
The hyperautomation market is burgeoning: Analysts predict that by 2025, it will reach around $860 billion. Let’s see why.
The purpose of a digital ops toolbox
The toolbox, the treasure chest of technologies it is, helps with three crucial aspects: process automation, orchestration and intelligence.
Process automation: A hyperautomation mindset introduces the world of “automating anything that can be,” whether that’s a process or a task. If something can be handled by bots or other technologies, it should be.
Orchestration: Hyperautomation, per se, adds an orchestration layer to simple automation. Technologies like intelligent business process management orchestrate the entire process.
Intelligence: Machines can automate repetitive tasks, but they lack the decision-making capabilities of humans. And, to achieve a perfect harmony where machines are made to “think and act,” or attain cognitive skills, we need AI. Combining AI, ML and natural language processing algorithms with analytics propels simple automation to become more cognitive. Instead of just following if-then rules, the technologies help gather insights from the data. The decision-making capabilities enable bots to make decisions.
Simple automation versus hyperautomation
Here’s a story of evolving from simple automation to hyperautomation with an example: an order-to-cash process.
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Q3 IPO cycle starts strong with Couchbase pricing and Kaltura relisting
Today we have new filings from Couchbase and Kaltura: Couchbase set an initial price range for its IPO, something we’ve been waiting for, and Kaltura’s offering is back from hiatus with a new price range and some fresh financial information to boot.
Both bits of news should help us get a handle on how the Q3 2021 IPO cycle is shaping up at the start.
TechCrunch has long expected the third quarter’s IPO haul to prove strong; investors said as 2020 closed that quarters one, three and four would prove very active in terms of public market exits this year. Then the second quarter surpassed expectations, with more companies going public than at least some market observers anticipated.
With that in mind, you can imagine why the newly launched Q3 could prove an active period.
So! Let’s start with a dig into the filing from NoSQL provider Couchbase, working to understand its first price range and what the numbers may say about market demand for technology debuts. Here’s our first look at the company’s value. Then we are taking the Kaltura saga back up, checking into the pricing and second-quarter results from the technology company that provides video-streaming software and services.
Frankly, I’ve been waiting for these filings to drop. So, let’s cut the chat and get into the numbers:
Couchbase’s IPO price range
In its new S-1/A filing, Couchbase reports that it anticipates a $20 to $23 per share IPO price. With a maximum sale of just over 8 million shares, Couchbase could raise as much as $185.15 million in its public offering.
The company will have 40,072,801 shares outstanding after its IPO, not including 1,050,000 shares that are reserved for possible release. The math from here is simple. To calculate Couchbase’s possible simple IPO valuation we can just do a little multiplication:
- Couchbase simple valuation at $20 per share: ~$802 million.
- Couchbase simple valuation at $23 per share: ~$922 million.
If you want to include the company’s reserved shares, add $21 million to the first figure, and $24.2 million to the second. Notably, TechCrunch wrote before it priced that using a historical analog from the Red Hat-IBM sale — both Couchbase and Red Hat work in the OSS space — the company would be worth around $900 million. So, we were pretty close.
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What does Red Hat’s sale to IBM tell us about Couchbase’s valuation?
The IPO rush of 2021 continued this week with a fresh filing from NoSQL provider Couchbase. The company raised hundreds of millions while private, making its impending debut an important moment for a number of private investors, including venture capitalists.
According to PitchBook data, Couchbase was last valued at a post-money valuation of $580 million when it raised $105 million in May 2020. The company — despite its expansive fundraising history — is not a unicorn heading into its debut to the best of our knowledge.
We’d like to uncover whether it will be one when it prices and starts to trade, so we dug into Couchbase’s business model and its financial performance, hoping to better understand the company and its market comps.
The Couchbase S-1
The Couchbase S-1 filing details a company that sells database tech. More specifically, Couchbase offers customers database technology that includes what NoSQL can offer (“schema flexibility,” in the company’s phrasing), as well as the ability to ask questions of their data with SQL queries.
Couchbase’s software can be deployed on clouds, including public clouds, in hybrid environments, and even on-prem setups. The company sells to large companies, attracting 541 customers by the end of its fiscal 2021 that generated $107.8 million in annual recurring revenue, or ARR, by the close of last year.
Couchbase breaks its revenue into two main buckets. The first, subscription, includes software license income and what the company calls “support and other” revenues, which it defines as “post-contract support,” or PCS, which is a package of offerings, including “support, bug fixes and the right to receive unspecified software updates and upgrades” for the length of the contract.
The company’s second revenue bucket is services, which is self-explanatory and lower-margin than its subscription products.
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Network security startup ExtraHop skips and jumps to $900M exit
Last year, Seattle-based network security startup ExtraHop was riding high, quickly approaching $100 million in ARR and even making noises about a possible IPO in 2021. But there will be no IPO, at least for now, as the company announced this morning it has been acquired by a pair of private equity firms for $900 million.
The firms, Bain Capital Private Equity and Crosspoint Capital Partners, are buying a security solution that provides controls across a hybrid environment, something that could be useful as more companies find themselves in a position where they have some assets on-site and some in the cloud.
The company is part of the narrower Network Detection and Response (NDR) market. According to Jesse Rothstein, ExtraHop’s chief technology officer and co-founder, it’s a technology that is suited to today’s threat landscape, “I will say that ExtraHop’s north star has always really remained the same, and that has been around extracting intelligence from all of the network traffic in the wire data. This is where I think the network detection and response space is particularly well suited to protecting against advanced threats,” he told TechCrunch.
The company uses analytics and machine learning to figure out if there are threats and where they are coming from, regardless of how customers are deploying infrastructure. Rothstein said he envisions a world where environments have become more distributed with less defined perimeters and more porous networks.
“So the ability to have this high-quality detection and response capability utilizing next generation machine learning technology and behavioral analytics is so very important,” he said.
Max de Groen, managing director at Bain, says his company was attracted to the NDR space, and saw ExtraHop as a key player. “As we looked at the NDR market, ExtraHop, which [ … ] has spent 14 years building the product, really stood out as the best individual technology in the space,” de Groen told us.
Security remains a frothy market with lots of growth potential. We continue to see a mix of startups and established platform players jockeying for position, and private equity firms often try to establish a package of services. Last week, Symphony Technology Group bought FireEye’s product group for $1.2 billion, just a couple of months after snagging McAfee’s enterprise business for $4 billion as it tries to cobble together a comprehensive enterprise security solution.
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For SaaS startups, differentiation is an iterative process
Software as a service has been thriving as a sector for years, but it has gone into overdrive in the past year as businesses responded to the pandemic by speeding up the migration of important functions to the cloud. We’ve all seen the news of SaaS startups raising large funding rounds, with deal sizes and valuations steadily climbing. But as tech industry watchers know only too well, large funding rounds and valuations are not foolproof indicators of sustainable growth and longevity.
Failing to come across as a unique, differentiated company will likely mean settling for an exit that feels mediocre instead of incredible.
To scale sustainably, grow its customer base and mature to the point of an exit, a SaaS startup needs to stand apart from the herd at every phase of development. Failure to do so means a poor outcome for founders and investors.
As a founder who pivoted from on-premise to SaaS back in 2016, I have focused on scaling my company (most recently crossing 145,000 customers) and in the process, learned quite a bit about making a mark. Here is some advice on differentiation at the various stages in the life of a SaaS startup.
Launch and early years
Differentiation is crucial early on, because it’s one of the only ways to attract customers. Customers can help lay the groundwork for everything from your product roadmap to pricing.
The more you know about your target customers’ pain points with current solutions, the easier it will be to stand out. Take every opportunity to learn about the people you are aiming to serve, and which problems they want to solve the most. Analyst reports about specific sectors may be useful, but there is no better source of information than the people who, hopefully, will pay to use your solution.
The key to success in the SaaS space is solving real problems. Take DocuSign, for example — the company found a way to simply and elegantly solve a niche problem for users with its software. This is something that sounds easy, but in reality, it means spending hours listening to the customer and tailoring your product accordingly.
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How to ensure data quality in the era of Big Data
A little over a decade has passed since The Economist warned us that we would soon be drowning in data. The modern data stack has emerged as a proposed life-jacket for this data flood — spearheaded by Silicon Valley startups such as Snowflake, Databricks and Confluent.
Today, any entrepreneur can sign up for BigQuery or Snowflake and have a data solution that can scale with their business in a matter of hours. The emergence of cheap, flexible and scalable data storage solutions was largely a response to changing needs spurred by the massive explosion of data.
Currently, the world produces 2.5 quintillion bytes of data daily (there are 18 zeros in a quintillion). The explosion of data continues in the roaring ‘20s, both in terms of generation and storage — the amount of stored data is expected to continue to double at least every four years. However, one integral part of modern data infrastructure still lacks solutions suitable for the Big Data era and its challenges: Monitoring of data quality and data validation.
Let me go through how we got here and the challenges ahead for data quality.
The value vs. volume dilemma of Big Data
In 2005, Tim O’Reilly published his groundbreaking article “What is Web 2.0?”, truly setting off the Big Data race. The same year, Roger Mougalas from O’Reilly introduced the term “Big Data” in its modern context — referring to a large set of data that is virtually impossible to manage and process using traditional BI tools.
Back in 2005, one of the biggest challenges with data was managing large volumes of it, as data infrastructure tooling was expensive and inflexible, and the cloud market was still in its infancy (AWS didn’t publicly launch until 2006). The other was speed: As Tristan Handy from Fishtown Analytics (the company behind dbt) notes, before Redshift launched in 2012, performing relatively straightforward analyses could be incredibly time-consuming even with medium-sized data sets. An entire data tooling ecosystem has since been created to mitigate these two problems.
The emergence of the modern data stack (example logos and categories). Image Credits: Validio
Scaling relational databases and data warehouse appliances used to be a real challenge. Only 10 years ago, a company that wanted to understand customer behavior had to buy and rack servers before its engineers and data scientists could work on generating insights. Data and its surrounding infrastructure was expensive, so only the biggest companies could afford large-scale data ingestion and storage.
The challenge before us is to ensure that the large volumes of Big Data are of sufficiently high quality before they’re used.
Then came a (Red)shift. In October 2012, AWS presented the first viable solution to the scale challenge with Redshift — a cloud-native, massively parallel processing (MPP) database that anyone could use for a monthly price of a pair of sneakers ($100) — about 1,000x cheaper than the previous “local-server” setup. With a price drop of this magnitude, the floodgates opened and every company, big or small, could now store and process massive amounts of data and unlock new opportunities.
As Jamin Ball from Altimeter Capital summarizes, Redshift was a big deal because it was the first cloud-native OLAP warehouse and reduced the cost of owning an OLAP database by orders of magnitude. The speed of processing analytical queries also increased dramatically. And later on (Snowflake pioneered this), they separated computing and storage, which, in overly simplified terms, meant customers could scale their storage and computing resources independently.
What did this all mean? An explosion of data collection and storage.
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New Relic’s business remodel will leave new CEO with work to do
For Bill Staples, the freshly appointed CEO at New Relic, who takes over on July 1, yesterday was a good day. After more than 20 years in the industry, he was given his own company to run. It’s quite an accomplishment, but now the hard work begins.
On the positive side of the equation, New Relic is one of the market leaders in the application performance monitoring space.
Lew Cirne, New Relic’s founder and CEO, who is stepping into the executive chairman role, spent the last several years rebuilding the company’s platform and changing its revenue model, aiming for what he hopes is long-term success.
“All the work we did in re-platforming our data tier and our user interface and the migration to consumption business model, that’s not so we can be a $1 billion New Relic — it’s so we can be a multibillion-dollar New Relic. And we are willing to forgo some short-term opportunity and take some short-term pain in order to set us up for long-term success,” Cirne told TechCrunch after yesterday’s announcement.
On the positive side of the equation, New Relic is one of the market leaders in the application performance monitoring space. Gartner has the company in third place behind Dynatrace and Cisco AppDynamics, and ahead of DataDog. While the Magic Quadrant might not be gospel, it does give you a sense of the relative market positions of each company in a given space.
New Relic competes in the application performance monitoring business, or APM for short. APM enables companies to keep tabs on the health of their applications. That allows them to cut off problems before they happen, or at least figure out why something is broken more quickly. In a world where users can grow frustrated quickly, APM is an important part of the customer experience infrastructure. If your application isn’t working well, customers won’t be happy with the experience and quickly find a rival service to use.
In addition to yesterday’s CEO announcement, New Relic reported earnings. TechCrunch decided to dig into the company’s financials to see just what challenges Staples may face as he moves into the corner office. The resulting picture is one that shows a company doing hard work for a more future-aligned product map and business model, albeit one that may not generate the sort of near-term growth that gives Staples ample breathing room with public investors.
Near-term growth, long-term hopes
Making long-term bets on a company’s product and business model future can be difficult for Wall Street to swallow in the near term. But such work can garner an incredibly lucrative result; Adobe is a good example of a company that went from license sales to subscription incomes. There are others in the midst of similar transitions, and they often take growth penalties as older revenues are recycled in favor of a new top line.
So when we observe New Relic’s recent result and guidance for the rest of the year, we’re more looking for future signs of life than quick gains.
Starting with the basics, New Relic had a better-than-anticipated quarter. An analysis showed the company’s profit and adjusted profit per share both beat expectations. And the company announced $173 million in total revenue, around $6 million more than the market expected.
So, did its shares rise? Yes, but just 5%, leaving them far under their 52-week high. Why such a modest bump after so strong a report? The company’s guidance, we reckon. Per New Relic, it expects its current quarter to bring 6% to 7% growth compared to the year-ago period. And it anticipates roughly 6% growth for its current fiscal year (its fiscal 2022, which will conclude at the end of calendar Q1 2022).
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5 investors discuss the future of RPA after UiPath’s IPO
Robotic process automation (RPA) has certainly been getting a lot of attention in the last year, with startups, acquisitions and IPOs all coming together in a flurry of market activity. It all seemed to culminate with UiPath’s IPO last month. The company that appeared to come out of nowhere in 2017 eventually had a final private valuation of $35 billion. It then had the audacity to match that at its IPO. A few weeks later, it still has a market cap of over $38 billion in spite of the stock price fluctuating at points.
Was this some kind of peak for the technology or a flash in the pan? Probably not. While it all seemed to come together in the last year with a big increase in attention to automation in general during the pandemic, it’s a market category that has been around for some time.
RPA allows companies to automate a group of highly mundane tasks and have a machine do the work instead of a human. Think of finding an invoice amount in an email, placing the figure in a spreadsheet and sending a Slack message to Accounts Payable. You could have humans do that, or you could do it more quickly and efficiently with a machine. We’re talking mind-numbing work that is well suited to automation.
In 2019, Gartner found RPA was the fastest-growing category in enterprise software. In spite of that, the market is still surprisingly small, with IDC estimates finding it will reach just $2 billion in 2021. That’s pretty tiny for the enterprise, but it shows that there’s plenty of room for this space to grow.
We spoke to five investors to find out more about RPA, and the general consensus was that we are just getting started. While we will continue to see the players at the top of the market — like UiPath, Automation Anywhere and Blue Prism — jockeying for position with the big enterprise vendors and startups, the size and scope of the market has a lot of potential and is likely to keep growing for some time to come.
To learn about all of this, we queried the following investors:
- Mallun Yen, founder and partner, Operator Collective
- Jai Das, partner and president, Sapphire Ventures
- Soma Somasegar, managing director, Madrona Venture Group
- Laela Sturdy, general partner, CapitalG
- Ed Sim, founder and managing partner, Boldstart Ventures
We have seen a range of RPA startups emerge in recent years, with companies like UiPath, Blue Prism and Automation Anywhere leading the way. As the space matures, where do the biggest opportunities remain?
Mallun Yen: One of the fastest-growing categories of software, RPA has been growing at over 60% in recent years, versus 13% for enterprise software generally. But we’ve barely scratched the surface. The COVID-19 pandemic forced companies to shift how they run their business, how they hire and allocate staff.
Given that the workforce will remain at least partially permanently remote, companies recognize that this shift is also permanent, and so they need to make fundamental changes to how they run their businesses. It’s simply suboptimal to hire, train and deploy remote employees to run routine processes, which are prone to, among other things, human error and boredom.
Jai Das: All the companies that you have listed are focused on automating simple repetitive tasks that are performed by humans. These are mostly data entry and data validation jobs. Most of these tasks will be automated in the next couple of years. The new opportunity lies in automating business processes that involve multiple humans and machines within complicated workflow using AI/ML.
Sometimes this is also called process mining. There have been BPM companies in the past that have tried to automate these business processes, but they required a lot of services to implement and maintain these automated processes. AI/ML is providing a way for software to replace all these services.
Soma Somasegar: For all the progress that we have seen in RPA, I think it is still early days. The global demand for RPA market size in terms of revenue was more than $2 billion this past year and is expected to cross $20 billion in the coming decade, growing at a CAGR of more than 30% over the next seven to eight years, according to analysts such as Gartner.
That’s an astounding growth rate in the coming years and is a reflection of how early we are in the RPA journey and how much more is ahead of us. A recent study by Deloitte indicates that up to 50% of the tasks in businesses performed by employees are considered mundane, administrative and labor-intensive. That is just a recipe for a ton of process automation.
There are a lot of opportunities that I see here, including process discovery and mining; process analytics; application of AI to drive effective, more complex workflow automation; and using low code/no code as a way to enable a broader set of people to be able to automate tasks, processes and workflows, to name a few.
Laela Sturdy: We’re a long way from needing to think about the space maturing. In fact, RPA adoption is still in its early infancy when you consider its immense potential. Most companies are only now just beginning to explore the numerous use cases that exist across industries. The more enterprises dip their toes into RPA, the more use cases they envision.
I expect to see market leaders like UiPath continue to innovate rapidly while expanding the breadth and depth of their end-to-end automation platforms. As the technology continues to evolve, we should expect RPA to penetrate even more deeply into the enterprise and to automate increasingly more — and more critical — business processes.
Ed Sim: Most large-scale automation projects require a significant amount of professional services to deliver on the promises, and two areas where I still see opportunity include startups that can bring more intelligence and faster time to value. Examples include process discovery, which can help companies quickly and accurately understand how their business processes work and prioritize what to automate versus just rearchitecting an existing workflow.
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SAP CEO Christian Klein looks back on his first year
SAP CEO Christian Klein was appointed co-CEO with Jennifer Morgan in October 2019. He became sole CEO just as the pandemic was hitting full force across the world last April. He was put in charge of a storied company at 38 years old. By October, its stock price was down and revenue projections for the coming years were flat.
That is definitely not the way any CEO wants to start their tenure, but the pandemic forced Klein to make some decisions to move his customers to the cloud faster. That, in turn, had an impact on revenue until the transition was completed. While it makes sense to make this move now, investors weren’t happy with the news.
There was also the decision to spin out Qualtrics, the company his predecessor acquired for $8 billion in 2018. As he looked back on the one-year mark, Klein sat down with me to discuss all that has happened and the unique set of challenges he faced.
Just a pandemic, no biggie
Starting in the same month that a worldwide pandemic blows up presents unique challenges for a new leader. For starters, Klein couldn’t visit anyone in person and get to know the team. Instead, he went straight to Zoom and needed to make sure everything was still running.
The CEO says that the company kept chugging along in spite of the disruption. “When I took over this new role, I of course had some concerns about how to support 400,000 customers. After one year, I’ve been astonished. Our support centers are running without disruption and we are proud of that and continue to deliver value,” he said.
Taking over when he couldn’t meet in person with employees or customers has worked out better than he thought. “It was much better than I expected, and of course personally for me, it’s different. I’m the CEO, but I wasn’t able to travel and so I didn’t have the opportunity to go to the U.S., and this is something that I’m looking forward to now, meeting people and talking to them live,” he said.
That’s something he simply wasn’t able to do for his first year because of travel restrictions, so he says communication has been key, something a lot of executives have discussed during COVID. “I’m in regular contact with the employees, and we do it virtually. Still, it’s not the same as when you do it live, but it helps a lot these days. I would say you cannot over-communicate in such times,” he said.
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As UiPath closes above its final private valuation, CFO Ashim Gupta discusses his company’s path to market
After an upward revision, UiPath priced its IPO last night at $56 per share, a few dollars above its raised target range. The above-range price meant that the unicorn put more capital into its books through its public offering.
For a company in a market as competitive as robotic process automation (RPA), the funds are welcome. In fact, RPA has been top of mind for startups and established companies alike over the last year or so. In that time frame, enterprise stalwarts like SAP, Microsoft, IBM and ServiceNow have been buying smaller RPA startups and building their own, all in an effort to muscle into an increasingly lucrative market.
In June 2019, Gartner reported that RPA was the fastest-growing area in enterprise software, and while the growth has slowed down since, the sector is still attracting attention. UIPath, which Gartner found was the market leader, has been riding that wave, and today’s capital influx should help the company maintain its market position.
It’s worth noting that when the company had its last private funding round in February, it brought home $750 million at an impressive valuation of $35 billion. But as TechCrunch noted over the course of its pivot to the public markets, that round valued the company above its final IPO price. As a result, this week’s $56-per-share public offer wound up being something of a modest down-round IPO to UiPath’s final private valuation.
Then, a broader set of public traders got hold of its stock and bid its shares higher. The former unicorn’s shares closed their first day’s trading at precisely $69, above the per-share price at which the company closed its final private round.
So despite a somewhat circuitous route, UiPath closed its first day as a public company worth more than it was in its Series F round — when it sold 12,043,202 shares sold at $62.27576 apiece, per SEC filings. More simply, UiPath closed today worth more per-share than it was in February.
How you might value the company, whether you prefer a simple or fully-diluted share count, is somewhat immaterial at this juncture. UiPath had a good day.
While it’s hard to know what the company might do with the proceeds, chances are it will continue to try to expand its platform beyond pure RPA, which could become market-limited over time as companies look at other, more modern approaches to automation. By adding additional automation capabilities — organically or via acquisitions — the company can begin covering broader parts of its market.
TechCrunch spoke with UiPath CFO Ashim Gupta today, curious about the company’s choice of a traditional IPO, its general avoidance of adjusted metrics in its SEC filings, and the IPO market’s current temperature. The final question was on our minds, as some companies have pulled their public listings in the wake of a market described as “challenging”.
Why did UiPath not direct list after its huge February raise?
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