An automated opportunity
Automation still confuses many, with either images of graceful robots on a choreographed production line, or a machine column rolling out endless iterations of little things.
However, when talking about business automation, the conversation could just as easily be about the process of onboarding an employee, supplier or vendor, or that of handling a claim for an insurer or account opening in a bank.
The automation of a business process can be as simple as taking all the necessary information and transforming it, through various tasks along a process, to fulfill a specific need.
It is perhaps the varied perceptions of what automation is that leads to confusion in implementation, resulting in some of the common failures. A lack of clear business cases and hazily defined goals still dog automation projects.
Before getting into the reason for failure, let us look firstly at adoption. Globally, according to Gartner, the robotic process automation (RPA) market grew by more than 63%, making it the fastest growing category in enterprise software. The analyst site MarketsandMarkets.com says that process automation and instrumentation market is estimated to be worth $71.4 billion (€64.8 billion) in 2018. With a compound annual growth rate of 6% to drive the market to some $95.5 billion (€86.7 billion) by 2024. That growth will be propelled by such factors as the growing importance of energy efficiency and cost reduction, emphasis on digitalised technologies such as industrial IoT (IIoT), increasing adoption of industrial automation, and optimum utilisation of resources.
Specifically, Forrester Research expects spend on RPA tools to top $1 billion (€907 million) in 2019 but will ratchet up to $1.5 billion (€1.36 billion) by 2020. The analyst reckons that 40% of enterprises will operate automation centres and frameworks this year. These investments have been a boon for vendors such as Blue Prism, UiPath and Automation Anywhere, that are collectively valued at $11 billion (€9.9 billion).
“Investment dollars continue to flow into RPA platform companies,” wrote Forrester analyst Craig LeClair in a blog post last April.
With those kinds of growth rates, there is little doubt as to intent in the market, or vendor commitment.
Here, automation technologies are already seeing widespread adoption. In TechBeat survey from earlier this year, in association with Expleo, 85% of respondents said their organisation was using some kind of business automation. Almost three quarters of those (73%) said using automation helps employees to focus on business-critical tasks. Nearly two thirds (64%) expect it to reduce costs, while the vast majority (4%) believe it will be making an impact in their organisation in the next three years.
Put simply, RPA enables IT departments to configure or train software to perform routine tasks, such as generating an automatic response to an e-mail, or to tackle more complex jobs, such as process flows in insurance systems. Unlike machine learning (ML) and artificial intelligence (AI), which organisations also use to automate workloads, RPA is governed by set business logic and structured inputs.
RPA’s potential for streamlining processes sees its use across every sector, notably with the likes of EY, US pharmacy giant Walgreens and Deutsche Bank.
However, automation can also be problematic. Other automation efforts, including those related to DevOps, cloud automation, and IT service management (ITSM) and help desks, are also not without challenges.
If done correctly, automation can live up to its promise, but the key is knowing which IT automation issues to avoid. Writing for CIO, Bob Violino documented many of the common pitfalls for RPA, that apply across the business automation spectrum.
It might seem counterintuitive to need a strategy for automation. Why not just deploy automation wherever it seems to make sense, given that automation is inherently a good thing for business?
As with any other major IT-related initiative, however, there needs to be a master plan for using automation, that is an overarching, clearly defined strategy that keeps things from spinning out of control because of a lack of foresight.
“Implementing automation without a strategy outlined and goals in place is like setting out on a road trip without a map or GPS. You don’t know where you’re going to end up,” said Anant Adya, senior vice president and business head for cloud, infrastructure and security services, Infosys. “Instead of embarking on a large process and end-to-end lifecycle automation, identify automation opportunities in smaller processes, operational areas, repeatable activities.”
Before investing in automation technology, organisations should have a full understanding of what the total costs of products and services are likely to be, as well as what the benefits will be for the business, in order to calculate an accurate return on investment (RoI).
“You need to understand what your real benefit over time will be,” said Joe Schuler, VP, network operations, Mastercard. “Be careful to not spend too much time automating brownfield and rather develop a strategy for where you plan to take the brownfield. Automation of older technologies can become a black hole for resource consumption. Don’t let it swallow your overall effort.”
Oftentimes companies calculate RoI before making investments in tools and technologies, said Adya, which can lead to disappointing results.
“Sometimes, not having out-of-box implementations and tools [and] technologies requiring heavy customisations can kill the RoI,” said Adya. “It’s easy to go overboard purchasing [technology] as well, especially since there’s a plethora of tools in the market and each one has a unique selling proposition.”
Organisations should consider automation tools that are based on open source technologies and are easy to implement, configure, and support, Adya says. “Also, ensure that the solutions you choose can integrate with the native tools,” he says.
Too much too soon
Lots of business processes can potentially be automated, but that does not mean it makes sense to deploy multiple automation tools all at once across the enterprise.
A ‘big bang’ approach is not best for IT automation, according to Schuler.
“While I do think you need to build a critical mass and get some wins under your belt, you cannot radically alter the face of your organisation,” he said. “It’s important to get some early adopters and then showcase their successes. This will build momentum, especially among the naysayers.”
Mastercard tried to implement a database automation platform as a standard and saw some successes with specific use cases. But for others it did not make sense. “I think the important lesson is to provide these tools and stories that showed we reduced implementation times from 16 hours to four hours and allow teams to see the success and embrace the new tools,” said Schuler, on their own terms.
There has been a lot of hype related to RPA, and even though the benefits can be substantial for automating lots of processes, organisations should not rush into deployments without due diligence.
“They make these tools too easy to implement and this could cause a lot of headaches down the road,” said Bob Moore, EVP of delivery for US technology consulting firm SPR. “You must first completely understand the process that the RPA software is going to perform. The key items to consider when designing the RPA process are the need for real-time decision making and application programming interface (API) integration.”
RPA tools can be powerful when deployed correctly, said Moore, but conversely, can be extremely frustrating and expensive to implement when the processes are not completely defined.
“I have spoken to clients who are considering using machine learning to make decisions within the RPA process,” said Moore. “To be able to do this, you would really need to understand the data that you currently have and how it could be used to make a particular decision.” The first question to ask in a scenario like this is whether the organisation has the data needed to make this decision.
Rushing into DevOps
The adoption of DevOps for enhancing development environments and speeding up processes has also gained steam in recent years, but the wisdom is that organisations should resist the temptation to jump too quickly.
“Prepare yourself and your team. DevOps does not happen overnight,” said Moore. “People use the term DevOps for infrastructure as code and for software development processes. This can be a confusion point as they may not always happen together.”
With the DevOps processes currently, it is extremely easy to create new branches in code or environments in the cloud, said Moore. “Unless you have a specific control or process for creating branches, there will be a lot of different code bases in your repository and potentially a lot of orphaned environments.”
Try to select appropriate tools before they find their way into your environment, he advises. “I have seen clients in the past that have had different tools for different teams. As you can imagine, that was extremely difficult to get under control and standardise.”
There is also, of course, the case where a process is working just fine, begging the question as to whether it needs to be automated at all. Changing things by automating something solely for the sake of automation could easily backfire. Before automating anything, consider the impact on the people most affected by such a change: those responsible for carrying out the processes being considered for automation.
“Too often, CIOs automate a process that shouldn’t be the priority,” Adya says. “Talk to your team and assess which processes are major pain points for them. Make sure that the automation initiatives have a significant [and positive] impact on experience, operational efficiency, and of course cost.”
The automation of a particular process, or within a department is all very well, but sometimes companies can neglect to expand the effort beyond the starting point because they were not thinking in terms of scalability.
“The biggest missed opportunity in automation that I am seeing is a lack of scale; for instance, automation being used primarily for IT service management or customer service inquiries,” said Bhaskar Ghosh, group CEO, Accenture Technology Services.
While organisations have been investing in automation for years, most of these implementations have been in “pockets” rather than enterprise-wide, Ghosh says. “This results in friction between processes that can slow down the speed of operations,” he says.
“The key is enterprise-wide adoption of automation. This equips IT workers to do more with technology, undertake complex and creative problem solving, and achieve greater speed and scale for the business.”
The people, process, and technology principle that is commonly cited in business and academic presentations also applies to automation.
“Automation goes beyond a technology,” said Ghosh. “Taking a tech-driven approach will miss out on key elements to success.” Designing and implementing a comprehensive automation approach also needs to take people and processes into account.
Process involves measuring an organisation’s maturity in tooling, culture, automation, and talent, and builds benchmarks for measurement, according to Ghosh. And working with the people within an organisation is crucial to building the right automation culture, identifying new automation roles, and equipping people with the relevant skills and knowledge to work alongside automation.
“Finally, while the technology implementation may seem straightforward, automating at scale requires a platform that can bring data, technology, and industry assets together, as well as provide a 360-degree view of status and governance across all automation projects. We are already entrenched in the era of intelligent automation, and companies that don’t accelerate their adoption are going to find themselves left behind,” he said.
Having had long experience in process automation, Kianda’s founders decided to take a different approach.
Our team of founders came from the experience of doing the actual ground work in business process automation (BPA).
We were the ones that, at some stage, were doing the early design work with clients, and so we have the experience. We decided to take a fresh approach to process automation, allowing users to move in a more agile manner.
Rather than going through the big cycle of diagrams where you spend months and months trying to refine shapes, we can take clients straight into interactively building what is to become end to end digital solutions.
We do this through modern, interactive tools and workflow generators that allow low and no-code generation of processes.
It is a different approach to the other major players.
We achieved this through simplified interfaces that are attractive, familiar and intuitive. We started with a modern approach, a modern interface so it makes everything very familiar to users.
And that, to us, is a very important aspect of process automation. At the end of the day, we are building for people; we are building systems for people. They need to be built with their typical expectations in mind.
Drawing on our industry experience, we created ways of turning those mapped processes into automation systems, but in a simplified manner, hiding the complexity, so that a beautiful front end allows you to leverage all the functions behind it.
Our value proposition, what we really see as our strong suit, is that in the words of our customers, we are a ‘true no-code’ platform, meaning they can build processes and systems without writing a line of code.
Kianda is a no-code platform, but it is also available to developers. A developer can create a new module, or widget, that would then extend the existing functionality for a customer.
However, attractive tools are not enough.
Working with large organisations, we are very agile. Being a small organisation ourselves, we can really listen to what customers are asking for and be nimble and agile in response to what the market and customers are looking for.
Sometimes a customer may ask for a certain facility, such as being able to print or distribute a view or a page from a system, when what is actually required is a document generation system. We develop those relationships, where we listen and understand the customer’s needs and deliver for them.
This process is a two-way exchange. The feedback we receive from working very closely with large enterprises, and even those coming from a developer background, is brought back into our own development cycles. They provide detailed feedback on what they need, and we sometimes work with them on a one-to-one basis to make sure their needs are being met in what we do.
This kind of relationship has proved to be invaluable.
As well as simplified tools and a deeply collaborative process, we help and encourage customers to stand back initially, to get a more holistic view of their goals before proceeding into the detail of BPA.
It is a common mistake to try to do too much, too early.
This helps people with a common problem which is clearly defining exactly what they want to achieve.
Once they have that answered comprehensively for themselves, it is much easier to create a roadmap of what to do. This applies to not just our platform, but to any such projects, but it is particularly important to what we do.
This is where people commonly struggle, and we can help with that.
Agility and flexibility are our key principles, as reflected by our name. Kianda is an African goddess who walks and is seen as protector of those on the water.
Osvaldo Sousa is co-founder and CEO of Kianda
Beyond the obvious
An holistic approach to automation is always recommended. Don’t just focus on the apparent low-hanging fruit; the immediate and obvious processes that can be automated, rather consider allowing for following the breadcrumb trail of processes that these immediate process candidates may start with. Start your discovery with the obvious but explore around this for further value; the adjacent processes may not immediately be recognisable as targets for automation as they may appear more complex however it is rare that a process cannot be automated at least in part. Be willing to attribute more than just man hours or time saving as the metric for measuring value through cost reduction or headcount optimisation. Rather spend some time analysing the target processes for potential additional value such as the unlocking of the next candidate process or the speeding up of the overall business process or the reduction in error counts.
Automation works best where a process is well defined for all possible outcomes. This type of process tends to be based on a pre-defined dataset and associated step order which means deviations from the norm are easily detected and dealt with. Errors in these cases can be classified based on cost of resolution (for example man hours, skill availability, complex additional recovery steps) which provide direct indicators of where automation can best be utilised.
It can also be useful to consider the data hand-offs between different sub-processes or teams within the business as these can be used to identify distinct boundaries. Where such boundaries are identified, they can be used to pass discrete sections of the process dataset and execution between automated processes and real people. For example an automated process can take over from a front-line user after initial data has been gathered and the automated section can generate additional data based on rules or templates before returning control to a human.
Donal Byrne is director of technology with Triangle
The availability of artificial intelligence (AI), low code platforms and robotic process automation tools (all part of business automation) is enabling Tekenable to help organisations create an augmented workforce.
The elimination of non-value adding tasks has always been on the lean agenda. But now it is possible to take that a step further and automate many value-adding activities that humans would once have done. This enables the human workforce to be focused on human skills such as empathy, creativity and emotional intelligence, enabling the organisation to offer improved service levels.
When assessing the potential for business automation technologies typical things that Tekenable sees as strong indicators in any business automation assessment include:
• Incoming paper forms or phone calls – These immediately generate data quality issues and chase processes
• Swivel chair interfaces – The re-keying of data or triggering of workflows manually
• Siloed systems or departments – Which causes companies services to reflect these silos rather than being holistic and collaborative
• Insufficient capacity to meet demand including lack of availability – For example. call centres that close after 6pm and demand peaks like Black Friday leading to overload. Humans do not scale well.
In Tekenable, we have noted over the years that in general it is the simple automations that pay the biggest dividends, allowing self-service foal registration for thoroughbred horses, the removal of paper application forms from a pensions business and not the grandiose digital transformation schemes which often fail to deliver. We believe in Digital Evolution, not Transformation.
A great example of a simple automation by Tekenable was the implementation of Barry the Chat Bot for the parcel carrier DPD. This AI based customer interface handled more than 25% of the call centre enquiry volume from day one leaving the human operators free to deliver higher value customer service.
Peter Rose is chief technology officer of TEKenable