Yes, folks, that was one of the key takeaways one of the delegates pointed out at the FORA Summit in London last month, where a very mature conversation took place about the real future of operations in this lovely robotic age (download your full copy here).
This packed-out event was attended by 120 senior executives, the majority being senior buyside enterprise clients, joined by the CEOs of the leading automation solutions vendors, practice leaders across the leading service providers and global advisors. and the HfS analyst team. This was a chance to get beyond that deluge of wooden marketing and sales hype that is murdering our sanity… and get to the real nub of the of the issues plaguing a confused – and fumbling – industry.
Ten Big Takeaways from the Discussions
1. RPA needs to move beyond the teenage romance stage. One delegate pointed out that RPA often started out like a teenage romance – a lot of fumbling around with enthusiasm that ends quickly, often leading to disappointment. Past events have focused on the importance of change management to the process, however, our recent study of 400 automation buyers shows that a lack of clarity around the business case is the major barrier to RPA adoption (change management rears its head after all the fun and games of implementing the software):
2. RPA hype is over and it’s nearing time to retire the term in favor of Digital Operations and the emerging Digital Workforce. Hype needs to move from replacement to enablement. The benefit of automation and AI are not reducing the workforce, but enabling machine to human and human to machine interaction. Helping enterprises and governments make better decisions with data. Building a more virtuous cycle with automation, decision making and data.
3. The Pace of Change Cannot Be Slowed – If You Aren’t Disrupting You Aren’t Surviving. Companies that view disruption as an opportunity and are not complacent are the most successful. Paranoia about the world ahead is your friend – driving staff to innovate and disrupt. Technology in this circumstance is a tool not a solution. Our customer panel said that there are ‘burning platforms’ already being created and businesses are going to have to come to a decision at some point soon to adopt. The supplier panel were agreeing that automation is surviving for big businesses and large enterprises have less than five years to sort this out.
4. The biggest challenge for Automation is the shift to scale. It’s not a technology problem, but an organizational change issue and how to achieve a broad set of outcomes at scale. Currently many implementations are sub-scale – tens or hundreds of bots instead of thousands they could potentially be.
5. Ultimately the world needs to shift its economic measure from effort to outcomes – where value is linked to achievement rather than the effort to achieve. The value of relationships need to be more interactive than ever, to make the shift towards outcome-based engagements, and away from effort-based.
6. The C-Suite is paranoid about the future and eager to make changes, while middle management is complacent and resistant to change. Culture is a major impediment to changing this dynamic. This requires a number of changes –change in the way companies operate, change in the skills that companies value, change in the incentives and the training that enterprises offer staff.
7. To adapt we need to constantly learn. This means better understanding of new technologies, better understanding of underlying processes and what can be improved. But ultimately it is about the best way to drive outcomes within the business.
8. We still need more use cases – especially as we look to Cognitive/ML/AI. As the hype shifts to higher forms of automation the need for use cases for all automation expands. There needs to be clearer understanding of where the value lies and where the process should begin. RPA is being passed over even when it offers 80% value for 20% cost and should be recognized as a valuable tool in an enterprise’s arsenal.
9. The purpose of digital is to bring humans and technology together. One of the panellists made the comment that digital was not about specific technology or about a transformation. “Digital” is about the bringing together of humans and technology. It is the interface, closing the gap between the two.
10. Change management remains a vital component of automation strategies. The difficulty in delivering at scale is exacerbated by poor change management and planning. It’s clear from our event in Chicago and in London that enterprise customers and service providers need to spend more time on planning to get automation to work effectively. One senior buyer representative said “change is not like flipping a light switch… more like a dimmer where it comes to full light over time and every new leaders is a new start.” So there needs to be a clear outcome and commitment – one of the main topics of conversation during the event was around the need for better change management to ensure that nothing is left behind in the race to transform. With important advice that “change management is about educating people slowly toward what the world will look like tomorrow”.
The Bottom line: Here are the anti-fumbling themes taking the conversation to New York this coming March…
To conclude the London summit and take the narrative onto our biggest and baddest FORA summit yet, the following four themes will steer the next phase of this industry mandate:
The Technology – a means, not an end. Data is the currency of transformation
Like with many new technologies, analysts, consultants and industry practitioners become obsessed with definitions and the demarcation between automation variants: in this case RDA, RPA, AI, Machine Learning, Cognitive, and all their permutations and combinations. Whilst this might be important for market sizing and positioning – many of the conversations in London reinforced the point that technology is a means, not an end – deemphasizing this definitional obsession. All these pieces of tech are tools, not solutions themselves. Without a coherent, end-to-end business transformation strategy, “dabbling” with automation technologies frequently does more harm than good, at best yielding only meagre results. Given the amount of potential disruption to legacy work practices businesses are facing, a deeper transformation strategy is required which will take automation at scale – “you need to go big,” as one participant put it, to get real benefit from automation. But first, organizations must map out the path to understand where they’re going. This brings with it another crucial part of the transformation recipe – data. Understanding the centrality of data to the digital enterprise – how to acquire, structure, interpret and act on it – is essential
The Value – shifting the metrics from effort to outcomes
Much of the discussion during the event focused on the outsourcing services industry, in part because that’s where the prevailing labor-arbitrage business model is under existential threat, and in part because that’s where automation technology is already being deployed at scale. During his keynote Phil Fersht observed that “Transactional outsourcing’s death throws began in 2012” – dating its demise to the rapid emergence of RPA. However, there is a new, business model within reach. Providers have meaningful experience with automation technologies and valuable know-how, while buyers desperately need expert help with design and implementation. What’s needed is a new value proposition – one that separates effort and time from cost and revenue, and shares risks and gains. “Clients will have to contribute value to their suppliers,” as one participant put it, and providers will have to become more innovative and willing to expose their balance sheets – in short, being less transactional and more consultative.
The Talent – taking the robot out of the human and putting insights back into the process
As has been discussed at the FORA and HfS Summits in the past – and as noted by Professors Leslie Willcocks in London, automation is not about replacing humans, automation “takes the robot out of the human.” Taking the mundane and process-centric tasks to free up employees to engage in more meaningful activities. Artificial Intelligence, on the other hand, augments and extends the human mind, empowering humans to make more consequential decisions. Together, they fundamentally change human behavior and workplace management paradigms. In the digital future, all employees will need skills in data analysis and interpretation, and middle managers in particular will need to be able to connect the work they supervise with the outcomes the business requires. Both must be granted what one participant called “permission to change” the way they have traditionally operated, and business must invest to equip them with new skills to succeed.
The Change Imperative – the way operations support the business itself needs to be redesigned
There is a growing awareness that we are at a step-change – a discontinuity – in business history. The challenge presented by digital and automation technologies can only be met successfully with a commitment to transformational change; incremental, tactical approaches will only yield limited results and risk failure. As never before, senior executives in every industry face existential decisions about the future of their enterprises, and will need to “make themselves uncomfortable,” as one participant put it – to re-imagine their businesses based on the centrality of data and digital relationships (see Technology above). They will need to shed the constraints of the “as is” and articulate the journey to the “to be.” Success will be measured not on beating last quarter’s results but on the ability to see and grasp the scale of change required and create a viable and compelling digital vision for what one participant called the “journey to improvement.”
Our Chief Strategy officer, Saurabh Gupta has been pioneering new research and vision across distributed ledgers, blockchain and smart contracts. In his latest POV, entitled “The Blockchain Reality Check. Where are we, and what can we expect in 2018?” Saurabh dives into what we describe as “Blockchain Six-Pack”, which describes six built-in features of blockchains that manifest into a disruptive potential over the long run for enterprises, when leveraged intelligently in relevant business use-cases. Net-net, the Blockchain Six-Pack is changing the way we think about business transactions, data storage, and even industry value chains and associated revenue models:
Distributed shared data over Peer-to-Peer (P2P) network reduces single points of failiure. The most fundamental difference between DLT and the way we store data today, is that Distributed Ledgers do not have a central administrator. A distributed ledger is replicated, shared, and synchronized digital data geographically spread across multiple sites, countries, or institutions. This allows information to be available across the network in a fully transparent and autonomous way, reducing single points of failure and enabling far better collaboration.
Consensus-driven trust cuts out the middle-man. In blockchains, there is no need to trust the middle-man as you don’t have one. Trust is driven by consensus algorithms such as proof-of-work (PoW) or Proof-of-Stake (PoS) or some variation of these. As a result, we don’t need to worry about unreliable, inaccurate, dishonest or overpriced intermediaries.
Immutable transactions ensure trust. Each block in a blockchain contains a timestamp and a link to a previous block. By definition, blockchains are inherently resistant to modification of the data. Once recorded, the data in any given block cannot be altered retroactively without the alteration of all subsequent blocks and a collusion of the network majority creating a single source of truth.
Hashing-based data ensures integrity and security. All records are individually encrypted. Blockchains use cryptographic hash codes to verify data that drives up integrity and creates strong resilience to cyber-security concerns
Automated smart contracts promote touchless interactions across process chains. Several blockchains also offer ‘Smart Contract’ functionality. These are computer protocols that facilitate, verify, or enforce the negotiation or performance of a contract, or that obviate the need for a contractual clause. This allows contracts to auto-execute based on pre-set conditions or triggers and allows for much higher levels of straight-through It can even allow the millions of IoT devices to work autonomously
Permissioned and permission-less flavors give enterprise users flexibility. Much like public and private clouds, blockchains can be private (permissioned), public (permission-less), or somewhere in between (hybrid). These flavors give enterprises the flexibility to choose their solution based on their needs and preferences. Permissioned blockchains enhance privacy and take less computational power (so have higher throughput) but lack the Utopian trust that permissionless blockchains, such as Bitcoin, can bring.
Blockchain’s inherent features give it the potential to drive new touchless business models and disrupt existing ones by removing the need for intermediaries in the long-run. This results in significant increases in the speed, security and reliability of executive processes, transactions and interactions on both micro and macro scales. The potential is enormous, provided blockchains are adopted, sensibly regulated and executed effectively. However, HfS expects a five to seven-year horizon for blockchain to delivery fully, given the nascency of the technology and associated challenges. In addition, media hype and fake news, in addition to negative activity from threatened legacy stakeholders and other economic impacts, could impede adoption.
What can we expect from blockchain in 2018?
In the near term, we do expect blockchain initiatives to drive significant business impact and create a frenzy of excitement as ambitious businesses jump on the potential of new technology developments like never before. Use-cases around traceability through provenance and asset tracking, digitization of contracts leading to faster settlements, management of private data and digital identity will drive significant efficiency and effectiveness gains in existing business models. Blockchain can also become a source of competitive differentiation in the medium term by re-imagining IT infrastructure that is shared and decentralized, re-defining transaction management that is transparent and immutable and driving additional trust in multi-party collaboration.
We might not see the true disruptive potential of blockchains over the next 12-18 months, but we will see it become much more than a conversation topic with several use-cases that are generating tremendous business value for its constituents. And let’s not discount the levels of hype that tend to drive our industry in new directions, especially when the tech works. While digital, AI and automation have been the flavors of 2017, blockchain is gearing up to lead the hype in 2018, as enterprise leaders search for new levels of value that have genuine, proven business applications.
So don’t sit back and assume that the world is not changing, because very soon this funnel is going to flip. Go ahead and investigate blockchain!
HfS subscribers can click here to download our new POV: “The Blockchain Reality Check. Where are we, and what can we expect in 2018?”
The tech is here and is being proven, but are we really, truly ready to disrupt our underlying corporate DNA to exploit it to its full potential? Can we really change how we operate, think, collaborate and focus to embrace the new wave of data-driven transformation that is engulfing us? In true ballistic HfS style, we are bringing together some of the finest minds from enterprise buyers, academia, technology and BPM services to share how change can be realized – and how to venture outside of our comfort zone to get there. As always, this is a non-salesy sharing of best practices and research between the key industry stakeholders. No cardboard cutouts, plastic booths or dodgy salesmen… honest!
The new “rules” of the workplace are being defined as computers are frantically being programmed to take the lead in the workplace, when it comes to judgment and intuition. We humans need to be the idea generators, the motivators, the negotiators, and the trouble-shooters to fix computer errors, if we want to govern our emerging digital environments. In short, we need to get closer to our firms, be more tightly integrated and intimate with work performance than ever before… which means the role and tenure of the much-derided middle-manager in the Dilbert Cartoons could be taking on a whole new potential twist – and a whole new (potential) level of relevance.
I would go as far as declaring 2018 as a new beginning of the value of the full-time employee – where alignment with the mission, spirit, culture, energy and context of an organization has never been so important. We are seeing the value of contract work diminish as so much “outsource-able” work is so much easier to automate and global labor drives down the cost of getting things done quickly and easily. Business success is more about investing in the core than ever – and that core includes the people who are the true pieces of human middleware to hold everything together.
The onus is circling back to the value of being a full-time employee, who needs to value the fruits of having a predictable income and adapt to the changing balance of how humans need to work with computers.
Remember when the rise of the gig worker was supposed to revamp how so many of us worked, as we escaped the shackles of the “evil employer”?
Almost two decades ago, the internet was creating the independent worker, as exemplified in Dan Pink’s timeless book “Free Agent Nation: How America’s New Independent Workers are Transforming the Way We Live” became the seminal guide for what is now known as the “gig worker”.
Furthermore, unless recent research from McKinsey of 8000 workers can now be categorized as fake news, 162 million people in Europe and the United States—or 20 to 30 percent of the working-age population—engage in some form of independent work today. And a recent study from freelance site Upwork (which undoubtedly wants to hype the impact of gig world) cranks up the numbers even further, claiming that a staggering 50% of US millennials are already freelancing, before declaring the freelance sector will comprise the majority of the US workforce within a decade. Wow.
So are the days of being gainfully employed really disintegrating before our very eyes? Or is the gig hype beginning to atrophy for many people?
The gig economy is becoming a tough place to craft a living if many of the new reports are to be believed. And it’s not just about driving Ubers, delivering food orders and contracting for logistics firms – i.e., working for businesses that exploit the gig economy to drive down labor costs and improve services. It’s the freelance gig economy where people forge a living writing code, supporting content development, delivering consulting work on-demand etc. Even that lovely Upwork research admits: “While finances are a challenge for all, freelancers experience a unique concern — income predictability. The study found that, with the ebbs and flows of freelancing, full-time freelancers dip into savings more often (63 percent at least once per month versus 20 percent of full-time non-freelancers)”. So even if the most biased of sources admits most gig workers can’t cover their living costs, we can conclude that those “Free Agents”, which McKinsey describes as the gig worker sector using gig work as its primary income, are not in a sustainable earning situation.
Today, it’s a buyer’s market for gig work
You only need to spend a little time on LinkedIn to observe just how many people are now marketing their wares as solo free agents, or as part of a company bearing their name. It’s abundantly clear that so many people have decided to set themselves up as independents, that the market for gig talent is saturated and it’s become a “buyers’ market” for gig work. Whether I want to commission a crack consultant to validate some RPA software, hire an analyst to endorse my product, commission a writer to produce a white-label assessment of an emerging market, produce a go-to-market strategy for my business, redesign my website, my logo, or just have someone support my business on a part-time basis… today, I am spoiled for choice. I barely need to hire fulltime employees these days, unless they are truly core to keeping my business ticking along – and I can create real competition to get the work done for much lower costs than a few short years ago.
On top of the risks of commoditizing gig work, we have to contend with the impact of automation and Machine Learning to stay relevant and worthy of earning a paycheck
We’re not in a world rejecting human work, but a world where work is rapidly changing – and the skills of the dynamic middle manager has never been so important. In short, the increasing availability of computing power to crunch massive amounts of data, coupled with advancing tools to tag and label data and workflow clusters with breakthrough programming in languages such as Python for syntax and R for data visualization, are the game-changers that will increasingly impact how we get work done, as we develop continually smarter algorithms to keep teaching computers to do the work of the human brain.
What’s more, the rapid development of Machine Learning (ML) environments such as Google’s TensorFlow, the Microsoft’s Azure Machine Learning Workbench, Amazon’s Sagemaker, Caffe and Alibaba’s Aliyun are becoming the new environments driving armies of coders and developers to align themselves with ML value – desperate to stay relevant (and well paid) against the headwinds of commoditization of legacy coding and app development.
As ML takes over judgment and (eventually) intuition, the human-value onus moves to interaction, agenda-setting, problem defining and idea generation
In short, the disruptive ML techniques are teaching computers to do what comes naturally to humans: to learn by example. Today’s emerging ML tools use massive amounts of data and computing power to simulate neural networks that imitate the human brain’s connectivity, classifying data sets and finding patterns and correlations between them.
Net-net, pattern-matching jobs are increasingly being affected by ML – vocations such as radiologists, pathologists, financial advisors, lawyers, procurement executives, accountants etc. are all being challenged as judgment work is (gradually) being replaced by smart algorithms. However, as elements of these types of jobs are being affected, other job elements become even more important, namely interacting with other humans, creating, setting the agenda, defining and finding the problems to go after. They motivate, they persuade, they negotiate, they coordinate. They are the dynamic conduits of driving information and ideas in an organization and will be increasingly in the driving seat as Machine Learning advancements increasingly take hold. The digital middle manager who can bring a team together and lead people in the right direction does not exist and likely never will…. I’d be amazed if we saw one emerge soon.
Fulltime employment is now becoming a premium situation
Having predictability of income, healthcare costs covered, guaranteed paid vacation time – and a constant supply of work to do – is fast becoming the dream scenario for the disgruntled gig worker. So here’s a thought – go get a JOB. Or if you’re in a job and wanted to try the gig work thing… spare a thought for what your ideal situation looks like, because last time I looked, most firms are doing everything they can to avoid hiring well-paid staff… especially if they can get the work done much cheaper from desperate gig workers.
The Bottom-Line: Five steps to keeping your job:
i) Become the conduit of ideas and information that is irreplaceable right across your organization. So we’ve now come full circle, where the value of having people really close to the business is becoming more important than ever, as computers perform more and more of the routine and judgement based tasks. To the point, the value of the full-time employee goes both ways: companies need people who really understand their institutional processes, their quirks and ways of getting things done… who are onhand to troubleshoot mistakes, but also there to keep the ideas flowing to keep the business ahead of its competition and close to its customers. “Human middleware” is becomimg the real OneOffice glue to break down those siloes and help govern a slick business operation from front to back office.
ii) Develop a positive attitude by finding aspects of your job you do like. Your full time job is likely the best gig-work you will probably ever get, so even if you hate your boss and most of your colleagues, ask yourself if you’d prefer scrapping around for the boring work other companies prefer to outsource. Focus on the interesting stuff you can do and keep reminding yourself that the grass is rarely greener elsewhere. Unless you are a whizz at Python development, the chances are your job-hopping days are numbered and you need to figure out how to stay put and make it better for yourself.
iii) Motivate yourself and become a real motivator. Being motivated – and helping to motivate others – is probably the least computerizable trait of all. If you aren’t motivated, you are placing yourself at risk when your leadership assess which of their team then want to take them forward into the future. If you really can’t get yourself excited about what you do, or your company just demotivates you in such a way you can’t dig yourself out of your rut, then you may need to take that Python course and brush up your resume…
iv) Let the computers take the lead and become the controller to fix mistakes double checking, intervening when the computers do something dumb. Humans and computers make different kinds of mistakes, so we really need to bring humans and computers together intelligently to cancel out each other’s mistakes. Fighting automation and ML is a lost cause, especially when your firm is completely bought in to the concept and it rolling out bots and working on developing smart algorithms. Just let these things take the lead and them figure out how to make them functional and monitor their errors, ad computers will always keep making them. You can’t fight innovation, but you can nurture it, manage it and troubleshoot it.
v) Find your pareto balance and stop whining. Nothing in life including your current or prospective employer will be perfect. Focus on the 80% that is right, versus making yourself (and others around you) miserable by the other 20%. There is rarely a perfect fit where workers only get to focus 100% on all the things they love to do… there has to be this 80/20 compromise, or you will be forever hopping around trying to find a workplace nirvana that doesn’t exist. And it today’s social world your reputation follows you around like never before… and employers are steering clear of the whiners at all costs.
With our governments going broke and looking to go even broker, here is my simple wish-list to fix our endemic societal issues, and recoup some much needed tax income, so we can start dreaming about things like improving disastrous education and health services…
Trump is gone …and a new political party emerges in the US that isn’t controlled by greedy corporations and corruptible misogynist dinosaurs. The American voters go back to voting on policies, not stereotypes and hatred. Wouldn’t that just be so awesome? Is it illegal to dream these days?
Britain finally gives up on Brexit, realizing that changing the color of passports from red to blue doesn’t make up for trashing the country’s economic future and hurtling it back into the 1970s. Please can we all just admit there is not one single good thing about Brexit for any living being, so we can just consign the whole thing to the time-capsule of bad ideas, along with communism, dodgeball and the George Foreman grill. Bad ideas are OK, as long as we admit later they were bad ideas…
Political leaders finally realize that smartphone addiction is the worst disease to affect society since cigarettes and booze. In fact, it’s worse – they could fund entire health, military and education programs taxing booze and ciggies, but with smartphones, all the money is now getting sucked offshore somewhere, and into Mark Zuckerberg’s and Jeff Bezo’s bank accounts.
Re-open pubs and bad discos. Back in the pre-smartphone era, our social world was centered on bad pubs and even worse dance floors. Yes, we had to get drunk and make idiots out of ourselves to meet people and get married… now it’s just swipe left or right, a few photos and you’re all done. Where did all the “fun” go? Can’t governments declare what’s left of our pubs as places of national heritage and conserve what we have left of life before Instagram? Is the joy of youth consigned to sharing bad selfies and playing online video games alone in their bedrooms?
Tax gym memberships. What was wrong with a few extra pounds and a beer gut? Now, if you don’t have a perfect six-pack on your chest, rather than in your fridge, you’re not exacty making friends like you used to… where did all the fun go? Not sure about you, but I don’t have much energy left for socializing after 45 mins on the treadmill and benchpressing 130lbs, so I might as well donate the $20 I should be spending on booze to the government to fund the reopening of classic pubs.
Tax anyone trying to buy Bitcoin. Just because.
Tax vendors double for sponsoring every ropy conference under the sun. They’re wasting their money in any case, so why not make them do something useful with it?
Place income tax on robots. This will end the inane conversation about “digital” labor, as everyone goes out of their way to call it something else, like workflow efficiency… which is what it really always was, right?
Tax vendors for using the term “digital” in their marketing. Why not make some use out of a meaningless overused term…
Tax #fakenews. Forget the detritus of Obamacare, this will fund a whole new health system, right?
Tax bloggers for writing opinionated blogs, because they think they can. Make them realize there’s no such thing as free opinion these days…
The Bottom-line: As we near the end of a ridiculous year, we can all dream, can’t we?
On behalf of the HfS analyst team and global community, I am delighted to announce our flagship FORA summit taking place this coming March 7th and 8th at Convene, Times Square, Manhattan, New York City.
This will span the entire two days with the theme “Learning to Change” dominating the conversation. The tech is here and is being proven, but are we really, truly ready to disrupt our underlying corporate DNA to exploit it to its full potential? Can we really change how we operate, think, collaborate and focus to embrace the new wave of data-driven transformation that is engulfing us?
Key Topics up for Debate:
Intelligent Automation in Practice (not theory); Blockchain demystified; Emerging Sourcing Models and the Digital OneOffice; The Emergence of the Chief Data Officer; Making Change Management actually work.
Key Speakers and Panelists:
Tim Leberecht (Author of the Business Romantic); Tony Saldanha (VP, IT and GBS P&G); Phil Fersht (CEO, HfS Research); Mike Salvino (Pioneer behind Accenture Operations and a key investment partner for Carrick Capital); Larry Carin, Professor of Computer Engineering, Duke University (More to follow….
CEOs of the leading Intelligent Automation software firms and IT/BPM service providers
Key enterprise leaders managing data, automation, global business services and operations initiatives
HfS analysts spanning emerging technologies, industries and sourcing solutions.
Why FORA is Special:
The worlds of software providers, business operations leaders, and services providers have always been chasms apart – different mindsets, vernaculars, conversations, ideas of what constitutes value – and vastly different cultures. At FORA, we are bringing together these diverse groups of people to rethink completely how we run global operations in this robotically digital era, to debate the challenges and opportunities posed by automation, AI, analytics, blockchain, global talent on our business operations and our careers.
If you have further questions regarding FORA, how you can attend, sponsor, speak, or just make suggestions, please drop us a note at [email protected]
When the statement “It’s just like BPR from twenty years ago, but with tech that actually works” rang out at the recent London FORA Summit, the nods around the room were palpable.
2017 has undoubtedly been the break-out year for enterprise robotics software. We witnessed a whole new industry emerge around robotic technologies that can stitch together workflows, processes, applications and desktop interfaces to provide a genuine transformation of the digital underbelly for so many enterprises, many of whom have suffered for decades from inefficient manual workarounds and spaghetti code clogging up their ability to access data and run their businesses properly. Today, the emerging solutions available on the market do not load the enterprise transformation blunderbuss with silver bullets, but they do provide a starting point to improve fundamentally the data underbelly of an organization. And, for so many organizations, they are turning to robotics software RPA (Robotic Process Automation) and RDA (Robotic Desktop Automation) as the starting point.
Robotic Process Automation
The global market for RPA Software and Services will reach $898 million in 2018 and is expected to grow to $2.2 billion by 2021 at a compound annual growth rate of 54%.
RPA Definition:
Example use-case: automating invoice processing across multiple business applications handling rule-based exceptions. RPA is different from traditional automation software as it is inherently capable of recognizing and adapting to deviations in data or exceptions when confronted by large volumes of data. In effect, it can be intelligently trained to analyze large amounts of data from software processes and translate them to triggers for new actions, responses, and communication with other systems. RPA describes a software development toolkit that allows non-engineers to quickly create software robots (known commonly as “bots”) to automate rules-driven business processes. At the core, an RPA system imitates human interventions that interact with internal IT systems. It is a non-invasive application that requires minimum integration with the existing IT setup; delivering productivity by replacing human effort to complete the task. Any company which has labor-intensive processes, where people are performing high-volume, highly transactional process functions, will boost their capabilities and save money and time with robotic process automation. Much fr RPA is self-triggered (bots pass tasks to humans), but requires human intervention for judgment-intensive tasks and robust human governance and to make changes / improvements.
Similarly, RPA offers enough advantage to companies which operate with very few people or shortage of labor. Both situations offer a welcome opportunity to save on cost as well as streamline the resource allocation by deploying automation. The direct services market includes implementation and consulting services focused on building RPA capabilities within an organization. It does not include wider operational services like BPO, which may include RPA becoming increasingly embedded in its delivery.
Robotic Desktop Automation
In addition to RPA, the other software toolset which comprises the emergence of enterprise robotics software is termed RDA (Robotic Desktop Automation). Together with RPA, RDA will help drive the market for enterprise robotic software towards $1.5bn in software and services expenditure in 2018 (with close to three-quarters tied to the services element of strategy, design, transformation and implementation of enterprise robotics). HfS’ new estimates are for the total enterprise robotics software and services market to surpass $3 billion by 2021 as a compound growth rate of 39%.
RDA Definition:
Example use-case: automating transfer of data from one system to another. RDA is essentially surface automation, where desktop screens (whether desktop-based, web-based, cloud-based) are “scraped”, scripted and re-programmed to create the automation of data across systems. A well-designed RDA solution can automate workflows on several levels, specifically: application layer; storage layer; OS layer and network layer. Workflow automation on these layers requires equally specific technologies but provides advantages of efficiency, reliability, performance and responsiveness. Much of this automation needs to be attended by humans as the automation is triggered by humans (humans pass tasks to bots), as data inputs are not always predictable or uniform, but adaptation of smart Machine Learning techniques can reduce the amount of human attendance over time and improve the intelligence of these automated processes. Similarly to RPA, RDA requires human intervention for judgment-intensive tasks and robust human governance and to make changes / improvements:
The Bottom-Line: Automation and AI have a significant part to play in engineering a touchless and intelligent OneOffice
However which way we spin “digital”, the name of the game is about enterprises responding to customer needs as and when they occur, and these customers are increasingly wanting to interact with companies without physical interaction. This means manual interventions must be eliminated, data sets converged and process chains broadened and digitized to cater for the customer. This means entire supply chains need to be designed to meet these outcomes and engage with all the stakeholders to service customers seamlessly and effectively. There is no silver bullet to achieve this, but there is emerging technology available to design processes faster, cheaper and smarter with desired outcomes in mind. The concept was pretty much the same with business process reengineering two+ decades ago, but the difference today is we have emerging tech available to do the real data engineering that is necessary:
In short, every siloed dataset restricts the analytical insight that makes process owners strategic contributors to the business. You can’t create value – or transform a business operation – without converged, real-time data. Digitally-driven organizations must create a Digital Underbelly to support the front office by automating manual processes, digitizing manual documents to create converged datasets, and embracing the cloud in a way that enables genuine scalability and security for a digital organization. Organizations simply cannot be effective with a digital strategy without automating processes intelligently – forget all the hype around robotics and jobs going away, this is about making processes run digitally so smart organizations can grow their digital businesses and create new work and opportunities. This is where RPA and RDA adds most value today… however, as more processes become digitized, the more value we can glean from cognitive applications that feed off data patterns to help orchestrate more intelligent, broader process chains that link the front to the back office. In our view, as these solutions mature, we’ll see a real convergence of analytics, RPA and cognitive solutions as intelligent data orchestration becomes the true lifeblood – and currency – for organizations.
Do take some time to read the HfS Trifecta to understand the real enmeshing of automation, analytics and AI.
What we love about the Digital OneOffice™ is the simple fact it not only defines “digital”, but it also provides a meaningful framework, comprising of five fundamentals, that must come together to create a real-time flow of data across customers, partners and employees:
Fundamental 1) – Fostering genuine Digital Customer, Partner and Employee Engagement
A genuine “digital” organization has the ability to take all the cool social, mobile and interactive tech we use in our personal lives and create that experience for all the people in its environment – its employees, customers, and partners – and empower them to interact with each other seamlessly, and in real-time.
The outcome is all about creating, supporting and sustaining an immersive customer experience, where all touchpoints across an organization are tied to serving the customer as effortlessly and seamlessly as possible (and often not necessitating any actual human to human interaction). These “immersive” customer experiences are about leveraging these omnichannels (typically mobile, social, interactive technologies) and creating meaningful analytics from these converged datasets that make this real-time digital experience happen for the organization and its customers, its employees and its partners, right up and down the supply chain. The OneOfficeorganization needs a support function to service those customers, get its products/services to market when they want them, manage the financial metrics, understand their needs and future demands and make sure it has the talent which truly understands how to meet the desired outcomes of their work.
Fundamental 2) – Embedding Design Thinking Techniques to achieve Continuous Digital Outcomes
Design Thinking offers an approach for a diverse group of people to work together to identify and articulate a common problem, brainstorm ideas for addressing it, quickly prototype/wireframe/storyboard and test it, and continue to iterate on the idea as it takes shape into a proposed solution. A Design Thinking led approach to designing a Digital OneOffice framework moves the focus of the operations executive and service provider partner away from the process itself, and the internal, “what’s wrong inside of what we do” to “what do we actually want to achieve” (the business outcome), and what do we want people to feel and do naturally that will lead to further engagement and new—and different—results.
At HfS, we are finding that Design Thinking is actually changing the way many clients and service providers work, that there is a real complement between designers, consultants, engineers, and service delivery as organizations seek to bring the front, middle and back offices closer together to achieve common outcomes. Moreover, it’s vital that Design Thinking is firmly embedded as the method for ongoing engagement across all organizational stakeholders, as outcomes constantly evolve as markets evolve and business needs change.
Fundamental 3) – Building a Scaleable Digital Underbelly that Automates, Digitizes, Cloudifies and Secures
Every siloed dataset restricts the analytics insight that makes process owners strategic contributors to the business. You can’t create value or transform a business operation without converged, real-time data. Digitally-driven organizations must create a Digital Underbelly to support the front office by automating manual processes, digitizing manual documents to create converged datasets, and embraces the cloud in a way that enables genuine scalability and security for a digital organization. Organizations simply cannot be effective with a digital strategy without automating processes intelligently – forget all the hype around robotics and jobs going away, this is about making processes run digitally so smart organizations can grow their digital businesses and create new work and opportunities. This is akin to a “central nervous system” that incepts and processes all the elements necessary to make the organization function.
Fundamental 4) – Achieving an Intelligent Digital Support Function without Hierarchies and Silos
Enterprises need their support functions such as IT, finance, HR and supply chain, aligned with supporting the customer experience, as opposed to operating in a “vacuum”. We are terming this ”Intelligent Digital Support,” where broader roles are created and human performance is aligned with the achievement of common business outcomes. With the Digital OneOffice, the focus needs to shift towards creating a work culture where individuals are encouraged to spend more time interpreting data, understanding the needs of the front end of the business and ensuring the support functions keep pace with the front office. This is especially the case in industries that are more dependent than ever on real-time data, using multiple channels to reach their customers and being able to think out-of-the-box to get ahead of disruptive business models.
Progressive OneOffice enterprises prefer flat structures, where staff naturally collaborate in autonomous, cross-functional teams motivated by shared outcomes. They look towards much more dynamic management, where managers and staff constantly interact to fine-tune performance against evolving outcomes and manage diverse workforces across global cultures.
Fundamental 5) – Establishing Intelligent, Cognitive Processes that Promote Predictive Decision Making
The Digital OneOffice is not about collecting and archiving historical data simply to discover what went wrong, it’s about being able to predict when things will go wrong and devising smart strategies to get ahead of them. The Digital OneOffice is about embedding smart cognitive applications into process chains and workflows, it’s about learning from mistakes and new experiences along the way. This is the “organization neural system”. Cognitive technologies, advanced analytics and automation help create the capability necessary to operate in digital environments by automating and extracting the data needed real-time to respond to markets, support critical decisions and stay ahead of the game.
The Bottom Line: The secret sauce of the Digital OneOffice is the sum of the Five Fundamentals as one integrated experience, not merely the quality of individual fundamentals themselves
When we conducted the Digital OneOffice Premier League earlier this year, we focused on the ability of service providers to deliver each fundamental, and the winners were those who scored highest as an aggregate across the five. When we re-run this in the future, the Digital OneOffice framework should be mature enough to evaluate outcomes based on the ability of providers and their clients to create the most effective real-time digital experience, by managing the five fundamentals as one integrated organization unit, where teams function autonomously across front, middle and back office functions and processes to promote real-time data flows and rapid decision making, based on meeting defined outcomes.
And front, middle and back offices will cease to exist, as they will be, simply, OneOffice.
