The State of Outsourcing and Operations 2017

Organizations may be struggling to cope with competing priorities, but directives from the C-suite are growing increasingly clear: Executives say it is becoming more important — and often essential — to implement a business model that digitally-integrates and aligns front and back-office operations, while putting customer needs first.

That is the result of a recent HfS Research/KPMG report, “State of Operations and Outsourcing 2017.” The study found that 31% of respondents call aligning front and back-office operations “mission-critical,” with another 48% saying it is “increasingly important.” Not surprisingly, an even larger majority of executives also home in on reducing operating costs as imperative.

The upshot for operations leaders is an eyes-open recognition that the world is shifting as they speak, so they need to pivot smartly to keep up with complex transformations and emerging business models. After all, the number of things a sourcing leader has to contend with has grown exponentially: It’s no longer just about managing a contract and a provider relationship. Instead, it’s about understanding shared services; the dynamics and risks around global labor; intelligent automation; software platforms and efficient SaaS products; how to get smarter about cognitive and self-learning; and the true power of digital to offer a holistic view of customers.

“Operations leaders have to look at the world, and the organization’s growth, and understand how to conceptualize the digital business that can take them to the next level,” says Phil Fersht, CEO of HfS Research, who also emphasizes a critical need to move away from innovation-killing, status-quo-ridden organizational charts.

Operations leaders: Under pressure to shift towards digital integration

The HfS Research/KPMG report clearly found that senior-level decision-makers are putting operations leaders under pressure to change. “There’s a determination to start wrapping the customer into more thinking about business models,” Fersht explains. “They want to flatten organizational structures, get rid of silos and have process leaders thinking more about customer ends. That is dominating a lot of mindsets now.”

According to Dave Brown, Global Lead, Shared Service & Outsourcing Advisory at KPMG, of particular interest in the 2017 study was a clear increase in conversations around the strategy of delivery models and how integrated they are becoming, as companies strive to get to market more quickly. One of the biggest challenges, of course, is how to boost the organization’s ability to do that. Today’s disruptive digital technology, including automation, is enabling companies today to accelerate and be more effective in their integration approach he says — and it is critical to be hearing this now from such a high level in the C-suite.

“This is starting to tell us that senior leadership is beginning to understand the enterprise approach to be able to solve for digital disruptors,” he says.

The “One Office”: Digital experiences combine with intelligent, integrated support

The endgame, say Fersht and Brown, is a “One Office” strategy that replaces the front, middle and back office to create digital customer experiences with an intelligent single office to support it, with automated processes as its underbelly. “In a few months, the lever of automation will become more and more embedded and there will be less talk about a front and back office,” says Fersht. “Instead, there will be more talk about an integrated support operation that has digital capabilities and prowess to enable the organization to meet customer demand.”

The idea of “One Office” homes in on the needs and experiences of the customer as front and center for the entire business operation. The old barriers between corporate operations and functions are eroded and the constraints of legacy IT are limited. Digital organizations can work in real-time to cater to clients, where intelligence, processes and infrastructure come together as one integrated unit, with one set of unified business outcomes — on a unified business infrastructure tied to exceeding customer expectations.

The bottom line is that digital has become the language of business. But while consumers are increasingly digitally sophisticated, many organizations are still beholden to legacy technologies and processes. Operations may need to be dragged kicking and screaming out of the dark ages to support the customer by breaking down the barriers between departments; investing in bringing digital customer experience into all practices; and creating an entwined digital culture across the organization to deliver to the consumer.

A digital underbelly, with automated, predictive and cognitive processes including robotic process automation, digitization of documents and standardization is necessary to support these changes. On the service provider side, says Fersht, there will be “One Office” enablers — or providers who can help orchestrate data and drive human collaboration — as well as a great deal of tech-dominated outsourcing, with startups and consulting firms coming through to support a $7 trillion economy.

Bigger RPA investments requires more training and workforce development

Study results also made it clear that these shifts will increasingly focus on relying less on both lower and higher skilled labor and investing more in robotics process automation (RPA). In fact, close to 90% of businesses now have emerging or increasingly important strategies to make this shift, with companies looking at both automation and cognitive as strategies for the future. And a significant 43% of senior-level respondents said they are looking at RPA as the number one initiative for investment. It is important to note, however, that in many cases only portions of a job function will be automated, leaving the human employee freed up to do more strategic activities. This is good for the employee but will often require different and higher level skills. Identifying employees that can step up and providing training to do so will prove critical.

Further to this point, according to Dave Brown, what is most interesting to note is the increase in emphasis on training and workforce development that is accompanying these shifts toward automation and cognitive solutions. “Clients are realizing that RPA and cognitive-type solutions aren’t the only answer to their problems, that they need to look at things holistically,” he says. “You can’t just deploy an RPA software solution without looking at what it means to the organization and what it means for required skills in the new organization. In addition, what happens to your workforce if you’ve now have automated even entry-level positions?”

It is encouraging, he continues, to see more focus around training and workforce development, given the high degree of excitement and investment in RPA in efforts to digitally-integrate operations.

“I think people are getting that it’s not just about coming in and doing a proof of concept for RPA solution,” he explains. “Instead, what does this mean to our entire ecosystem, including third-party outsourcing? This is a different story than you would have seen twelve months ago.”

There is a huge opportunity for organizations that can keep up with these drastic shifts. But, with so many changes — jobs being created, jobs being eliminated, skill requirements changing, business models emerging — operations leaders need to be ready for the challenge. “We know pivots happening, but companies need to start being prepared for those pivots,” he says.

Source: cio.com-The State of Outsourcing and Operations 2017

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Is the legal sector embracing the tech revolution?

Dan Taylor, director of systems at Fletchers Solicitors, explains how the legal sector is opening its mind to the innovations tech has to offer.

At the start of 2017, the Law Society (guardians of the UK legal profession) published a report on the state of tech in the nation’s law firms. In his opening address, Robert Bourns, head of Law Society of England and Wales, expressed the belief that the reputation of lawyers as technological Luddites was undeserved and that the sector was “one with energy and ideas, ready to promote a revolution in how we deliver legal services.”

In the same report, however, research into the awareness of lawyers regarding a range of tech innovations revealed a slightly more realistic picture; a sector where innovation is being led by a select few, with the remainder following in their wake.

This is, perhaps, understandable and not too dissimilar to many other professional services, where the emphasis is on human judgement and skill – rather than efficiency and scalability.

However, what is clear is a growing appetite for innovation and an increasing realisation that technology isn’t replacing professional skill and judgement, but instead enhancing it by enabling lawyers to focus their energies to best the effect.

What tech is currently capturing the attention of lawyers?

The Law Society found that, at best, a quarter of lawyers are unaware of emerging technologies (in areas such as artificial intelligence), rising to 38 per cent, 64 per cent and 75 per cent for Big Data analysis, IBM Watson and RAVN respectively.

However, at the other end of the spectrum, the sectors’ innovators are focusing on a range of potential solutions, with artificial intelligence and natural language processing (NLP) being most closely followed by 14 per cent to 20 per cent of the most innovative firms. These areas of tech are narrowly ahead of other appealing solutions, such as Robotic Process Automation (RPA) and expert systems.

A key reason why these are being singled out and gaining the most attention is that they are seen to be most closely aligned to improving client services, making the administration of legal services smoother and quicker, while maximising the quality time with their lawyer.

The report also singles out the desire by firms to use tech to become more agile and stimulate growth. In particular, firms are looking to increase collaboration – with those both inside and outside the firm – and use technology to access new markets, particularly by better serving the needs of international clients.

What specific solutions are lawyers looking for?

In 2015, there were 600 legaltech start-ups offering new solutions to legal clients. Despite this, the report by the Law Society found that there is still suspicion over the extent to which these can currently replace tasks carried out by lawyers and their human assistants.

Instead, the interest appears to be focusing on the future development of ‘augmented workforces’, where computers and humans form a true partnership. Machines will be capable of following basic human-to-human social interactions and lawyers will possess more computer skills to better tailor and utilise technology to support their day-to-day work.

The role for AI

AI programs and solutions have the potential to be invaluable when it comes to coping with the increasing amounts of data that lawyers have to handle, making it easier and quicker to sift through and analyse large collections of documents. It can also be used to automate a number of time-consuming tasks, particularly when it comes to legal research.

Greater use of intelligent systems could allow lawyers to focus more of their time on more complex, high value tasks like the core legal analysis, driving efficiencies and helping lawyers to make quick and accurate decisions. Such systems also have the potential to reduce overhead costs and increase profits.

Optimising online legal services

Law firms have operated online for many years, but at the moment, many firms only offer a small selection of their services online. A large number of legal services offered online merely comprise of external links to communication services, such as Skype, or online forms to be completed for primary legal processes, such as conveyancing or probate matters. Very few legal firms offer “end to end” fully integrated online services, which have long been adopted in other sectors, such as insurance or financial services.

At some point, law firms need to acknowledge that the legal expertise that’s long been the preserve of lawyers is becoming more freely available to the public. Once this is accepted and embraced, law firms will need to start offering their services both in the traditional way in order to survive, while also offering a variety of different online-based options to allow the client more flexibility in how they purchase legal services.

Introducing intuitive management systems

As of yet, such an intuitive case management system isn’t currently available, even though the technology exists and we all use it. This would reduce the time spent on case management significantly and would free up more time to get through more of the core legal work. The development of such a system will surely dominate the market, and those law firms that adopt these systems would see huge efficiencies in productivity and cost savings.

The Law Society’s report reveals much about where tech and law with combine and thrive. Most notably, it is those areas where tech isn’t seeking to replace the human element, but instead to enhance it – augmenting rather than replacing the skills and judgment of lawyers to the advantage of their clients.

Source: itproportal-Is the legal sector embracing the tech revolution?

How Service Providers are Adopting Robotic Process Automation Internally. Part 2

In our last post, we discussed how service providers were using robotic process automation (RPA) to dramatically change the way outsourcing is designed and delivered. This technology, which allows companies to automate support processes, data manipulation or any other transactional activity, is revolutionizing the outsourcing industry and provides an attractive alternative to combat the growing costs of offshoring. This can dramatically improve the way outsourcing service is provided and offer many benefits to clients.

We have already discussed how RPA can improve scalability, offer better support and improve efficiency. Today, we will continue describing the benefits of adopting RPA, why outsourcers need an alternative to outsourcing and how service providers will continue to use RPA in the future to lower costs and deliver better service to their customers.

A new model for global service providers

Although the cost of labor in Asia is still significantly lower than in the U.S. and Europe, it is rapidly catching up. Wages in China have consistently risen by 12% each year since 2001. [1] This, coupled with mounting political pressure to bring jobs home is making many outsourcers reconsider their past strategies.

In order to be successful in the coming years, it is important for companies to rethink the way they design and deliver their services. According to industry consultants at the Everest Group, there are three principles for reimagining global services and automation comes first. “Automation and intelligence lie at the heart of our ability to reimagine technology services, because automation helps us deliver breakthrough outcomes without blowing the cost model out of the water.” [2] Taking an automation first approach that focuses on delivering innovation while maintaining costs allows companies to stay competitive in dramatically changing global markets. This is driving an unprecedented adoption of RPA, with the market seeing an expected annual growth rate of 60.5% between 2014 and 2020. [3]

Benefits of adopting RPA

By giving service providers the ability to use automation to mimic human actions and complete tasks in the same way that a person would, automation can reduce operating costs while allowing the organization to stay agile and responsive. Our last post discussed several of the high-level benefits of adopting RPA. Today, we will discuss some of the more specific benefits the technology can provide to outsourcers.

  • Deeper insights & analytics – RPA can be leveraged to provide automated in-depth logging and reporting, allowing users to gather data more efficiently. This can allow the company to gain insights into processes, improve efficiency, reduce errors and lower costs.
  • Rapid ROI – The efficiency of automation allows companies to roll out new features faster. This can dramatically increase the speed with which they attain a positive ROI for new solutions.
  • Reduced redundancy – Human workers often perform redundant tasks and do unnecessary work. Automated processes can automatically identify these redundancies and eliminate them, improving efficiency and reducing costs.
  • Better management ability – RPA naturally lends itself to better governance and compliance. Managers can look at statistics in a dashboard, easily turn off or adjust processes with the click of a button and generate reports and visualizations quickly. This allows them to gain finer control over day-to-day operations without investing more time or energy in the process.
  • Leverage human employees – Although many workers are afraid that automation will take their jobs, it can actually allow companies to assign their workers more rewarding and stimulating jobs. Creative roles and management roles still need to be performed by human workers and will continue to be for the foreseeable future.

Outsourcing providers will only continue to find more applications for RPA, using it to make their services more efficient, more reliable and better able to meet the requirements of their clients. As the need to find alternatives to increasingly costly and politically difficult offshoring increases, a greater number of companies must turn to automation in order to stay competitive.

Source: Softomotive-How Service Providers are Adopting Robotic Process Automation Internally. Part 2

5 ways to kick-start your business automation and technology plans

The year is ending, yet your company has yet to get its arms around how to leverage technology to compete, remain in business and improve the customer experience. Let’s explore some key recommendations that all businesses should be considering as they embark on the ever-changing business technology landscape.

Here are five ways to kick-start your thinking, along with recommendations to help you automate your company operations and workforce.

1. Technology planning

Technology plans should focus on at least these three core areas: customers, workforce and operations.

Customers always come first and, of course, some technology areas will definitely overlap (i.e. operations and customers). While you are preparing or evaluating your core technology or IT budget, you must lead with the “why” and the “who” first, making sure you are covering all of your technology bases.

Customer technology may include online and in-store systems, through partners and third parties, and through distributors or wholesale. Each technology path through these channels must be explored in depth: What is working? What isn’t? What can be automated? What can be improved? And how does this impact the customer experience (CX)?

As you explore the customer experience, keep in mind the ways customers are being touched by your company, your brand, your products and services, and the news. Social media is now being used as a marketing pull method, marketing through consumer channels may even be important for your B2B brand or B2B2C brand.

Operations are critical to technology plans, including both the IT (information technology) and the OT (operational technology) used for processes, business activities, delivery, etc. In some cases it makes sense to integrate IT and OT; in others, it does not — due to security concerns.

Operations include any and all activities being performed to design, develop, produce, and deliver the goods or products to the end customer. Technology plays a vital role throughout the supply chain, and exploring areas to automate, improve and leverage technology to provide for more efficiencies and better experiences are key drivers.

Working closely with a neutral third party or technology partner may also be recommended, as technology decisions are being made and identified. Of course, you may find working closely with vendors or technology partners is helpful, but remember that they may not always be thinking of your budget and may be biased to their own products or services.

2. Exploring automation

Businesses must continue to leverage technology (cloud, mobile, IoT, robotics, AR/VR, connectivity, e-commerce, wearables, mobile devices, displays, video, virtualization) in ways to further automate the supply chain and the delivery of goods and services to customers. As you explore IT and OT throughout your company, developing an ecosystem map of your own company and locations will provide better visuals. This ecosystem map should include touchpoints, suppliers, channels, applications, core systems, etc. It will provide visualizations as to where automation might be implemented and help you prioritize.

3. Don’t forget content

Content in the form of video, information, intelligent data and live supply chain intelligence should be part of your technology road map. Companies continue to collect and store customer, product and process/operational information but struggle to properly analyze and use the data in meaningful ways. Collecting the right data to improve business processes and integrate with decision-support systems is where the industry is moving. Content that enhances the customer experience is expected to be a higher priority for enterprises, especially those that provide consumer=facing products and services.

4. Evaluations and moving fast

As you evaluate plans for systems that are currently working or being implemented, it is best to have periodic evaluations and check-ins to see what is working and what is not, providing direct improvements to the business. Instead of continued investments in areas that are not producing, it is important to step in early to change the course and make adjustments as needed. Technology is changing rapidly, and so is competition. It is not smart to stick with a plan for the year that is not expected to produce results. Check in, and check often!

5. Fitting IoT in your business

If you are not implementing internet of things (IoT) technologies into your business, you will not be able to compete in the long run. That sounds harsh, but it is what we are seeing today, and technology is being used more and more as the tool to differentiate and automate.

The market is speaking loudly, as many retailers close down and the financial markets tighten. This has many businesses focusing on internal operations to further improve quality, expand efficiencies and enhance the customer experience. Sensor networks and connected machines combined with a secure network and data stored and computed to change the way business is performed today is true differentiation. Businesses not exploring the use of IoT technologies within their operations as a way to provide excellence in the customer experience will not be able to compete, because others in the market will either change business models or launch something new and exciting that distracts your bottom line.

Consumers of products and services are impatient, want it now, expect flawless customer services, and want to use technology to do business with you. Business that react may be too late in the game to survive!

Source: CIO-5 ways to kick-start your business automation and technology plans

7 AI Trends to Watch in 2017

What’s hot in AI this year? Here’s what the analysts say.

Semi-Supervised AI

Unsupervised learning, e.g., when the machine “learns” what is a spam email without first looking at a lot of emails labeled “spam” or “not spam,” is the holy grail of the AI field according to its leading practitioners.

An interim step on the journey to unsupervised learning is a hybrid approach, with some of the data labeled, but letting the machine guess the labels for the rest of the data, using associations. Google has developed one such technique, called Graph-based learning, which uses semi-supervised learning. Using its Knowledge Graph technology, which makes relation associations between words, Google is able to leverage the associations to replace the cumbersome task of labeling all of the data. Google is already using this technology for many of its products like question answering, reminders, visual object recognition, dialogue understanding, and smart email replies. Semi-supervised learning is expected to see increasing usage for very large data sets, where data labeling is an issue, especially around vision and language.

Voice assistants for the home proliferate

VoiceLabs estimates that 33 million voice-activated devices will be installed in the U.S. by the end of 2017. Amazon (Alexa), Microsoft (Cortana), Google (Google Assistant), and Apple (Siri) are investing heavily in bringing consumers into their own devices’ ecosystem by inventing ingenious ways for lock-in. One way to win customers will be offering exclusive features or specific discounts (e.g., inclusive subscriptions to content channels for a certain time period.

Social Chatbots

Social media-based messaging services in China such as WeChat have established and popular chatbots to aid in daily tasks. Facebook is just beginning to drive integration through the use of adverts which link to chatbots, as well as sponsored adverts in Facebook Messenger. These virtual agents will grow in presence and popularity, streamlining eCommerce activities such as enabling users to book flights and hotels, or to order items directly by speaking with a bot through an app.

But they are moving rapidly from consumer applications to offering assistance business users. A survey of corporate executives found that 32% said voice recognition chatbots are the most used type of AI tech in their workplace. Gartner predicts that chatbots will power 85% of all customer service interactions by the year 2020. Slack, Skype, Oracle, Salesforce, other enterprise messaging and collaboration platforms and numerous startups offer in-house or software-as-a-service functionality, helping employees do their jobs faster and better. Like the smartphone, business users of virtual assistants will eventually want these artificial intelligences to follow them throughout the day—possibly giving rise to Bring Your Own Robot (BYOR) movement.

AI as extension of enterprise IT

The enterprise use cases that are attracting the most investment today are automated customer service agents, quality management investigation and recommendation systems, diagnosis and treatment systems, and fraud analysis and investigation. The use cases that will experience the fastest revenue growth over the next five years are public safety and emergency response, pharmaceutical research and discovery, diagnosis and treatment systems, supply and logistics, quality management investigation and recommendation systems, and fleet management. The ability to recognize and respond to data flows using algorithms and rule-based logic enables AI applications to automate a broad range of functions across many industries and augment the work employees, making them more productive.

Self-driving grows up

According to McKinsey, self-driving cars will save an estimated 300,000 lives per decade by reducing fatal traffic accidents. This is expected to save $190 billion in annual critical care and triage costs. With Google alone racking up over 1 million miles testing autonomous vehicles, focus will shift from potential benefits to the necessary regulation. Legislators and policymaker will start the long process of designing and implementing the new legislation. 2020 could be the first year to see a marketable autonomous vehicle and society must begin to prepare for that day. We will see more lobbying groups in Washington DC and more vendor and user coalitions forming, to prepare the ground for widespread use.

The many faces and uses of hardware

Alternative hardware platforms such as field-programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), and specialized processor architectures will increasingly compete for attention and investment dollars with Graphics processing units (GPUs), which have been the dominant hardware platform for AI applications, specifically deep learning systems. As AI algorithms change to account for applications like autonomous driving or personalized medicine with dynamic inputs, there is a case for having memory storage on the processor itself. The evolving nature of algorithms and workloads will determine what architecture is best suited for which application.

The emergence of the AI services market

As happened recently with big data and data science, there is emerging opportunity for services related to AI, including vendor selection, implementation, training, application and algorithm development and integration, and consulting. As the skills and experience related to machine learning and AI are in short supply, we will see expansion of the on-demand services provided by cloud vendors.

Source: straighttalk.hcltech.com-7 AI Trends to Watch in 2017

The future is about services, not software

I was recently given the lowdown on how amazing ServiceNow is becoming with the “integration of Watson and Chatbots into its core platform”. Sounds terrific, but does this added functionality really deliver huge value to customers when we examine the realities of their current business models? I would argue our industry has become so carried away with the promise of technologies we barely comprehend, we have taken our eyes off the real prize: working with customers to help them be more effective. We’ve got to stop selling the Ferrari, when their Volkswagen will comfortably get them where they need to be with the help of a routine service inspection.

I increasingly believe today’s “post-digital” market is much, much more about aligning services to customer business models than selling software with lots of bells and whistles – there are so many tools on the market that have 10-50x the functionality customers today really need with their current business models. Whether Ignio has more bells than Holmes or Nia, or whether anyone truly understands Watson’s capabilities, the key here is which suppliers can work with their customers’ business models to drive better automated processes, introduce more self-learning capabilities and smart analytics that can truly improve their businesses.

Net-net – we must look at everything through the customer lens:

1) Why should I care about ServiceNow?
2) What can I truly do with ServiceNow that can improve my speed to market, my customer engagement, my OneOffice experience?
3) Can ServiceNow really make me a smarter, more analytical operation, based on the people I have on staff and within my service partners?

Just adding software isn’t the answer, it’s about really understanding your desired business model and crafting the operations to sustain and support it. The service providers who invest in staff, that can really align business models to new tech, will win; software firms that can train those winning services firms to do that will win.

This is why Watson is failing to meet IBM’s lofty expectations – they’re selling solutions to clients that simply do not have the skills or experience to understand how to improve their current biz models with cognitive.

This is why 50% of firms are already admitting they invested in RPA products they aren’t getting anywhere with. They just don’t have the internal structure, capability or know-how how to really adopt this stuff.

The Bottom-line: It’s time to invest in real consultative talent… or go home

Net-net – the biggest issue today is that these are solutions trying to find business problems, as opposed to clients having business problems who are looking to find tech solutions to get smarter. This should be about SOLVING existing problems first… Sadly, most of the problems today are too focused on people eliminationthat may not be feasible or financially viable.

The services industry needs to evolve to higher value consulting…. educating clients on the true business value of investing in solutions. But unless suppliers invest in themselves first to understand their clients’ real business needs, the ROI of investments like ServiceNow will never be realized. It’s time to invest in real consultative talent… or go home.

Source: HFS-The future is about services, not software

Have we finally become an industry? Have we become the Digital Operations Industry?

The worlds of software, business operations and services have always been chasms apart – different mindsets, vernaculars, conversations, ideas of what constitutes value – and vastly different cultures. Software people never understood the operations folks and vice versa – each thought they were top of the corporate food chain.

However, the past couple of years have seen the coming together of these diverse groups of people to rethink completely how we run global operations in this robotically digital era (or whatever we want to call this curious period of time in which we exist).

One thing is abundantly clear: the outsourcing phenomenon which has gripped the Global 2000 over the past decade is making way for a genuine industry in which we all play a part – an industry where we have no choice but to develop learning programs, sustainable business strategies and make real, actual investments in order to survive. And what’s most fascinating are the new conversations that have rapidly emerged to bridge this divide between the technologists and the business operators.

Suddenly, we’re talking about business logic, about datasets, about redesigning processes with genuine business outcomes in mind. We’re talking about deep learning AI systems that store what has been learned in the past, take notes of how variables and results have changed under different scenarios and then make decisions based on that.

The narrative has radically changed and the focus is now firmly on bringing together all the components that can escort us to this promised land of Digital Operations. So let’s take a look at what has transpired to get us to this point, where we can actually claim to be part of this emerging industry….

“Outsourcing” never materialized as an “industry”

Having spent the best part of the last two decades trying to make some sort of sense out of “outsourcing” I have come to the simple conclusion: “outsourcing” was never an industry – it was simply the practice of moving work around the world to save money. It consisted of people selling outsourcing deals and the poor suckers who’d been lumbered with trying to manage them – and the deal brokers and lawyers who took money from both sides making it all happen. It was never an industry, it was greedy corporates slashing their wage bills, and those lovely folks who were just so keen to comply with their wishes to turn a profit. Outsourcing has always been an activity searching for a higher purpose than cost take-out. While service providers and advisors undoubtedly feel part of an outsourcing industry, the buyers do not – they are operations people doing their job deploying whatever techniques are at their disposal to improve efficiencies and operating costs. They would not class themselves as “outsourcing professionals”. It’s like selling gym equipment to gyms. The seller is in the “gym equipment business”, the gym itself is in the “gym business”, and the customer at the gym is looking after their fitness. The “industry” is ultimately the higher purpose of which all the entities are all constituents – in this instance, it is the fitness industry – which could also encompass sportswear manufacturers, specialist outlets stores and so on.

How traditional outsourcing has left us in a right pickle

Outsourcing was like a one-time thing C-suite execs arranged on the golf-course to take 30-40% off the operations budget for a set of low-level processes – and enjoy the bulk of those savings upfront for a nice impact. Many folks became heroes overnight for making these deals happen, and they were lauded and courted at conferences as those radical executives who possessed some secret talent ingredient to make this all possible. Yes, a mystique around outsourcing was created, advisors did an amazing job making a science out of the “art of the deal”, and the façade of a new profession and (possibly) a whole new industry was borne.

Sadly, there was never (really) a long-term plan to sustain those productivity impacts, beyond moving as much work offshore, without overly impacting business performance and finding even lower cost cities to take on the low-hanging fruit to eek out a little bit more cost off the bottom line. Eventually, that well runs dry if you don’t make fundamental improvements to the quality of your processes and the convergence of the data sets they support.

Yes, we had a lot of fun creating useless qualifications and meaningless SLAs, but the end results were always the same: clients figured out how they only got what they had paid for, and the fancy innovations they were fed on those lovely pitch decks were always subject to change orders (or never really existed). The only real leverage came at rebid time, when the incumbent would usually make some new promises to get their house in order, if they felt there was actually a chance they could lose the business. Otherwise, it was business as usual.

The Global 2000 is littered with stale outsourcing deals that need radical transformation

However which way you paper over the cracks of short-termism, costs are like hedges – if you don’t look after them properly, eventually they grow back. As a result of all these fun and games, we are left with thousands of ropy outsourcing engagements littering the corporate world, where the clients are still paying for the same number of FTEs to deliver the same tired old obsolete processes, while their providers has no incentive to cannibalise their revenue streams, and the actual concept of moving these deals to other service providers is pretty desperate – all the smart ones have no interest buying up a legacy mess, while some desperate lower tiers ones may take on the work if they can shunt it to even cheaper, lower quality delivery resources.

But there is a way forward, and outsourcing has served a purpose

Believe it or not, there is a method to all this madness – companies managed to externalize work they didn’t want to run themselves, they got a lot of cost off their books, and they opened up the opportunity to pull more levers in the future to find new thresholds of productivity. Rarely will you ever find an enterprise which regretted outsourcing – they’ll never want that work back. The big issue, now, is ensuring that work is in a state to be optimized further by improving the quality and logic of process flows, digitizing them and applying smart automation techniques, where it makes sense. However, that can prove quite a challenge when the work has been distributed across third and fourth tier cities, and it actually requires some investment to transform those processes to consider meaningful automation and other delights that digitized processes can enjoy, such as Machine Learning and AI.

In fact, in too many cases, outsourcing resulted in enterprises sweeping their real process issues under the carpet and choosing to ignore the real need for genuine transformation until that day of reckoning occurred. And that day is now upon us, as CFOs are smoking the automation crackpipe and demanding that next 50% of cost to be ripped from the bottom-line in a 3 year timescale. Outsourcing provided them with a band-aid to enjoy cost savings through labor arbitrage, but robots can only provide further band-aids if the outsourced work has high-intensity, high-throughput processes that can easily be programmed into the software. If that work is distributed across too many locations, with service providers unwilling to make renewed investments to co-invest with those clients, we have an emerging issue facing many enterprises: their day of reckoning has been reached and they actually need to make some investments in their processes and underlying systems.

Welcome to an actual industry in which we can co-exist: Digital Operations. This is why we are now emerging as an industry – we are facing the reality that most enterprises need to make long-term investments in their digital underbelly, their process flows and their people to run them, in order to find sustainable value over the next decade.

For the first time, we are witnessing deep conversations happening across the operations spectrum: RPA, Machine Learning and AI software vendors and now talking with service providers about how to embed their offering into long-term service contracts to support sustainable productivity and incremental data value over time (our data already shows close to a third of the Global 2000 are already integrating automation into their service delivery):

Ambitious enterprise customers of outsourcing, shared services heads and other operations leaders are all feverishly learning how to understand the value of software tools and how to prepare their process flows for the benefits of digitization and automation. Consultants worth their salt are rapidly training their people to develop automation roadmaps for their clients and prepare them for a longer term strategy of creating a truly effective digital underbelly. Yes, we are still are suffering from a few cowboy consultants claiming their clients can slash 50% overnight through RPA, the our observations are quickly showing that people are learning fast and know they need to address many of their underlying processes and talent issues, if they are truly going to take the next step forward.

Bottom-line: The Industry is Digital Operations, and there are six levers to pull to find sustainable value

The conversation among operations executives has changed dramatically just over the past year. As the excruciating hype around robots taking our jobs and these outlandish predictions from drama-loving analysts and academics, a sense of reality is finally setting in – roles are not changing overnight, we just need to get out of our comfort zones and learn new stuff. We need to understand the pivotal role data plays in our professional lives and become smarter about how we manage it. We need to understand where RPA adds value, where to start with Machine Learning and AI, how we can truly leverage globally distributed talent to support out operations affordably and smartly, we need to be observant about the creeping impact of blockchain and how we can truly take advantage of digital technologies to nurture new revenue streams and enhance customer, partner and employee engagement up and down our supply chains. It’s taken a full decade just to take advantage of the cloud, and we need another one before that really fulfils its potential. It’s going to be even more complex to ingest the benefits of automation, AI and blockchain into our business operations – but now we have six genuine value levers to pull to tend the hedgerows of digital operations.

Source: HFS-Have we finally become an industry? Have we become the Digital Operations Industry?