Posted in : Artificial Intelligence, intelligent-automation

If I have to listen to another technologist promoting “AI as a key component of the CIO’s agenda”, I am going to start getting a little irked… AI is not another app that can be installed and rolled out like a Workday, SAP or a ServiceNow.  I even had to listen to an IT executive asking me whether he should “leave AI in the hands of SAP as part of their S4 upgrade”.  Not only that, I noticed a well-known analyst firm promoting a webcast last week advising “CIOs how to rollout RPA”.  Really?

One of the biggest issues in our industry today is the abject failure of the business teams who design and own the processes, to partner effectively with their IT teams to deliver automation and AI that supports the business vision of where the business leaders want to take it.  IT people are not clairvoyant – they can only aspire to deliver what their business colleagues clearly instruct them to do.  Otherwise, they’ll just buy all these fancy software suites and say they did their bit for AI…  So enterprise leaders have to knock the heads of their business and IT teams together and get them partnering effectively to design a roadmap that takes them and their data where they need to go to stay competitive.  There’s no time to keep pointing fingers, we just need to sit down and figure out how to work together in much more effective ways than we have over the past few decades.

Embracing AI is all about crafting the anticipatory organization, one that is hyperconnected across its ecosystem, its customers, employees and partners

The whole purpose of AI in the enterprise is to have business operations running as autonomously and intelligently as possible, which means we need to build enabling IT infrastructure that supports the business process logic and design.  People are talking about “re-platforming the enterprise”… this is really about redesigning IT to support the business needs, to help the business respond to customer needs as soon they occur, and have the intelligence to anticipate the needs of their customers before its competitors can.  

Enterprises need to be as hyperconnected and as autonomous as possible within their business environments if they want to pinpoint where disruption is coming from, where to disrupt and how to keep reinventing themselves in an unforgiving world when we no longer have time to rest on our laurels:

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The problem for IT is that AI doesn’t come packaged in a nice box with an instruction guide

I’m sorry to be mildly offensive here, but AI and automation are only effective when they are designed to solve process and business problems, not check another box on the CIO’s resume. While it is important to keep the IT team in the communication loop so that it is ready to provide the right infrastructure and technology stacks required for operationalizing AI solutions, the steering wheel of any business application of AI must be in the hands of the businesses. Smart businesses  know their key pain areas and can identify the most relevant and feasible business cases. They own the data, they know the context, and how a process should run when it is augmented with appropriate AI techniques.  

For many firms, the day they implemented their first ERP was akin to pouring cement into their enterprise

The reality is the ERP system of the last 3 decades is no longer the system of record for ambitious, hyperconnected enterprises. It is a rigid suite of standard processes that keep when wheels on a legacy operation.  The emerging system of record is the data lake itself, when the business leaders have the ability to extract the data they need to make the right decisions, or have systems that can start to help make intelligent decisions for them.

So let’s examine at the interplay between business and IT with these emerging AI-driven environments with 10 prescriptive activities business leaders and IT leaders need to put into effect, if they want genuinely want to develop AI capability that takes them into this hyperconnected state:

10 AI activities the business teams must lead to ensure AI success 

1. Prioritize use cases from AI technology availability. The business team must prioritize AI business use cases from the initially identified list of potential AI application opportunities. The team must demonstrate its process knowledge and desired end-state scenario to help the IT team to ensure effective project coordination and outcome-setting. Using external consultants at this phase can be very effective to ensure the best business/technology fit.
2. Develop the AI Business case: The most critical step, where the business team must set initial benchmarks, define pre- and post-process improvement metrics, and estimate target benchmarks.
3. AI feasibility analysis and specification development: Business teams must solicit help from IT teams for their expertise with items such as technical feasibility analysis, infrastructure requirement specifications, and technology stack selection. Other areas are technology cost estimation, deployment, and production release, 
4. AI Technology cost estimation: Developing estimates for the cost of technology stacks and solution deployment efforts must be the purview of business teams, but it requires significant and detailed input from the IT team.
5. AI Data preparation and identification: Business teams must ensures success by identifying and preparing the data for training algorithms and building models. The team must solicit assistance from analytics and data warehousing teams.
6. Coordinate with partners: During design phase of the target process model, the business team should must provide input to implementation partners (both internally and with their consultant/services partner) regarding ontology of the problem domain, the existing process models and rules. Teaming here with IT is essential, but the business team must define and communicate the business and process needs effectively. 
7. AI Testing: The business team must lead testing the models against the project goals during the early POC and pilot phases
8. Manage effective AI feedback loops: To make use cases fir for production release, the business team must provide detailed, regular feedback on the accuracy and performance. Again, they need  to work with implementation partners, which may be internal teams from an AI CoE or external partners.
9. AI Training: The business team must be responsible for budgeting, planning and executing the training for large AI user teams, encompassing all of the staffing resources, external consultant costs, processes and task owners that are involved in the implemented use case.
10. AI Deployment: Deployment doesn’t end once the use case is in production. The business team must continuously monitor the model’s outcomes, maintenance, and updates during the inferencing phase, and if the problem context changes with new rules or data, the team needs to add new dimensions and models and create new clusters. Users may also require retraining, especially as processes may change over time. There will also be the need to monitor change management issues, potential legal issues with data privacy / staffing impacts etc.

The Bottom-line:  AI is a business issue that must be directed and managed by business executives, supported by technology experts.  CIOs who ignore this will fail

The business team should seek help from IT in terms of infrastructure and tech stack needs, but it needs to own and run the AI projects because it owns the data, context, processes, and rules and understands the pain points.

CIOs will face an existential fight if they don’t start genuinely enabling the business. The world where IT was all about mitigating outages and avoiding risk is being replaced by one that demands speed, agility, and a genuine understanding of the business.

Being tech-savvy isn’t enough anymore… just knowing where to build a data center is pointless if you don’t know what the rest of the business has planned. And this IT obsession of continually trying to upgrade ERP solutions, when most business units these days can handle it. That’s the pitfall of the old traditional IT approach – we have to make sure we never get cemented in like that again.

Posted in : Artificial Intelligence, IT Outsourcing / IT Services, OneOffice, robotic-transformation-software

Just as the industry was running out of steam, just as we’re writing the obituary of the outsourcing model… suddenly we have sal-vation.  We’re an industry desperate for leadership, for new ideas, for personalities we want to work with, for a new culture that inspires us to get out of bed in the morning.

So how about one provider many of us were giving up on recruiting one of the most charismatic, energetic and determined leaders who grew Accenture Operations from $1.5bn to more than $7bn.  How about the guy who jump-started one of the most impressive machine learning businesses in the industry? How about the guy who pioneered whole new approaches to service delivery with the Six Generations of BPO and the As-a-Service Economy?  How about the guy who drove an acquisition so smart it locked up an entire market vertical? 

Just as we thought DXC was caught in a perennial treadmill of mere survival, they have made one of the most ambitious, creative – and smart – CEO appointments the services business has witnessed in Mike “Sal” Salvino – someone I have known as a friend and industry peer for two decades.  Sal is proven to take legacy business, mine the gold, bring in the talent and make strategic moves, which is exactly what DXC needs at a time this industry is in transition. We’ll have Mike at our HFS Summit on 2nd October to have a more candid discussion with industry leaders if you want to try and grab a last-minute spot.

So what are Mike’s challenges and opportunities according to the HFS analyst team?

Developing market position and messaging. The new combined entity still trying to find its unique market positioning. DXC needs to hit the ground quickly to consolidate and clarify its combined offerings and transform internally to cater to the changing market needs.

Double-down on tech where it can win.  DXC has oodles of capability and talent in automation, digital enablement and AI, in addition, to a $2bn business process services business.  There is gold here if it can bring it to the surface and take it to market in the right way.

Expanding its base. DXC has a significant existing client base of nearly 6,000 customers especially in healthcare, public sector, and CPG. Large deal heritage from CSC and HP.
they have capabilities across OneOffice but have been reduced to a me-too player. No one knows what they stand for… Mike needs to change that, and fast.

Find a way to highlight some of the hidden gems in their incredibly complex patchwork of assets and capabilities from past acquisitions. The “blanket DXC” is drowning out some of their areas of differentiation because they’re not talking about them anymore.

Verticalizing their offerings effectively. DXC spent a bunch of time slinging what HP + CSC can do and came up with 8 master offering buckets. But it was all horizontal. They are struggling to build relevance by industry. If they could fill the white space with their gigantic customer base alone would ensure success. 

Finding a thumb for the dyke. Stemming the flow of long term infrastructure customers getting poached by aggressive ITO competitors and AWS.

Build a true brand association and a mission. DXC doesn’t have a clear story for anyone outside of very specific groups, and that’s really dependent on who you speak to. It’s the same for clients – as part of a major branding project where we interviewed some industry luminaries who all struggled to understand what DXC is up to, what differentiates them, or why they should even think of working with them.

Target (and execute) on acquisitions that provide true differentiation. As Mike looks at strengthening vertical offerings and service delivery areas, there will me boundless firms on the block to evaluate. Time is not on DXC’s side and the right targets need to be integrated effectively, alongside the current firms in the organization.

Posted in : Business Process Outsourcing (BPO), intelligent-automation, IT Outsourcing / IT Services

As we discussed last week, the 2019 State of Operations data shows a strong appetite from enterprises to dump legacy outsourcing practices and reinvest in operating models that can take them straight to digital. 

While the desire to invest in an outsourcing model nose-dived from 62% in 2018 to 28% this year, it’s also worth looking at the definitive actions enterprises plan to take when their current outsourcing engagement come up for renewal:

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There is a clear appetite for change and complacent service providers are in serious trouble

Several service providers have already commented that they “just don’t see their clients wanting to change this aggressively” since our recent roundtable in London and the recent blog post which amassed huge attention across the industry. However, many are clearly in denial that we’re deep in a critical transition from the traditional labor-driven model to one that is much more touchless and less physical in nature.  In my view, the issue here isn’t that these peoples’ observations are wrong, they’re just not having the right conversations.  Most of the BPO executives admit they are “feeling their way” to address their clients’ needs for more RPA and digitization of their processes, but simply do not have the scale of people on hand with the necessary training and skills to help them.  Instead, they are simply waiting for a burning platform that forces them into some sort of action.  Worryingly, when we look at this data, when this burning platform finally appears under their posteriors, it’s already going to be far too late for them to save themselves. 

Why going straight to digital with your outsourcing engagement is like buying a Tesla – it’s a big change, can be expensive and requires a very different type of service partner to make it viable 

Most enterprise operations leaders are unlikely to tell their provider’s client partner “we’re fed up with spending the same dollars each year for the same tired old processes and small army of staff to deliver them”.  That is like going to your car dealer and saying you’re sick of paying extortionate sums for gas to fuel your car, and you’re also sick of polluting the environment.  Unless your car dealer is fully up on electric cars and has a great financing model to switch you up, you’re more likely to find a dealer who specializes in what you need.  The only way your existing car dealer is going to have a chance of retaining your business is if his firm has invested in mechanics who are trained in electric car maintenance, sales people who know enough to sell you one, and a financing partner to get you “fully electric” with a financially affordable package.  

So what can we expect today’s enterprises to do when their current outsourcing engagements expire?

Barely a quarter of enterprises content to stick with their gas-guzzlers.  As the data clearly tells us here, not even a quarter of clients intend to stay true to their tried, trusted, stable (and stale) relationship.  Perhaps they just don’t care that much and can quietly drift along to retirement by merely “keeping the lights on” with their legacy business practices that just about get the job done.

Another quarter wants to move the needle, but may opt for a hybrid model. Meanwhile, 27% are getting itchy to kick their service provider up the rear end and get them embedding some real automation into their delivery if they are to renew with them.  This means they want to see real commitment to reduce the dependence on the staff army and see real investments in process automation to digitize their delivery.  This could perhaps be the car dealer selling you a hybrid vehicle as you look to move to an electric model, but need a defined transition period to get there. It is also less extreme for a car dealer to invest in hybrid cars as they require less specialization than fully electric vehicles, so this is often a great compromise for both parties.

A third is more decisive and likely to make the switch.  32% have clearly got to know their current outsourcing provider only too well over the years and have zero hope they can get any real co-investment out of them.  As we have discovered over the last couple of years, some providers have made real investments in competencies like automation and AI, while others have merely added a little sugar-frosting and persist with selling the same old model with some cost shaved off the package, and some added incentives for performance (i.e “outcomes”).  Moreover, ambitious outsourcers are heavily targeting their competitors’ disaffected clients and are willing to offer eye-catching deals to win their custom.  This can include attractive pricing tied to aggressive delivery staff reduction over a 3-5 year amortization plan that is offset by efficiency savings due to automation and digitization.

In some cases, it may also prove more attractive for the legacy provider to shed the business than fight to keep a client that will quickly become unprofitable (and the industry is littered with those engagements). In many of these cases, this is more like a car customer moving towards a brand they haven’t driven before, most likely a hybrid, and having an acrimonious split from their current model because their dealer tried to sell them a car that just didn’t check the boxes.  However, in several services markets, we are seeing emerging offerings from providers where they are offering fully digital offerings (with vastly cheaper support), such as TaskUs in the customer call center market, or nDivision in managed IT operations, which can undercut traditional outsourcers so aggressively, there is no feasible way the traditional providers can compete.  In addition, we are seeing several India-centric service providers offer $-per-chat support models for some transactional services that are essentially chatbots offering basic-level support services at costs as cheap as 15 cents a chat… we are finally seeing “digital disruption” attack the traditional outsourcing market that has somehow staved it off for years thanks to lethargic clients and lock-in contracts.  

The 17% who have given up and will just look at something very different.  Maybe the cost of changing the model is just so abhorrent it’s time to pull the work back and fix it yourself.  Maybe you’re so fed up with the lack of innovation in changing anything you’ve realized you have smarter people on staff who are better deployed to take the work back, staff up to execute it while you explore all your digital and automation options.  Maybe you want to invest in an integrated automation platform, and you want to use the funds saved by backsourcing the work to invest in an automation backbone that enables you to perform work in a touchless, smarter manner?   Maybe you’ve seen that shiny new Tesla in the showroom window and decided to take the plunge and to hell with the upfront cost…

The Bottom Line – after years of providers complaining about their clients being unwilling to invest, the outsourcing chickens are coming home to roost

The problem with outsourcing is that it has always been underpinned by financial models that give the buyer or provider little wiggle room to make investments to do anything differently.  Most firms still run most of their processes exactly the same way as they did 20/30/40 years ago, with the only “innovation” being models like offshore outsourcing and shared service centers, cloud and digital technologies enabling those same processes to be conducted steadily faster and cheaper.  However, fundamental changes have not been made to intrinsic business processes – most companies still operate with their major functions such as customer service, marketing, finance, HR and supply chain operating in individual silos, with IT operating as a non-strategic vehicle to maintain the status quo and keep the lights on.  

And the poor whipping child over the past couple of decades has been the poor outsourcer, who’s taken on the putrid old processes and attempted to deliver them for their clients at lower cost, where the necessary investments needed to redesign the processes and improve the technology backbone would far outweigh the slim profits being eked out through using cheaper labor and following sensible process delivery templates.  Sadly for our lovely outsourcers, they have little choice but to suck up the fact that they ventured into this business to turn a profit, and if they want to remain in it, they need to make some new investments to get into a position to turn more profits in the future.

As we can see, 59% of their clients are open to doing things differently or using a different partner altogether, so the opportunity is there if you’re willing to take some short term pain for longer-term gain.  This means retraining current delivery staff; this means adding skills in areas like RPA, ML and AI; this means smarter partnering with software firms and specialist consultancies.  This means you need to get out of your niche and provide solutions that your customers need, not merely force them to buy what is convenient and profitable for you to sell them.  This means you may need to start selling Teslas, not gass-guzzling SUVs….

Posted in : Artificial Intelligence, Business Process Outsourcing (BPO), IT Outsourcing / IT Services, OneOffice, Robotic Process Automation

It’s taken more than 12 years – ever since the first-ever blog post written right here – but the outsourcing marketing is on the cusp of its most seismic change since the offshore revolution… the majority of enterprises are seeking to pull away from their stale outsourcing relationships and replace people with intelligent cognitive workers which learn context – or simply bots that perform transactional tasks.  And the reality of outsourcing is that it’s far easier for an enterprise to eliminate workers that are contracted via a service partner than have to go through all the painful change and resistance when trying to eliminate their own staff directly with software investments. What’s more, enterprises rarely want to bring outsourced work back inhouse until it has been fully automated and the outsourcing offers little future value.

All the lovely fluff about “automation and AI creating jobs” is being proved to be utter claptrap for the services industry when we look at fresh new data from the 2019 State of Operations and Outsourcing Study across 355 operations leaders in the Global 2000, conducted with the support of KPMG:

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What’s shocking here is the degree of change in mindset from operations leaders since a year ago, where 62% were still pretty gung-ho positive about investing in their outsourcing model, which has nose-dived to only 28% this year, and a startling 47% actually seeking to decrease their reliance on outsourcing.  So if they’re looking at new models to deliver their business operations – and traditional outsourcing no longer fits the bill – what are they looking to do?  Let’s take a deeper look:

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In short, up to half of major enterprises are looking to find another provider to break their years of painful status quo, while a similar number are looking to embed significant automation into their current engagement. About one-in-six are looking to pull the whole lot back in house and have given up on the delivery model. 

Why this change to outsourcing… and why now?

When we look at our reliance on staff to run our operations, we’re seen a substantial reduction over the last couple of decades, mainly due to advances in software applications that embraced process standards (and natively automation).  For example, most G2000 enterprises had hundreds of people running finance processes a decade-plus ago, and likely barely have 50-100 based on advances in financial software, combined with efficient outsourcing labor arbitrage models delivered by the likes of Accenture, Genpact, Capgemini, and WNS.  Procurement probably had 150 and today barely needs 30… and HR is down to its barebones across most large enterprises.  The division most affected by outsourcing – IT – has shrunk from the thousands to the hundreds in most major enterprises over the past two decades.  Net-net we’ve been through a very long, sustained period of labor osmosis from enterprises to outsourcers, while shared service functions have stayed largely static.

At the same time, people-driven outsourcing engagements have continued to deliver similar process work back to its enterprise clients with the same number of staff, where the outsourcers have had little incentives to make investments in automation and digital technologies, unless they can directly benefit financially, or have contractually agreed to reduce staff numbers over the course of a long term contract.  We are already witnessing the likes of Automation Anywhere, UiPath and AntWorks making significant investments in their own implementation staff as they are frustrated with their lack of traction many outsourcers to incorporate automation and AI technology into the people-focused delivery models. 

The new solution is to bypass staff-intensive processes and go “straight to digital”

The big change we are seeing now (and we’ll share more data to back this up shortly) is that the outsourcing models we know and love have long reached their saturation points, and the only real value enterprises can get from them (in the near future) is to remove the number of staff delivering the work and replace them with digital technology.  For example, a bank we spoke to recently that is replacing hundreds of staff whose job it is to create customer appointments with a conversationally-intelligent cognitive worker solution.  The savings are massive.  However, if the bank had outsourced those workers, the only way to force their service provider to replace them with a digital solution would be to demand it upon contract expiry, or bring it back inhouse and do it themselves.

The key is for software and services providers to develop aggressive adoption programs to create the real “straight to digital” ROI

In recent years, we’ve seen many of these digital models evolve – from simple software apps, to chatbots, RPA tools and now more conversationally-intelligent cognitive workers (such as IPSoft’s Amelia, IBM’s Watson, Automation Anywhere’s IQ Bot, TCS’s partnership with Amazon Connect, HCL’s Lucy and Wipro’s solution of Holmes with Avaamo).  However, the earlier models where enterprises were being forced to invest multi-millions upfront just to get a cognitive or RPA solution actually functioning without constant human intervention and training, have failed, with the notable inability of IBM’s Watson solution to reach anything like the heights the firm had promised because the market a) wasn’t ready and b) wasn’t convinced the massive outlay would reap massive rewards.  And the high-profile struggles of many RPA solutions to replace people with technology (merely augment processes) threaten the rapid rise of those solutions as investors pile on with unrealistic expectations.  So the answer is staring us in the face, and it’s pretty straight forward… the winners in this tough new transition market are those which can guide enterprises to take existing processes and move them straight to digital and remove the layer of people delivering them. 

The Bottom-line: The only true ROI which created the traditional outsourcing model is now repeating itself with digital solutions

As much as we can spin wonderful stories about augmenting people and enriching jobs etc., the goal of most Global 2000 enterprises is to maximize profits and the stated goals of C-Suites and Ops leaders are to a) reduce operating costs and b) move away from physical to digital environments:

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The industry has spoken and it’s clear where they will invest – in partnerships that can accelerate the move to digital without all the painful and costly steps to get there.  And the areas most primed to make this happen are where the staff have already been outsourced and the logical next step is to reduce or eliminate them altogether.  

The challenge for outsourcers. Defend the clients you really want to keep and attack ones from competitors to backfill the inevitable losses as the model shifts from people to digital.  This means you need to develop programs that get your clients leveraging the benefits of automation and AI quickly by hiring talent to make this happen, and forging deep, mutually-be partnerships with software firms to work with you.  As we recently discussed at our Robotic Business Outsourcing Roundtable in London, outsourcers face a stark choice between embracing digital models that require less labor, or fading into insignificance.

The challenge for enterprises.  Forcing your service providers to cannibalize your business is not an easy task, but if you are willing to work with them to build real digital models that work and become a showcase client for them, you should find a cooperative (and hopefully) ambitious partner to work with you.  If you do not, then look further afield for partners willing to invest in your business. If noone wants to transform your operations your business clearly isn’t very attractive (especially if you got a cheap deal to begin with) so you may well be better off bringing operations back inhouse and digitizing them yourself.

The challenge for advisors.  Today’s environment should be gravy for you – I’ve heard from several advisor friends that deal flow is really healthy – and it’s mainly outsourcing renewals demanding digital enablement and less people-centricity.  Hence deal amounts are declining and demanding more complex tech skills to enable new solutions.  Your problem is going to be finding providers willing to embrace disruptive models and work with thinner margins in the short-medium term for longer-term gain.  There are several providers out there willing to be aggressive to “land-grab” deals and increase market share, despite thinner margins and scarcity/cost of tech talent.  However, you really need to flesh out the providers prepared to put skin in the game, versus those paying lip service. 

End of the day, many of the outsourcing partnerships that got so many of us here are unlikely to be the same ones to take us to the next phase…

Posted in : Artificial Intelligence, Business Process Outsourcing (BPO), Robotic Process Automation

At HFS, we’re approaching ten years’ in existence – yes 10 bloody years’ of this stuff – and we’re still the “new analyst kid on the block”.  As we approach this new phase in our journey, we’re focusing heavily on the massive impact our research has across all corners of the services and tech industry.  The traditional channels of slapping stuffy reports behind a firewall and blackmailing suppliers with scatterplot grids are still the predominant way the analyst industry persists in operating (or simply regurgitating supplier press releases dressed up as “insight”), which has helped HFS expand our operations across three continents and bulldoze our way into a small elite group of analysts firms. 

However, we’re not stopping there… we want to engage even more digitally and effortlessly with our global community, using video, blogs, podcasts, webcasts, summits, roundtables and various other forms of social media.  So were gone and added some serious firepower to our digital prowess with our recent acquisition of Quigley Media, where the founder, Tom Quigley, joins us as Chief Marketing Officer.  So let’s hear a bit more from the unassuming Scotsman and his plans for HFS, while he’s not practicing his blackbelt in karate on his three wee lads…

Posted in : Outsourcing Heros

Who remembers this classic “statistic” from a couple of years’ ago, where we caught some friends declaring RPA fantasies that are simply miles from reality:

We’ve been keen to share with the world that RPA satisfaction has been in positive territory for more than half of the adopting enterprises, which is OK for a relatively complex new type of solution that takes a while to get right, and we revealed a 58% a satisfaction rating a few weeks later.

Sadly, two years on, satisfaction ratings have not improved

Our brand new study of 355 operations leaders, conducted with the support of KPMG, has revealed that only 56% of the Global 2000 express a positive experience from process automation and robotics:

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What’s alarming about this is we asked operation leaders to assess the satisfaction levels of all key C-Suite directives, such as the adoption of AI/ML, enabling hyper-personalization, ever the old faithful of “driving down operating costs” …and process automation finishes dead last.  I would argue this isn’t because process automation and robotics initiatives have been a disaster, but more likely, expectations from the sell-side have been vastly over-inflated.  While this may sell more licenses and consulting days in the short-term, it will stunt longer-term growth for the industry.  Let’s delve deeper here…

Why are process automation and robotics lagging in terms of satisfaction?

The over-hyping of how “easy” this is. The problem we have in this industry right now is an obsession with glittering outcomes and not enough real-world guidance on how to achieve them. The majority of robotic adopters have never ventured into double-figures of bots deployed, and many simply have little idea how to progress their adoption beyond a handful of pilot projects. The focus of the narrative needs to be directed to helping clients develop broader robotics strategies across organizational areas. We’re also hearing about some enterprises aborting some major RPA projects because they just didn’t expect the cost and scale of the effort to be so large. So we need to be realistic and balance the great benefits of robotic software with the challenges of training people on it, scaling the technology and gaining buy-in across business units.

Lack of real experiences being shared publicly.  Enterprises RPA adopters are fed up with the constant deluge of “motherhood and apple pie” being served up by the industry when they know full well these deployments are among the biggest challenges their customers have ever faced.  The RPA vendors – and several of the leading services firms – will be far more appreciated if they started sharing the real customer experiences with the world. For enterprise operations and IT executives, being successful at automation and AI is career critical – they want to learn how to be effective and how to invest their time wisely.  If this stuff was easy, they’d be out of a job pretty quickly, but fortunately for them, it is not, and they can embrace these experiences to increase their value to their firms and their careers.

Huge translation issues between business and IT.  Simply put, most IT folks have little understanding of RPA and think all their world problems can be solved with an API.  RPA – for most operations executives – is the first time they have had to work with actual software development and get involved in some low-code activities.  And they approach it with a “process first” context – how can I use these tool to integrate these apps / screen views / objects / documents etc?  I can honestly say I have been to two major software developer conferences where RPA is on display and the developers are simply clueless with regards to how RPA fits into their world of platform modules and APIs. If we can’t bridge this divide, we run the risk of RPA being relegated to the scrap heap of failed technologies.

Obsession with “numbers of bots deployed” versus quality of outcomes.  If I hear another executive claim he/she has deployed over 100 bots, and that is their prime measurement of success, I will start naming and shaming =)  In all seriousness, there is no race the finish-line with this, and can see many enterprises still grappling with automation projects for many years to come.  The ones whom I have met who have expressed the most dissatisfaction are those who have bought far more licenses than they know what do to with, and have real issues trying to explain this their over-investment to their bosses. I’ve even seen some fired because of it.

Failure of the “Big iron” ERP vendors and the digital juggernauts to embrace RPA.  Let’s be honest, with the exception of SAP’s small acquisition of Contextor, which didn’t even warrant a mention at the recent Sapphire event, the IT bellwethers haven’t fallen in love with RPA.  It’s just not sexy and scaleable enough for their suites, and if you read some of the guff on social media from IT “thought leaders”, they have no bloody clue what RPA really is – and does. IT people just struggle with a technology that starts with a business process headache – they prefer to work with code-intensive products that can be shoe-horned into businesses, which they can make really complicated to install and manage.  Only Pega, from the world of large enterprise software, has made greater efforts to embrace process automation with its 2016 acquisition of OpenSpan, and I was quite impressed with the prominence it gave digital process automation at the recent PegaWorld event, but, even at Pega, it’s clearly a challenge to communicate the true benefits of RPA to the Pega traditionalists, whose entire world revolves around its shiny CRM orchestration platform.  While we can point to all the lovely partner announcements we hear from the big three RPAs about their Google, Microsoft, Oracle, Workday, IBM etc partnerships, the truth of the matter is excitement and investment levels from the IT glitterati have been nothing close to what we were hoping/expecting just a couple of years ago.

Bottom-line: Over-setting expectations is putting the automation industry at risk of failure, not setting it up for the success it should be

The lesson here is that the sell-side is pushing too hard to sell too much too quickly and is setting up too many clients for disappointment.  We just need to set expectations better and get the balance right…. Rome wasn’t built in a day.  We need to hear the RPA big daddies talking about how enterprises are grappling with real issues of internal change management, training and education.  We need to hear our IT leaders finally reach their “aha!” moment when they finally understand how robotic software is pulling in their frustrated business operations leaders into their world of embracing technology to help achieve real business outcomes.  Because one adage has rang true for 30 years now – design your processes the way your business needs them to achieve the business outcomes you crave… then invest in the right technology to make this happen.  RPA has the potential to be the first true catalyst to make this a reality, and we mustn’t waste this opportunity.  Let’s create an industry that can flourish for the next 30 years, not one that we’ll break in the next couple with our greed to get rich and close that next contract…

Posted in : Robotic Process Automation, robotic-transformation-software

While the UK government is busily doing a tremendous job destroying the country’s position as one of the world’s great financial centers and multi-cultured commercial environments, one unlikely scenario is unraveling: the steadily devaluing currency, availability of labor (especially in its former manufacturing cities), and adequate education system is placing the country up the league as, now, the third-most attractive location to source business operations and IT support.  This is according to the brand new data from the HFS 2019 State of Operations and Outsourcing study, conducted with the support of KPMG, where we interviewed 355 operations leaders from 355 of the Global 2000:

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Bottom-line: As value from low-cost labor levels out, the focus shifts to increased complexity and talent closer to the business

As we reveal more of the new survey data, you’ll see a prominent shift away from enterprise intentions to invest in traditional outsourcing pivot towards a strong desire to find partners which can support technical complexity in AI, hyper-personalization, and automation.  Net-net, enterprises need support staff close to the business with the ability to understand process and technical complexity that they have never before needed.  This doesn’t mean that popular locations like India and Philippines will see their service industries plummet, it just means outsourcers and GBS leaders need a healthier balance of onshore/nearshore/offshore to bring it all together.  It also signifies a shift from “outsourcing” to “expertise partnering” that changes the location playing field significantly.  While the USA and China are no surprise as their host the world’s largest economies and businesses, the UK is the surprise mover, as political conditions have created a more competitive market to invest in support services. 

Watch this space for more as we drip-feed you this incredible data over the next few weeks…

Posted in : Business Process Outsourcing (BPO), Global Business Services, IT Outsourcing / IT Services, Sourcing Locations

We’ve reached a stage where we can start to assess the capability of leading service providers to deliver comprehensive services across key AI platforms, especially Microsoft’s Azure AI platform and Google’s emerging AI platform suite.  So without further ado, let’s ask HFS’ Research Vice President, Reetika Fleming, how she fared leading the two major Top 10 efforts this year…

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Reetika – how are services around AI platforms progressing?  And specifically, what have you learned with regards to Google and Microsoft platforms?

We’re continuing to see AI ecosystems evolve around the big cloud vendors – Microsoft, IBM, AWS, and Google. From our recent deep-dives into the AI services alliances developing around Microsoft and Google, I can tell you that there are different strategies at play here. Google and Microsoft themselves have their own strengths and priorities, and the SI and consulting alliance partners are collaborating with them in different ways.

• Google’s portfolio of AI components, such as text-to-speech and computer vision, is a great starting point for a fundamental development layer. Google’s AI R&D leadership is well respected among clients and service providers alike. What has been missing are combined applications of these technologies to solve specific business challenges for major business functions and industry verticals. This is where service providers have a critical role to play, and they are filling the gaps by building solutions either in collaboration with Google developers or with clients in selected industries that are ready for AI.
• Microsoft is emerging as the most ‘enterprise friendly’ AI ecosystem. As enterprise clients grow more comfortable with AI initiatives using the Azure technology stack, the services market is quickly developing around client demand. We expect this market to pick up significantly in the coming year as AI services and technology as a whole see greater adoption and as Microsoft and its services partners make more concerted efforts to bring more relevant and timely AI solutions to large enterprises.

Large service providers, including IT services firms, boutiques, and consulting houses, have established or expanded their ecosystem alliances to work with MS and Google on AI. Joint go-to-market activities are taking the form of:

• capability development (POC and pilot funding, talent development);
• market awareness creation and sales planning (joint account planning, campaign work such as Microsoft’s “Make AI Real” workshop series); and
• technical collaboration (joint research, IP creation).

What is driving firms to invest in AI – is it a real desire to meet newly designed outcomes, or more a compelling need to keep on top of emerging tech?

Most of the clients we’ve spoken to in the last year have gone through the learning curve of viewing AI simply as the shiniest new toy the need to be seen to have a strategy around. This is finally starting to become about plugging real business problems and tapping into new opportunities using the evolving range of AI technologies.

Here’s an anecdotal indicator of how things are skewing towards business – at least half the number of AI leaders and sponsors we’re speaking to are business stakeholders, whereas this was squarely an IT/Digital/CoE skewing peer group in years past. Enterprises in our research are certainly looking at business outcomes from their AI investments, including driving up customer experience with AI-enabled apps with virtual assistant support, improving the quality of anomaly detection in manufacturing equipment, and reducing turnaround time on invoice processing. This is good validation for our thinking earlier in the year that AI needs to be driven by the business, with IT as a key partner.

What type of services are you seeing drive the AI industry right now?  Is it more service providers delivering “support” work for clients who’ve already figured out what they need, or are you seeing real “co-innovation partnerships” where provider and enterprise work together to design new process flows to achieve pre-defined business outcomes? 

The last few years has seen many services firms go from completely opportunistic AI exploration to the formal development of AI practices. This is no small feat considering:  

• the technologies are still evolving, at a point where new academic papers are leading to breakthroughs all the time
• the talent is “thin on the ground” for both technical skillsets in data science, applied ML engineering, and distributed computing, and non-technical understanding of the application of AI into business
• the range of capabilities needed to make enterprise AI a reality require massive amounts of collaboration within a service provider’s organization (and their clients) going from data, analytics, cloud, infra support, business domain expertise, consulting, design thinking, product development…

Pure support work is still a norm today, as many clients will test the waters with service providers at the execution level on a project or two. But doing pilots and POCs on repeat can only take a service provider so far. They have learned over time that they need to bring a multi-disciplined team together with industry-specific solutions to actually “collaborate” with their clients.

A few market-leading service providers have certainly developed these types of co-innovation partnerships with their strategic clients. They jointly ideate and vet AI opportunities, and are able to connect across business and IT stakeholders within these firms because of their reach. Here’s how you know these engagements are really partnership-driven – the service provider will be as invested as the client organization in helping the client develop their own AI capabilities, whether that’s through training talent, setting up CoEs, advising on governance and control, or investing to solve unique client problems.

How are you seeing AI impact enterprise “experiences” in terms of customers and employees?  How do you see this advancing as AI evolves?  

We’re seeing tremendous interest in using AI to drive better experiences, particularly to improve customer relationships. Phil, you talk about the hyperconnected future state where enterprises need to not just respond to but anticipate customer needs. AI technologies are perhaps the biggest catalysts for hyperconnectivity, because of their ability to “hyper-personalize” customer experiences.

I love the concept of AI ultimately becoming invisible or just natively being built into the process. You don’t know you’re using it, don’t need specialized skills or training, you just get the benefits, whether you’re a customer, partner, or employee. The best experience in these terms is either delight (e.g. this company knows exactly what I want) or effortless engagement (e.g. it doesn’t take me what feels like a million years to serve this customer!) We’re going to start to see new standards emerge for major enterprise platforms and systems in the next few years for AI-driven user experiences based on this concept. It’s no coincidence that the SAPs and Salesforces’ of the world are pouring millions into AI. 

Casting your eye ahead 2-3 years, who do you see winning in the services space – will it be one of these early leaders, or can you see new players emerging with a different approach?

As we see the further formalization of the AI services market, we’ll need to watch for: 

• Who can find the most successful talent models for AI? Whether that’s crowdsourcing a la Wipro-Topcoder, EY’s “Badges” program to recognize employees’ new skills, or TCS’ investment with Cornell Tech through their new innovation hub in NYC… there’s different strategies on AI talent development for the future, and not all will pay off.
• Who is able to develop and successfully sell digital change management to clients – we see this all the time right? Change management is set to the side because clients believe they can do it all internally, but change management for AI is fundamentally different than other initiatives – you have to alter job roles, the workings of entire processes and decision-making points, establish and continually monitor governance and transparency of new models, and so on. Not everyone can firstly sell digital change management along with AI implementations, and then deliver successfully, and it can be what makes or breaks AI engagements.
• Who is able to make AI easy to develop and scale – internally and for clients. Centralizing and creating libraries of reusable assets, investing in “autoML” type of capabilities that can compress the data prep and training time, containerization of capabilities and existing platforms…these are all indicators of prioritizing scalability for AI.
• Who is able to bring an integrated approach to automation technologies like AI? It’s an easy tell when a service provider’s RPA team has no idea what their AI practice is doing. As we always say, clients want to buy outcomes, so the more service providers can bring a holistic set of capabilities to the table, the more their AI pitch will actually land.
• Who is able to partner with technology vendors most effectively? This includes joint account planning, joint go-to-market and product engineering AI specialists like kore.ai and of course the cloud vendors.

I see the market leaders in these early days pulling ahead, but there will also be a few new logos on the board in the next 2-3 years because of these factors. The service providers in the middle might be left doing some of that support work you referenced earlier.

Lastly, we’re in the final phase of analysis for our comprehensive Enterprise AI Services Top 10 report, so check back with me in a few weeks for more on this.

HFS Premium Subscribers can click here to access the 2019 Microsoft AI Services Report and here for the 2019 Google AI Services Report

Posted in : Artificial Intelligence, IT Outsourcing / IT Services

When it comes to staying relevant in today’s workforce, let’s get to the heart of the matter – YOU have a simple choice to make:

• Do nothing and be part of the “Frozen Middle”. Decide you can’t be bothered to learn anything new, so make sure your firm has the same attitude (or has a thin veneer of innovation masking a cesspool of lethargy and love of perpetuating legacy processes and business practices). And ride this next wave of hype out for a few years before you can quietly ride off into a comfortable sunset, or…
• Become a change-driver. Decide you have to get ahead of emerging technologies and their massive impact on business ecosystems and make sure your firm has what it takes to sponsor your burning ambition to drive cultural changes, new learning and ability to rethink how business processes and practices are wired.

Once you decide which of these two categories which you wish to belong, then make sure you’re in the right company to execute your survival plan… otherwise, leave and find one that is.

Because the data from the recent World Economic Forum jobs study shows half of enterprises are being held back because their staff fails to understand the disruptive changes in their industry, and an alarming 37% of enterprise leaders do not feel their current workforce is aligned to their innovation strategy:

There are no half-measures here, folks – you can’t dip in and out when it comes to driving automation and AI solutions – people are quickly getting found out for having a veneer of understanding.  Either you decide to focus on really understanding how to apply these solutions to your business, or decide you can’t be bothered and focus on maintaining the old way of keeping your business’s operations lights on.

Assuming more people who visit this lovely blog are in category (2), then let’s review what we can do to actually become an AI change-driver….

Saving our jobs when they become “AI-able”

So the automation/AI marketing spiel is firmly espousing that our jobs will be so much richer when we offload as many of our “operational” activities to RPA loops and self-learning algorithms. Isn’t it so cool that all these new un-computerizable activities will just magically appear to fill our job voids to make our lives so much more enriched and fulfilling?

The truth is that people will only truly buy-in to AI and automation when they are secure enough to hand off a lot of the tasks they currently do, with the transition to the new work already in place to maintain their relevance and value to their employer.

Let’s identify how to learn the new stuff so we can offload the AI-able activities

Let’s be direct – in today’s swirl of constant shiny new things, it’s becoming overwhelming for many of us who got by on a traditional education and an ability to deliver routine tasks, handle the usual game of corporate politics and command an ability to “know enough to be dangerous” to stay relevant to our colleagues and management.

Sadly, everyone is now being scrutinized whether they have certain “skills” that will make them worthy of employment as more and more of their job can be replaced by algorithms and automation loops.  So let’s take a look at these skills that came top in the recent World Economic Forum Future of Jobs report, where 100 of the leading firms within each industry were interviewed:

• Cognitive Flexibility. The ability to generate or use different sets of rules for combining or grouping things in different ways.

So this means you need to know your audience and adapt your ideas to suit their needs. You can’t just repeat the same things to everyone – you need to be great at listening and communicating, so you can pull together common threads and continually adapt.  Plus, people need to know you listen to them – there’s nothing worse than being that old windbag who just spouts off the same old guff because they love the sound of their voice.  For example, if you are convincing your HR head about your firm investing in an AI platform, they are likely to focus on the ethics and regulatory/data privacy issues.  Your CFO, on the other hand, will probably want to focus more on the cost/benefit and ease of use. Your CIO will want to understand why your firm can’t use existing tools they already have invested in. There are three sets of conversations you need to find common threads across if you are going to get a consensus to invest.

• Creativity. The ability to come up with unusual or clever ideas about a given topic or situation, or to develop creative ways to solve a problem.

Creativity is so important, especially in markets where differentiation points are wafer-thin.  Take our beloved IT services providers, for example.  Most of them today are offering an identical solution and their pricing is usually similar, and each of them can churn our analyst reports which portray them as the best.  Big fancy business terms, cardboard stories of transformation won’t cut it anymore…  So the differentiation is increasingly shifting to “who do you want to work with” at a people level, so the onus must shift to really listening and understanding your client needs and proving to them you really get them.  Hence, creativity and emotional intelligence are so closely aligned here.

• Problem Sensitivity. The ability to tell when something is wrong or is likely to go wrong. It does not involve solving the problem, only recognizing there is a problem.

My least favorite phrase these days is “fail fast”, as this is usually a term people use in hindsight after they screwed up.  But in fast-moving industries such as consumer goods or online travel, it is often not critical is you launched a poorly thought-out product or service.  In slow-moving industries, such as process manufacturing, a poor decision could affect a single process that takes years to get right, and could be fatal (hence “fail fast” only works in pilot phases, not in real business).  For example, your firm could be launching a recruiting campaign that you realize could be accused of discriminating candidates by age or gender, which would have been par for the course a couple of years ago.  You realize this could have serious implications for your firm in today’s hyper-sensitive data privacy environment, and alert you management asap to change course.  You may not have the solution, but you were sensitive to the problem.  Here, your ability to think laterally and other variables is so important.

• Monitoring Self and Others. Monitoring/assessing performance of yourself, other individuals or organizations to make improvements or take corrective action.

The ability to assess performance for your firm – and pinpoint improvements – is incredibly valuable to your management. As the WEF data emphasizes, two-thirds of financial services firms (for example) see an insufficient understanding of disruptive changes as a significant barrier to change.  At the same time, half of them see a poor alignment between their workforce strategies and their firms’ innovation strategies.  This indicates that staff who can pinpoint how to test their own understanding of the changes within their industries, and also the awareness of their colleagues, and then suggest ways to work together as teams to train themselves how to close these knowledge gaps, will be highly appreciated.

So if you work in a traditional bank, for example, and you recognize several digital startup banks that could really hurt your business as they target millennials who are prepared to switch banks because they have a better app experience, you need to make sure you are ahead of the game and your team is also.  Being able to bring in experts to educate you and your team, or forge enlightening discussions with disruptive startups willing to share their business model ideas are great examples of how you can be a great performance evaluator. This is where we see a lot of cognitive flexibility and creativity aligned with emotional intelligence – and a willingness to put your ego to one side.

The Bottom-Line: When times are good is the time to hone your skills and get ready for when times get tough.  You have an amazing opportunity to rise to the change, so please don’t waste it

Remember all the discussion about the carnage automation and AI were going to bring to the market place?  Forrester claimed 1 million US B2B sales jobs will go away by 2020; Gartner predicted one in three jobs will be converted to software, robots and smart machines by 2025; an Oxford University Study claimed about 47 percent of total US employment is at risk; Stephen Hawking (may he rest in peace) warned us that AI would be the biggest – and possibly the last – event in human history. At HFS, we have bleak predictions too about the future of job as most modern ambitious companies are simply stopping creating the jobs we’re doing today, and refocuses on the additive needs they have in the future, that technology cannot deliver them.

The simple truth is that change that necessitates the fundamental retraining and learning of new ways of working, new attitudes and collaborative cultures is much slower moving that analysts, academics and pundits can predict.  Merely slamming in new tech kit and expecting change to happen is the ultimate recipe for failure in today’s market. Remember it took enterprises two decades to adapt to ERP solutions (many still are)… it even took accountants a decade to adapt from Lotus 1-2-3 to Excel.  Why would we expect today’s business and IT professionals to adapt much faster to new tools and solutions that actually require real training – and all that coupled with making real changes to processes that have been operating exactly the same way as they did 20/30/40 years ago, with the only “innovation” being models like offshore outsourcing and shared service centers, cloud and digital technologies enabling those same processes to be conducted steadily faster and cheaper?  Let’s be honest, most companies still operate with their major functions such as customer service, marketing, finance, HR and supply chain operating in individual silos, with IT operating as a non-strategic vehicle to maintain the status quo and keep the lights on.

Coupled with the pain and pace of change and the lethargy of enterprises to do anything fundamentally different, is the fact that it’s been over a decade since we experience a real economic downturn.  We’re operating at a time where it’s challenging for firms even to populate the call centers and find junior staff willing to perform mundane routine activities.  And talk to any C-Suite executive and they will tell you finding leadership talent and managers with “transformational” skills is nigh-on impossible – and incredibly expensive.

We are lucky to live at a time where we have a multitude of established and emerging change agents at our disposal: global sourcing, Design Thinking, Robotic Transformation Software, AI, Analytics, IoT, blockchain among others. So use this time to learn-up and take advantage of the demand for talent, as one day the climate isn’t going to be so rosy for talent, and jobs that can be automated / AI-ed will never resurface.  The time to challenge yourself and make this crucial choice is now, please don’t sit on the fence and wait until it’s too late.

Posted in : Artificial Intelligence, Automation, GenAI, OneOffice, Talent and Workforce