Tag

business process transformation

What Venture Capitalists Can Teach Us about Driving Transformation | Sherpas in Blue Shirts

By | Blog

The current way we buy complex services through a purchasing department is to come up with elaborate detailed requirements, which often can only be implemented over several years. We put these out to bid, forcing the vendor community to respond with far more detail and waterfall project plans laying out in excruciating detail how they will architect and migrate this environment to the new desired state. We then conduct the services version of the limbo dance – how low can we go – where providers compete the price of the solutions. But there is a huge fallacy in this procurement methodology.

We have a long history of unhappy results from this methodology, a body of work spanning 10 to 15 years demonstrating that these procurement efforts mostly result in unmet expectations, cost overruns, and evolving service levels. This is insane. Insanity is doing the same thing again and again and expecting a different result.

The fallacy of the procurement methodology

By using this methodology, we effectively try to articulate a transformational journey in an overly precise way even though we have only a limited understanding of both the existing and future environments. The result is exercises in creative writing with overly precise work plans and cost estimates. The only thing we can be sure of is that the plans are wrong because of the lack of information (no matter how much time we spend on the plans), and the fact that the world changes during this timeframe. So we’re guaranteed to be wrong.

Therefore, our preferred way to purchase services is flawed. It pretends that we know with precision things we don’t know and it does not adequately accommodate for the nature of change in technology, business process and business conditions.

What can venture capitalists teach us?

For years VCs have faced a similar problem. How do they develop breakthrough, compelling new technology products, fund them, manage them cost-effectively and, most importantly, how do they get to great offerings?

They achieve these objectives by accepting that, although the vision for the journey can be had, the length of the journey is unknown, the amount of money required to accomplish is unknown, and the exact nature of the end product is also unknown.

This is very similar to the problem we find in most service transformations. We know the direction we want to head, but we can’t describe accurately and precisely where we’ll end up, can’t quantify how much it will cost, don’t know how many resources it will take to get there or how long it will take to get there. All of these factors vary. Yet, using the procurement methodology, we pretend we know these details and set up artificial constructs.

Applying the VC principles to transformation services

Why don’t we do what the venture capitalists do? First of all, they break the project down into a series of gates. The only detailed road map is the one between where you currently are and the next gate. That requires a detailed plan. One of the parts of the plan is to develop a plan for the next gate.

Using VC principles, the vision and the dimensions of what you want to accomplish are clearly stated. For example, “I want to bring the cost of IT down by 40 percent” or “I’m going to standardize my components and move them into an elastic or consumption-based model, and I’m going to develop agile vehicles to integrate the components.” But how you will do that and how it will involve your current environment is unknowable.

All that is knowable is how you develop a proof of concept and how you move from POC to rapid implementation. You can fund each step much like VCs do (Series A, Series B, and Series C funding) and break it down to create funding associated with milestones that get you to the next gate.

This is a broad application of the VC philosophy, and there’s much more to it. But I believe by applying these principles, we can change how we drive transformation. We can dramatically lower the interaction costs of the purchasing process, and we can spend that money and time instead on the actual transformation. And we can deal with our providers or ecosystem partners in a much more transparent and direct way.

It’s best to apply this VC-based methodology where the benefits of design and architecture drive the value, instead of price reduction as the driver. You can still get lower unit prices, but the old procurement process is dead. That process is useful if you’re trying to take a stable environment and reduce its unit price. But it is not useful where you are driving a transformational agenda, which cannot be precisely defined. Using the old methodology for a transformational agenda tends to waste time, frustrate ecosystem partners and create false promises.

Thinking about Robotic Process Automation (RPA) – What Can You Learn from Your Cloud Journey? | Sherpas in Blue Shirts

By | Blog

Everyone is talking about the emerging disruptive technology that is the next transformational solution…

Tales of massive cost reductions and time-to-market improvements that will leave your competitors in the dust abound…

You are getting pressure from the C-Suite about what you’re doing about it…

The vendors have lots of slideware, but precious few production examples at scale…

Everyone is launching pilots or proofs of concept…

Hmmm…is this recounting the cloud services situation of 5 to 7 years ago, or today’s RPA situation?  Well, I think it is both. Our discussions in the market – encompassing both enterprises that are commencing their RPA journey and services and technology providers jockeying to deliver solution to those enterprises – suggest a picture that is eerily similar to a number of patterns we saw as the “last” disruptive trend was gaining its footing a few years ago. It got us thinking about what those wishing to capitalize on the emergence of RPA might learn from the trials and tribulations many firms went through as cloud services emerged.

  RPA
today
Cloud Services during emerging phase Fast forward: what happens next for RPA
Market maturity
  • Every conversation begins with “here is what we mean by RPA…”
  • Every conversation began with “here is how we define cloud…”
  • As enterprise-wide usage patterns emerge, nomenclature will converge to drive clarity on the value levers
Adoption patterns
  • Lots of pilots; slow to scale across processes/ enterprise
  • Focus on “no brainer” use cases
  • Lots of pilots; slow to scale to enterprise workloads
  • Early focus on “spiky” workloads where cloud yielded extraordinary benefit
  • Many “red herring” barriers (“cloud can’t be secure”)
  • Business users will continue to drive siloed initiatives until market reconciles buyer needs with provider business models (see below)
Solutions
  • Targeted at specific use cases with value enabling providers to extract maximum profit surplus
  • Not oriented toward enterprise value
  • Targeted at “low hanging fruit” use cases where benefits were unassailable
  • Broad enterprise-wide solutions limited to niche players (private cloud-led for most larger enterprises)
  • Solutions evolve from “bolt-on’s” to serving as a foundation/primary dimension of the environment
  • ROI driven by impact across processes and internal organizational boundaries
  • Enterprise software vendors build automation capabilities into their products
Market leading solution providers
  • Bifurcated market structure with leading software providers and business process services providers
  • Software firms struggling to align a software business model with market needs
  • BPO players conflicted with cannibalizing installed base
  • Tradeoffs embedded in software and BPO business models hinder adoption
  • “New entrants” exploited unique cloud business model
  • “Incumbents” that attempted to leverage their historical business model made compromises and fell behind
  • New RPA business model must emerge to fully align with market needs and drive enterprise-wide value
  • Solution providers will emerge with approaches that align interests (rather than create conflicts)
Value levers
  • Cost reduction with the ability to replace human capital with robots

 

  • Cost control by tying  cost structure to usage patterns
  • Value levers emerge that supplant cost reduction such as accuracy, flexibility, agility and compliance 

That’s not to say there aren’t some key differences in how these two disruptive trends are playing out. For example, while both sets of key early players created their business models from a blank sheet of paper, the cloud leaders (Amazon Web Services, Google, Microsoft Azure, etc.) clearly had deeper pockets than emerging RPA leaders and they leveraged that ability to invest ahead of demand to drive a market share-driven pricing strategy that secured and continues to protect distinct advantages.

Notwithstanding the differences, it sure feels like many enterprises (and service providers) have been down this path of pursuing the next disruptive technology before.

As you contemplate your RPA strategy, it probably makes sense to step back and gauge how your organization responded to the emergence of cloud services. The steps you took that worked for your cloud initiatives – and those that didn’t work so well – will provide a good path forward.


Photo credit: Flickr

Breakthrough Metrics for Solutioning a Customer Transformation Journey | Sherpas in Blue Shirts

By | Blog

There’s no silver bullet for driving change; it’s a challenge in any organization and services providers and their clients struggle with this. In working with providers and buyers on transformation deals over the years, I observed the need for breakthrough metrics to drive the change through the buyer’s organization.

As I mentioned in my previous blog post, transformation needs to start with defining the business outcome goal from the customer perspective and then translating it into issues and organizational implications that the delivery organization can align against. Those issues include metrics that you must clearly articulate at three levels in the buyer’s organization:

  1. C-level vision – Here the highest level of metrics calibrate the benefits and what needs to change in the status quo to accommodate the benefits. In the event you find you can’t get to the goal with what you conceive for the journey, you need to start again and conceive the journey differently.
  2. Direct reports responsible for executing on the vision – These metrics focus on the implications for the delivery organization.
  3. Technical talent – Metrics at this level focus on the tools, talent, and process changes that the goal affects. What are the details that the architects need to understand as they solution the goal?

Having metrics at each level puts business transformation not in light of those who are doing it but, rather, those who are experiencing it.

Service providers need to keep in mind that this shouldn’t be a roadmap with a detailed plan. But people at each level in the client enterprise need assistance in understanding what they are trying to do, how they have to measure themselves against that goal, and what the implications are to technology, talent, policy, process, and sourcing. The metrics can’t be prescriptive.

If you’re an executive, you can break through your organization’s obstacles to change by driving change through the benefit goal and the metrics that allow the organization to understand and configure against the goal. First define the experience you’re looking for. Then ask how to accomplish that. You’ll end up with a set of metrics that defines what you have to do to get to that experience.

As an example, let’s say you want to improve the speed of the employee onboarding process. What are the technologies you have to put in place? What talent issues do you have to think through? What policies and processes do you need to think through? What are the consequences of changes to those technologies, talent, policies, and processes? Now you have the metric and sub-metrics that help guide those implications.

Once the client organization is committed to the transformation journey at each level, the service provider can then engage with them around how that should be done.


Photo credit: Flickr

Transformation Services Procurement: What’s Wrong with this Picture? | Sherpas in Blue Shirts

By | Blog

For large transformation projects, the services world has locked itself into a world permeated with high dead deal costs, wasted solutioning, and long transitions of nine to 18 months where the client sees low value and tries to get the provider to absorb the cost as well as expensive consultants and legal fees for the client on top of distracting management. And in the end, we have a lot of unhappy clients. This needs to change.

Remember John Lennon’s song: “Imagine?” Imagine a world in which we compress these cycles and we don’t have high transition costs. As Lennon wrote, you may say that I’m a dreamer, but I’m not the only one. Over the years there have been a lot of experiments in how to shorten the sales cycle. But largely they were frustrating. Even when you rush through the process, it still tends to straighten back out to the nine-plus months’ duration because it takes time for the enterprise to understand and absorb the journey and get to decisions. Others have experimented with sole sourcing, but it doesn’t really shorten the sales cycle and has a lot of limitations from the client side in terms of leaving them wondering whether they got a market deal, despite benchmarks and pricing assurance.

From studying this over the years, I’ve come to believe that as long as providers and clients define the goal in terms of procurement, they’re likely to be disappointed. The process and price become too influential and the provider loses sight of the client’s real goal. So they end up with incremental gains but not breakthrough, transformation gains.

Let’s think about these deals as transformation journeys instead of procurements. Just imagine ….

After all, the client doesn’t want the outcome to be a contract; the outcome needs to be a transformed state of the client’s process or capability. So we need to reconceive the origination of these transformation deals along this line.

We need to first focus on the benefits, defining the game-changing benefits the enterprise wants to build. Typically those benefits in today’s world have something to do with efficiency gains, cost savings, better aligning the process to the requirements of the business users, and improving the speed and agility to be responsive to the business needs.

If service providers stop thinking about the procurement process and think from the consumer’s point of view, it works great. The client gets what it wants and needs, friction is reduced, it’s clear what the client needs to reach its goal, and the provider gets to pull the client on the journey rather than pushing and selling to the client.

After defining the business outcome goal from the client’s perspective, the next step in developing a solution would be to develop breakthrough metrics to drive the change through the client’s organization. I’ll discuss this in my next blog post.

The parties build the journey together, and the client sees the solutioning as value rather than a sales exercise to be viewed with skepticism. In effect, this method turns the procurement process on its head and eliminates the sales cycle. The provider get paid to assist the client in solutioning rather than for building a complete construct to be compared to competitors’ solutions and examined at every level.

The result is a better outcome, focused not on contractual terms but on results for the client. And this process goes a long way to eliminate the nettlesome issues around the procurement transition phase because transition is accomplished as the transformation journey progresses. Just imagine.

In John Lennon’s words, I hope someday you’ll join us, and the world will be as one.

“My Digital is Bigger Than Yours” and the Technology Pulp Fiction | Sherpas in Blue Shirts

By | Blog

It’s the middle of the week and despite all the caffeine-induced stimulation I am in a cynically contemplative mood.

Reason? The past 6 weeks have been spent attending analyst events and conferences, listening and debating with business leaders and thought leaders on what will make the global services industry click. There has been a flood of “paradigm-changing” buzzwords, new solutions on the horizon, and yes, the predictions that claim to change the world in the next 24-36 months. I’ll not go into the details but if you have managed to find your way to this blog, you probably have already heard these terms – Innovation, Robotics, Automation, Digital, and Internet of Things! (And are probably thinking – “here goes another blog on digital transformation. Yawn!”)

That “yawn” is a symptom of the problems facing the technology industry. Gone are the days when you would look at a new product or an interface and say – “Wow!” I think the last time I exclaimed wow was more than a decade ago when I first saw a GPS map and the smooth voiceover guiding me to my destination. Since then there indeed have been some “Aha” moments but nothing that made me fall off my chair. The reason probably is this – most of our attention has been on innovation rather than invention.

  • Innovation is putting together working concepts and turning them into industrialized mass adoption successes
  • Invention is creating a new concept altogether and make it work

Frankly, all the innovation that we talk about today is a mishmash of just three inventions – computing, internet, and devices. Robotics – check. Automation – check. Digital – check. Internet of things – check! True, we are working on miniaturizing, increasing processing speed, writing hugely complex analytics code, and building beautiful interfaces. Reality check – we are still just exploring the “art of the possible” with the Legos.

What is wrong with that? Absolutely nothing. Incremental invention (or innovation) is a great thing. My issue is with paradigms that are dime a dozen these days. Here is the problem – We are in the age of the “moolah.” Theoretical or conceptual innovation has lesser weight since anything that is not investor-funded and cannot be in hands 18 months down the line, is meh. And that is why the less than smart pursuit to reset and invent terminologies instead of true touch and feel invention. Due to lack of true innovation, buzzwords and bubbles are what keep investors excited and money mobile. And these buzzwords are finally leading to madness.

Each industry event I went to saw analysts and leaders beating each other up with their own definitions of what “Digital” meant – for some it was “business transformation using digital,” for some it was “SMAC,” for some it was “driving growth and efficiency using digital,” while some lazy ones were resigned to “anything that is not analog”! Frankly, this debate made me cringe. It is only when industries lack true innovation that they resort to chest thumping using buzzwords. Global automotive industry is a case in point. Till Elon Musk came along, it was all about lines and curves, three-year warranties, and miles per gallon.

Hence, while I take another sip of my café Americano, I hope a maverick comes along and says, it’s time for telepathic computing, time travel, and an invisibility cloak. Gulp!

Digital Marketing? Digital Will Kill Marketing | Sherpas in Blue Shirts

By | Blog

“When you have a hammer, everything looks like a nail.” This quote from The Psychology of Science easily, and disconcertingly, applies to many of today’s marketers, who are vigorously using digital technologies to “nail” the multiple customer touch points – e.g., context-based services, IoT, mobility, and social collaboration – at their disposal.

Indeed, there is significant vendor sponsored “research,” from the likes of Adobe, IBM, Microsoft, Oracle, Salesforce.com, SAP, and marketing consultants, that hammers home the idea that marketing has no future without digital technologies. Volumes of literature debate and explain how digital technologies are changing the role of traditional e-marketing, and that these technologies are providing the needed ammunition in terms of social conversations, mobile interfaces, and consumer analytics.

But there’s been surprisingly little discussion on whether marketers are overdoing it, whether all marketers are equally equipped to drive such technology-heavy initiatives, and whether digital marketing strategies benefit everyone, all organizations, across all industries. Here’s my take on a couple of these points.

  1. Most marketers do not fundamentally understand technology: For example, they get carried away by Facebook likes, and overwhelmed or too excited by what they see from marketing technology vendors, such as a new content management platform, irrespective of the value delivered. Though there is “hot money” flowing for digital marketing, this should not drive the adoption of digital technologies. For example, the business case of data analytics may become an “availability heuristic bias” without realizing whether it delivers good or bad data, or whether it can produce meaningful insights and business value or just become another academic exercise to please business leaders.

  2. Digital marketing is not about only marketing anymore: Earlier marketers could operate in their ivory towers with somewhat limited integration with the broader organization, as digital technologies were limited to email marketing, surveys, and/or occasional mobility projects. Today, however, with the plethora of customer touch-points, the fundamental shift in consumers’ interaction with a brand, the confluence of big data, the IoT, context-driven services, and mobility, marketers must realize that digital impact is broad-based across the organization. Many different departments, including production, support, supply chain, procurement, operations, customer service, and IT, need to be in synch to drive a meaningful digital marketing strategy. If the entire organization is not geared toward this transformation, the digital marketing efforts will eventually turn into traditional e-marketing, creating little business value.

Effective digital marketing should result in seamless excellent customer engagement, and requires an overhaul of multiple interconnected processes within an organization to avoid actually driving a disconnect with the customer. A plethora of digital technologies cannot improve a bad business process. Therefore, marketers have the difficult task of taking the entire organization together, explaining why process changes are required, how to improve customer touch-points, and how to build a customer experience lifecycle.

But, are marketers capable of doing this? Do they have the needed support and mandate from senior executives? Do they have the required organizational standing and stature to drive these changes? Can they fathom and swim across the political landscape and inertia of their organization?

Most importantly, marketers must keep the customer top of mind when considering use of digital technologies. The reality is that extreme technology leverage may confuse, frustrate, and overwhelm the customer. The branding message may get convoluted, confusing, and irrelevant. Though increasingly marketers are becoming more tech savvy, they should never forget their role is not to adopt latest digital technology but to serve their customers.

Digital channels are means to an end, not the end by themselves. For marketers, it is easy to get carried away by believing new technology is “digital marketing.” But what they may not realize is that “digital” may actually be killing marketing.


Photo credit: Flickr

Pervasive Artificial Intelligence in Software: Trends & Impact on Outsourcing | Sherpas in Blue Shirts

By | Blog

One prediction I have made about the future of service delivery automation (SDA) is that increasingly enterprise software will have the technology embedded. This is particularly true of intelligent and cognitive type of tools. I expect these to become a common feature of enterprise software in the next 5-7 years.

We saw this kind of trend in the earlier days of business intelligence and reporting. The popularity of third-party tools saw the functionality built into enterprise software. As well as reports on activities, dashboards started to feature in applications giving instant views of what was going on in the enterprise. We do not have to look far to find such software today, for example, Blue Prism, includes analytics that report on operations and performance of its robots.

A current example of a more intelligent enterprise software is Oracle Policy Automation Cloud Service. This reads policies written in natural language. Then based on business rules and the policy, it decides what questions to ask the customer, performs eligibility checks, and produces a decision report.

Another example is HighSpot, an enterprise search tool that uses natural language processing for searches and machine learning for finding the most relevant information and ranking the results.

The availability of open source machine learning software libraries, such as Apache Mahout, and software tools from industry giants, such as Microsoft (Machine Learning Service on Azure), will accelerate the next generation of smarter enterprise software.

Some would say that intelligent enterprise software would be function-specific, but I believe some varieties will be able to do more than one thing within large software applications. The need for standardization of interfaces to these tools and the ability to interact with other intelligent applications will grow over time too. We could even see more automations crossing paths across workflows leading to more complex machine-based decision making.

The question is what impact will pervasive intelligence have on the outsourcing industry:

  • On the one hand, intelligent software will shrink the size of the workforce that is needed to fulfill many services and thus reducing the need for outsourcing
  • On the other, intelligent software will open up opportunities for outsourcing processes that have not been outsourced before:
    • These could be heavily document-centric processes, such as anything involving the administration and management of searching large volumes of content, for example, for legal discovery
    • The processes could also be the evolution of other processes. For example, in hospitals we might see the patient “meet-and-greet” services outsourced to service providers who can also run basic health checks supported by AI engines to produce first-pass health assessments, before the patient is ushered to see a doctor
  • Another outcome will be higher expectations of artificially intelligent outsourcing services; upping the ante for smarter outsourced processes – this is inevitable as those on the buy-side of the market become more and more accustomed to intelligent software.

Intelligent enterprise software is here. And we are on the brink of it becoming pervasive and commonplace. As it does, I’ll continue to share my insights on its evolution.


Photo credit: Flickr

Automation Introduces New Business Risks | Sherpas in Blue Shirts

By | Blog

Automation has the essentials for introducing different kinds of business risks and risk at a different order of magnitude. The new risks manifest differently and have greater consequences than in a normal business process. The issue is the difference between type 1 and type 2 errors.

  • Type 1 error. This is a normal error such as making a mathematical error on an invoice. The consequences are that you would under-bill or over-bill a client. Once you reconcile the error, you may have lost a revenue opportunity or may have to rebate the client for the difference in overcharging.
  • Type 2 error. An example of this situation is that you under bill all your clients. The consequence is often 10X or more the impact of a type 1 error.

We at Everest Group have discussed with clients this impending shift of business processes to a far more automated landscape where type 2 errors are inadvertently introduced.

In a previous blog, I talked about automation bias and how people tend to blindly come to accept or believe whatever comes out of an automated tool. This makes the likelihood stronger that type 2 errors would occur.

On an industrialized services basis with broad-scale business processes, we must be aware of type 2 errors and guard against them. This is why many of the leading firms that are looking at adopting automation, cognitive computing, and robotics are considering implementing a Center of Excellence (CoE) to help the business understand the changes that accompany automation. A CoE can help educate employees to guard against automation bias and type 2 errors that could inadvertently be institutionalized in automated approaches to business processes.


Photo credit: Flickr

A Light Bulb Has to Want to Change | Sherpas in Blue Shirts

By | Blog

There’s an old joke that asks how many psychologists it takes to change a light bulb. The answer is it doesn’t matter; the light bulb has to want to change. I think this has a deep truth when applied to the services market.

Almost every service provider looking for growth sees that capturing a share of the transformational marketplace is key to their success. In their effort to pursue this, they come up with arguments and proof points that they can do a business function better, faster and more cost-effectively than shared services or the target organization. They then conduct significant analysis, looking at which customers would be the best fit for their strategy.

Unfortunately for these providers, their efforts often are frustrating and come to very little reward. The reason can be seen in the light bulb joke. The key to significant transformational change has less to do with the potential impact and more to do with the motivations of the client and its willingness to change. Few people can be squeezed to undertake the risk of a significant large-scale change and transformation.

Key for service providers

Service providers seeking to capture transformational deals must first identify senior executives with a change agenda and then gain an understanding of how they wish to change. That is where the transformation journey must start. Although this sounds obvious, my experience has been that providers rarely approach the problem from this perspective.

When you couple this starting point with the changing objectives of customers focusing on business value and cycle time instead of costs that I’ve blogged about before, it’s easy to understand why so many providers’ strategies fail. Looking for transformation opportunities through the lens of cost savings is a mistake, and increasingly the provider’s efforts will go unrewarded.

Just like the light bulb joke, transformation opportunities won’t happen unless the customer wants to change and the provider understands what the customer wants to accomplish through the change.


Photo credit: Flickr

Automation Bias | Sherpas in Blue Shirts

By | Blog

We’re at an inflection point in the ITO and BPO services world where we’re about to see a new level of technology: automation. On the whole, automation is a good thing. But there are some significant aspects we should be aware of. One is automation bias. And it’s dangerous.

When we move to automation, whether it’s cognitive computing or replacement of repetitive tasks, the people who are in the process become dependent on the automation. In fact, not only do they become dependent, they start to believe that whatever comes from the computer is truth. They take it for granted that the results are accurate. This is automation bias.

As a simple example, when you use a calculator, you quickly start to trust whatever the calculator results are. We have blind trust in automated tools.

Why is automation bias so dangerous?

A computer will slavishly do what it’s told to do or will run down the same cognitive analysis it has done in the past. When the world changes, the computer may not recognize that the world has changed. Change can come from one of the data sources having made a change. Or it could be an upstream or downstream change in a business process. Although people in the business process should recognize the change, automation bias may cause them not to recognize it because they believe that everything coming out of the computer is correct. This is a significant business risk.

The fact is automated tools are fallible. We all know that the world constantly changes, and automation bias presents the risk that the computer won’t recognize the change.

We’re on the verge of taking robotics and automation at a scale we have never done before. This will dramatically change how we perform business processes and how we run data centers. Organizations going down the automation path need to be aware of automation bias and build safeguards against it.


Photo credit: Flickr