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Tag: customer experience

3 Performance Challenges as Chatbot Adoption Grows

Today, many organizations are starting to use voice or text-enabled chatbots for the first time or already have chatbot systems in place. In fact, Gartner said 25% of organizations are predicted to make chatbots their primary customer communication channel by 2027. This is because consumer behavior has shifted to primarily digital interactions and away from traditional customer support channels.

As a result of today’s digital landscape, consumers are now accustomed to immediate gratification and expect instant responses and resolution from customer support, which makes chatbots an ideal solution for brands to rapidly serve customers. Due to this rising demand for instant customer service, chatbot systems have become more sophisticated and consumers’ reliance on them is increasing. This increase in adoption has led to higher performance expectations for bots and if those expectations are not met, customer satisfaction and brand loyalty will suffer.

Below, we’ll look at three major challenges tied to the growing popularity of chatbots as they handle larger and more diverse groups of customers, and how business leaders developers and DevOps and customer experience (CX) teams can tackle these common challenges with a continuous testing approach.

The Pain Points of Adoption: 3 Key Challenges as Chatbot Usage Grows

As the popularity of chatbots explodes for customers around the world, the underlying systems that handle natural language processing (NLP), latency, data security and other functions need to be stronger. This is due to a growing and increasingly diverse demographic of users, many of whom are sharing more of their personal information to address a wider range of customer needs. Common chatbot pain points can be summarized by three overarching challenges.

Challenge #1: Chatbots must contend with a larger and more diverse base of customers

Chatbots that are voice or text-enabled must be smart enough to operate securely while navigating countless variations in spelling, a wide range of spoken accents and vernacular, background noise, static from bad connections and more. Even in a single language, there may typically be only four or five “intents” from most customers in engaging a chatbot, but those intents may be phrased in hundreds of different ways. Now, the global growth in adoption raises the chance of poor connections and exponentially increases the number of languages and variations in phrasing that a chatbot must understand and interpret.

Challenge #2: Customers are trusting chatbots with more personal and sensitive data

As chatbots become smarter and more trusted by customers to meet their needs, people are getting more comfortable giving their personal data to chatbots. That increases the number of situations where chatbots are working with personally identifiable information (PII) or other highly sensitive data. Especially given GDPR and other data privacy regulations being enacted worldwide, there’s added pressure to ensure a chatbot system’s handling of this data remains secure and compliant across all use cases and geographic regions.

Challenge #3: Modern chatbots require 24/7 availability and reliability

In an era of flexible work and millennial and Gen Z audiences interacting with bots after business hours and on weekends, chatbots can’t afford to work in shifts. Users may be spread across many time zones or around the world, meaning there’s always a sizable portion of customers awake, online and looking for fast and efficient service. Because of this, chatbots must be able to handle spikes and heavy traffic 24/7.

The executive takeaway from these challenges is that modern chatbot investments must be built around dynamic systems capable of adjusting to shifting customer usage and performance requirements.

A Continuous Testing Mindset is Required for Top Chatbot Performance

Fortunately, by honoring a few best practices and making the right strategic technology investments in automated artificial intelligence (AI) and machine learning (ML)-driven systems, C-suite leaders responsible for CX and the teams they manage can deploy chatbots capable of keeping up with the above challenges. Perhaps the most central element for success is to embrace a continuous testing approach.

For example, when a company is undergoing digital transformation and shifting its contact centers and supporting systems to the cloud, they are moving a significant amount of data, reimagining complex integrations and rearchitecting processes. In order to maintain application stability and existing integrations in the contact center, continuous testing is critical to ensure that an organization’s systems still operate effectively throughout the cloud migration process. With continuous testing, development and testing aren’t separate processes. The testing is automated and quality assurance is involved as developers submit code.

The most effective approach to continuous testing includes end-to-end analysis across all channels. Testing chatbot behaviors should mimic real-time customer interactions. This should include challenging scenarios such as unexpected user inputs and usage spikes at random times of the day and night. Automation is critical, especially in peak demand scenarios such as Black Friday, Cyber Monday, open enrollment, etc. Load testing up to 1,000-100,000 bot requests per second, or more, can help ensure companies will be able to handle the increased traffic. Ideally, the testing approach should be comprehensive to include automated NLP score testing, conversational flow testing and security testing and performance testing and monitoring.

By promoting the continuous testing approach across contact center operations, executives can empower their teams to build and maintain chatbots that remain optimized on an ongoing basis and that form an essential part of providing exceptional CX. This will make a huge difference in performance and reliability as systems scale and adapt to the evolving demands of a growing customer base.

Continuous Testing Elevates Chatbot Reliability and Value

High-performing chatbots and the continuous testing that keeps them optimized at those performance levels can benefit any company by lowering risks and enhancing revenue. Organizations that become adept at applying continuous testing avoid 90% of the downtime from high-severity (SEV 1) errors, which can result in saving $2.2 million in costs over a three-year period. When continuous testing touches every stage of the development process, it identifies issues earlier and helps strengthen an organization’s ability to innovate faster and service its customers effectively and profitably.

January 31, 2023
The Importance of Customer Experience Observability

Ask anyone to name their favorite brand, and they’ll often respond with minimal hesitation. Prod a little further and the importance of customer experience (CX) is sure to play a major role in their response. In fact, 96% of consumers say CX is a key factor in their choice of loyalty to a brand. This sentiment is even more powerful post-pandemic, with 58% of consumers saying they place more importance on CX when making purchasing decisions than they did pre-pandemic.

Will the importance of CX only increase? That’s a safe bet. So how does a business get to Apple, Disney or Amazon-level CX? Reliability is a good place to start.

Reliability—in the context of a digital-first business—is the ability to quickly identify and resolve issues before they reach the customer. Reliability is a critical demand of both consumers and enterprises as they pursue digital transformation, especially cloud migration and automation.

Achieving reliability may sound rather straightforward, but many factors in DevOps often work against reliability. For instance, many DevOps teams focus solely on technical performance metrics but turn a blind eye to CX metrics like churn rate or net promoter scores (NPS). Some business leaders fix this with advanced AI and machine learning technology, but too often those solutions don’t live up to expectations enough to provide a return on investment (ROI).

Observability, on the other hand, is an approach that collects and analyzes data on every component of a system, application and infrastructure—from performance to security to accessibility. This information allows DevOps teams to glean insights on the reliability of actions performed within a unique business environment, such as an interactive voice response (IVR) system or a contact center.

Gartner defines observability as the evolution of monitoring into a process that offers insights to speed innovation and enhance CX. To establish digital observability, DevOps teams should consider the following components.

Enable Automated Testing of Digital Technology Functions

Every day, companies are losing revenue due to a lack of customer experience observability. Forrester reported that more than $1 billion in potential revenue is being left up for grabs. This is largely due to poor comprehensive customer experience technology investment decisions. As DevOps teams work to deliver new CX innovations—like personalized VR shopping experiences or advanced AI-based chat support functions—they do their best to foresee potential flaws or bugs. However, flaws will inevitably creep in. That’s why consistent observability is crucial. Observability helps DevOps practitioners see these issues quickly and gives them optimum time to respond before it becomes a costly threat to customer experience.

To provide this level of observability, data must be available, accurate and analyzed in real-time. This requires automated solutions because the faster a data set can be analyzed, the more value it will deliver. Automated testing tools work by generating thousands of synthetic omnichannel interactions to test the customer journey from the outside-in—from the network through IVRs to digital apps and routing systems, all the way to agents at their desktops. Automated testing of elements such as connectivity, responsiveness, quality and functionality can help DevOps teams ensure quality is achieved throughout the entire CX development life cycle.

Determine How Test Data Will be Used to Improve Reliability

Detecting issues early also requires precision and intentionality that answers questions like: What data will be collected? Who will own and examine the data? Why does that data matter to our business? Being able to analyze, organize, manipulate and share test data helps DevOps teams have greater ownership and oversight over information that’s constantly coming in.

DevOps organizations benefit from using a platform that centralizes all voice call test data for the entire team so that nothing is missed, and the data can cover a wide array of use cases. Typical test datasets might include information on factors such as customer persona labels (for example, Gold, Silver and Bronze customers or labels by Line-of-Business), order status or payment methods. A centralized monitoring and testing platform allows DevOps teams to create and import comma Separated Values (CSV) files to create a test dataset for a specific IVR and then use it to test the organization’s other IVR systems to save time by not re-creating it manually. It’s also important for internal teams to be able to track who is modifying test data, when it’s being modified and which test cases are using specific datasets.

Dedicate an Executive Champion of Customer Experience

E ighty-four percent of businesses that focus on improving CX report an increase in revenue. Executive investment in CX is critical here and considering the ROI, should not be a difficult sell. To go even further, businesses should consider establishing a leadership role that is responsible for proactively addressing CX and reliability.

For CX digital transformation initiatives to succeed, they must be led by an executive leader who can champion the need to drive cultural change and strategic investments. Appointing an executive to this role will ensure that CX initiatives aren’t siloed from DevOps teams, but also from the rest of the enterprise, including sales, marketing, operations and more.

Some organizations choose to create an entirely new chief CX officer role so that the leader can give their full attention to CX transformation initiatives, processes and technologies. Others, depending on the company’s organizational structure, may decide to appoint these responsibilities to the current COO, CIO or CMO. Whatever the decision, the digital transformation leader must have broad authority that covers budget, people and processes in order to be effective in their role.

Focusing on observability within customer experience technology will help organizations improve their reliability as a brand. With greater observability and automated testing capabilities, DevOps teams will be empowered to innovate faster and deliver higher-quality solutions that will improve customer interactions and solidify brand loyalty for years to come.

April 13, 2022
DevOps for Customer Experience

Charlene O’Hanlon and Amy Hudson of Cyara discuss the concept of DevOps for customer experience, which takes DevOps methodology and focuses it on CX software. But there are pitfalls DevOps teams face when dealing with customer experience software. The video is below followed by a complete transcript of the conversation.

Announcer: This is Digital Anarchist.

O’Hanlon: Hey, everybody, welcome back to Tech Strong TV. I’m Charlene O’Hanlon, and I’m here now with Amy Hudson, who is the VP of Global Center of Excellence at Cyara. Amy, thank you so much for taking a couple minutes and talking with me today—I really appreciate it.

Hudson: I’m happy to be here.

O’Hanlon: Great, great. So, Amy, tell me a little bit about Cyara to start off.

Hudson: Oh, absolutely. Cyara has been around for about 10 years at this point, but we really focus on what we call customer experience assurance. Companies spend a lot of money in designing the right customer experience and all the technology that supports it, and Cyara is in the business of making sure that you are getting the experience you’ve invested in. And if you are, how do we help you continue to innovate and double down? And if you’re not, how do we help you fix it very quickly so you can stay ahead?

O’Hanlon: Alright. That sounds great, and I imagine your business has been booming over the last year or so, because customer really came to the forefront for a lot of organizations as they kinda had to double down on their digital transformation efforts just to stay alive over the pandemic, over the last year and a half or so. And some of them have done it really well and others have not done as well.

So, what are you guys seeing in the market right now as far as customer is experience is going?

Hudson: Yeah, no, that’s a great question, because it has changed a lot in the last year, with the pandemic. I mean, listen, customers have historically always been demanding, right? That’s in our nature as customers. But now, with their hands on the technology, customers have very high expectations right now. And switching costs are low. So, if a customer doesn’t get what they’re looking for out of an experience, you may lose them.

And so, the importance of having a good customer experience and staying ahead of it is at an all-time high from our perspective.

O’Hanlon: So, we’ve been, obviously, you know, through devopsy.kinsta.cloud, we focus on the benefits of going with a, kind of a DevOps methodology and mindset and culture shift and all that good stuff. And we’ve seen kind of that whole premise of DevOps kind of shifted to other parts of an organization as they recognize the benefits of kind of blending two different maybe mindsets and areas of an organization together to kind of streamline operations and actually build a better product in the long run.

I imagine customer service is not—has not been left out of the conversation when we’re talking about organizations adopting those DevOps principles for customer experience.

Hudson: Yeah, that’s right. It’s interesting. So, about four or five years ago at Cyara, we started seeing DevOps fold into the contact center/customer experience space, but it was a little bit more of a rarity then. DevOps hadn’t necessarily intersected with customer experience yet at that point, but over the last three couple years or so, we’ve really seen DevOps become much more commonplace in the customer experience space. Which I think is a good thing, because, exactly what I mentioned before—you need to stay ahead. You need to be able to innovate quickly for customer experience, and I think these companies are starting to see that.

So, we’re starting to see DevOps adopted almost universally. Either somebody has started it or is halfway through or a little more mature, but it’s in the conversation with almost everybody we talk to these days in terms of customer experience.

O’Hanlon: That’s great. That’s really great to hear, because there are certainly a lot of benefits to DevOps in the customer experience space, you know, not the least of which is being able to service the customer much more effectively and quickly.

But it’s not kind of a one to one adjustment, though. You know, it seems like, especially since, when we’re talking about DevOps, we recognize that each DevOps implementation and each DevOps experience, if you will, is different. You know, everyone is kind of a snowflake.

So, how does that equate to the customer experience and how might that actually kinda trip up organizations if they’re looking to kind of add DevOps to their customer experience?

Hudson: Yeah, absolutely. So, when I first started at Cyara, I led a very small strategic consulting group, and we worked with customers on how Cyara can help them through any major transformation. And because of the shift of the industry, it ended up being a lot of DevOps transformations. And so, we’ve seen customers at multiple different points in the journey, and the struggles that they’ve bumped into. And I think there are a number of different kind of pitfalls if you will, or lessons learned from that.

And, you know, one of the first things—and we can go into as many of these that are of interest, but one of the first things and most important that pops out at us is that leadership level cultural shift. I think, so frequently—and I’m leading with this because if you don’t get this part right, it’s really gonna hold you up. But so frequently, DevOps is viewed as a technical or process change and so, it happens at the day to day level. But really, it is a mind shift, cultural shift, has to be top down, has to be embedded in the culture, and it has to be leadership driven.

O’Hanlon: Mm-hmm, yeah. I agree, agree, and that goes across an entire organization, no matter where they’re implementing DevOps, whether it’s in IT or if it’s in the back office or marketing. Because we’re seeing this blending of so many different disciplines in an organization these days as ways to advance and accelerate just their ways of doing business.

But to your point, if we don’t have, or if an organization doesn’t have that buy-in from the top, no matter where they’re implementing DevOps in an organization, it’s doomed to failure.

Hudson: That’s right, that’s right. And it’s, you know, and it’s not just the kickoff, it’s not just somebody at the C level saying “rah rah” at the beginning.

O’Hanlon: Right.

Hudson: This is, like, through the process, embedding into how you motivate, incentivize, how you reward people, how you—you know, in your regular cadences. It’s everywhere. It needs to be treated as a cultural shift.

O’Hanlon: Yeah, yeah. I totally agree. Now, what about, you know, beyond kind of that initial, as organizations start to kind of adopt this mindset and these principles, what are some of the things that maybe we call it kinda DevOps Phase Two or DevOps 2.0, the Second Day DevOps—what are some of the things that you guys are seeing that organizations need to be very mindful of to make sure that they are successful?

Hudson: Yeah, another thing that we’re kinda bumping into at more of the kind of operational level is, as you know, the importance of flow in DevOps, right?

O’Hanlon: Right.

Hudson: You don’t wanna disrupt the flow. And to do that well, you have to think about automation, right? It’s just—it’s a no-brainer. It’s a pillar, right? And to me, when I think about automation, there’s a lot of different pockets you can automate. But for me, I think primarily around deployment automation and testing automation.

We did an interview—or I did an interview with a consulting, one of the big four consultants with the DevOps expertise and a customer. And both of them agreed that automating the testing, while it’s not always completely simple or straightforward, it is, they would almost consider it the low hanging fruit, right? Get the testing automated so you can just kind of plug and play that part of it, don’t disrupt the flow.

From a deployment perspective, there’s a number of different environments, right, to get something into production. So, the more you can automate from that perspective, the more you can continue to push things out and learn fast and fail fast, if you will.

And so, finding those pockets of automation and having a strategy on how you can automate as much as possible as to not disrupt the flow is something that we’re really recommending to folks to realize the total benefit of the transformation.

O’Hanlon: What about from a people perspective? You know, DevOps is as much about culture, as we know, as it is about the processes and the technologies. So, are there ways that organizations—maybe they’re not thinking about particular things when it comes to culture and people in their adoption of DevOps specifically for customer experience?

Hudson: Yeah, sure. So, I would answer that a couple different ways. The first one I would talk about is essentially around—this is, again, it’s a culture thing. One of the pillars of DevOps is to create an environment that encourages learning and a safe place to fail. And so, you want your teams to be encouraged to fail if they have to and learn from it and get better the next time and feel safe doing that. So, that’s one from a person perspective.

The other thing I would mention is just around measuring, key performance indicators, right? You can’t know if you’re successful without measuring, right?

O’Hanlon: Mm-hmm.

Hudson: And then publishing those KPIs so they’re transparent. Transparency is really important, so everybody is charging towards the same goal, and everybody feels like they are part of achieving that goal. So, let’s get the performance indicators out there, let’s be clear what we’re trying to achieve, let’s make people feel safe in that process. And, you know, that’s kinda the culture you wanna build around it.

O’Hanlon: So, when we’re talking about customer service applications and software versus, say, an internal process or internal DevOps process or an internal application that is being advanced by these DevOps processes, what is the difference when we’re looking at what may be what those KPIs are or what the service level objectives are, things like that? Are there certain things that an organization needs to be more mindful of when they’re working on a customer experience type software rather than maybe more internal focused or maybe other customer that’s not maybe customer facing, end user customer facing?

Hudson: Yeah, I think that’s a great question. And what we’re trying to do within our industry is create this mind shift where you are thinking about the end customer all the time—not just in the production environment, you are always thinking about the end customer experience through every step of the journey.

And I’ll give you an example of what I mean by that. Traditionally, the contact center space, how they would monitor things in testing or production is kind of server loads or capacities, right? If it’s reached capacity, it’ll set off an alarm and that’s a problem, right? You don’t want it to be at capacity.

Great, but you might not know what the customer experience is if that server is at capacity, right?

O’Hanlon: Mm-hmm.

Hudson: And so, at Cyara, what we’re trying to do is say—absolutely, that server might be at capacity and that’s a problem, but what is the customer experiencing in the moment right now in production? But we also wanna test in Dev and QA and UAT and performance testing, what the customer experience would be. So, if there’s an issue that comes up, you know it could be a pretty serious one, it could be calls being disconnected. If, in your revenue generating phone lines or chat windows, customers can’t get through—you wanna know that before it gets into production.

O’Hanlon: Mm-hmm.

Hudson: You don’t wanna know necessarily that—or it may be less helpful to know if a certain piece of technology is at capacity. What’s most valuable is to know what the customer would experience in that moment, even before it gets into production, if you can do that.

O’Hanlon: Interesting. You know, it’s really fascinating to have the conversation about DevOps in different vertical markets, because everybody’s got something different that they’re really, really focusing their efforts on, but at the end of the day, it really is all about just making sure that the end user experience is the best it can be, and that the application is working as advertised and certainly that there’s a level of security as well within that application.

So, I do imagine that security is also a big part of the equation, especially with the customer experience and the amount of sensitive data that a lot of contact centers, to your point, that they’re dealing with on a regular basis. So, heavy emphasis on Sec on DevSecOps?

Hudson: Oh, absolutely. And that’s really from two ends. One is that customer data, right? There’s—you have to protect that. There are sensitivities, and those need to be protected, and we need to invest in those, and you need to be able to test that in production or prior to that if possible, right?

But the other side of it, too, is around the regulatory requirements, right? Customers will—our customers, large companies—will get fined if certain requirements aren’t met, right? And so, from a pure business perspective, you’re motivated to make sure the customer is experiencing that requirement. But then from their own protective perspective, you’re also motivated.

And so, DevSecOps, we really encourage people to fold security in very early in the discussions. It’s often one of the last things to come up—“Oh, wait, did we talk about security, did we bring in that team?” Fold them in early, complete transparency, get the conversations in and weave them into the process, because it’s critical.

O’Hanlon: Excellent, excellent. Amy, this has been a great conversation. I’ve really, really enjoyed it, and would definitely love to have future conversations with you about other topics related to DevOps and the customer experience, because I really think that this is something that is—it’s not gonna be a one and done conversation. It’s like DevOps. Customer is an evolving conversation.

But for now, thank you so much for taking the time and having the conversation with me. I do appreciate it.

Hudson: Thanks for having me. It’s a privilege to be here.

O’Hanlon: Alright, great. Alright, everybody, please stick around. We’ve got lots more Tech Strong TV coming up, so stay tuned.

[End of Audio]

February 14, 2022
The Next Phase of Pandemic Tech Transformation

Last spring, we were inundated with headlines, tweets and Medium posts applauding the rapid digital transformation that businesses were going through—almost overnight—due to the pandemic and the shift to remote work. It made for an interesting feel-good narrative at the time, but it didn’t paint the full picture. Companies were thrown into the deep end; many barely staying afloat by implementing quick-fix, surface-level changes that they assumed would only be needed for a short time. Turns out, the “transformation” touted was just the tip of the iceberg.

More than a year later, the workforce is still in flux. The reality is, some form of distributed, hybrid work is likely here to stay. Employees will continue to expect remote options and customers will want seamless, digital ways to interact with businesses, pandemic or not.

As a result, companies must move past the temporary, band-aid solutions of last year and make those sweeping changes permanent. It’s time to move forward with true, sustainable change: Technical, experiential and, most importantly, cultural. Every company will need to become a modern technology company capable of delivering first-class digital solutions to customers, partners and employees—or risk becoming obsolete.

Transactional Vs. Transformational Change

The good news is just about every company understands the value of leveraging technology. A recent 2021 State of the CIO survey found that 82% of CIOs said they implemented new technologies, new IT strategies and/or new methodologies over the past year. The issue is how companies go about their technology deployments.

People talk about digital transformation all the time, but it’s been used so much that it has become an unhelpful misnomer. More often than not, the change that companies are implementing isn’t truly transformational, but rather transactional or just slightly incremental.

When companies have a transactional mindset, the focus is on immediate, simple and predictable changes. The purpose—or, more importantly, the outcome—is simply to continue business-as-usual. This is reminiscent of many companies last year turning to technology just to keep the lights on. A transformational mindset, on the other hand, aims to disrupt this business-as-usual and fundamentally change the paradigm in how the company operates through ways of working, use of technology and culture. It’s purposeful, aiming to solve business problems holistically and spur long-term growth.

To be successful in today’s climate and to gain a competitive edge with customers, companies must strive to be transformation-focused.

How to Move Toward True Transformation

Here are three examples of how companies can shift from a transactional mindset to a transformational mindset.

Cloud Migration vs. Modernization

Often, when companies talk about their use of cloud, they tout that they’ve “moved to the cloud.” But all too often, it’s treated as a one-time event; a destination to reach and a box to check. At the outset of the pandemic, we saw so many organizations quickly mobilize to shore up their digital strategies and ensure they were thinking about the limitations of doing business in a virtual context, but their cloud strategies didn’t evolve to rethink these paradigms, as well. They simply accelerated their migration strategies to get out of their physical data centers and into the cloud.

The opportunity to leverage the cloud is so much bigger than that. It can unlock greater efficiency, flexibility and growth and underpin new digital experiences and revenue opportunities—exactly the kind of strategies most companies envision. For example, health care leader InnoCare was struggling with outdated clinic management software. Instead of just moving the old bits to their cloud provider, they adopted a broader digital strategy to modernize their delivery capabilities and reimagine both the patient and clinician experience, setting new industry standards in the process. This is what we refer to as modernization and it is what leads to transformation.

Software Engineering vs. Product Engineering

With the rapid growth of software, it’s no surprise that software engineers are in high demand. The U.S. Bureau of Labor Statistics projects that software engineering job openings will grow 22% through 2029. And while software engineers will play an irreplaceable role in helping build innovative solutions, transformational-focused companies know to bring more people under the tent. By combining software engineers with other cross-functional experts who bring a different level of artistry, design and audience understanding, the end result is a more engaging, customer-centric product that evolves and grows over the entirety of its useful lifespan.

This is exactly what fitness giant Nautilus did. They brought together a team of engineers, data scientists and machine learning experts to help bridge the gap between their equipment manufacturing prowess and their digital experience and software development goals. Collectively, they produced a total platform that integrated hardware, software and data to create a dynamic workout regimen that impressed users and fended off competitors.

Moving Beyond Proof-of-Concept to Long-Term ROI

A proof-of-concept (POC) is a rite of passage in the tech world. It’s how a company or team demonstrates that their idea is feasible and can work in a real-world application. But POCs alone are insufficient; they are transaction-minded and don’t focus on achieving lasting business outcomes or generating deeper ROI. Rather, they mostly focus on technical feasibility. The key to upleveling toward transformation is by focusing on the processes, not just the end product. When testing features in a real-world setting, make sure that you’re proactively measuring not just that they work—but that they contribute to business imperatives, meet customer expectations and strategic outcomes. And if they don’t, go back to the drawing board and optimize with those higher-level goals in mind.

Culture is Key

As you can see, the difference between a transactional and transformational mindset is more about culture than technology. A culture of innovation and modern ways of working leads to transformation that fundamentally shifts the way technology is conceptualized and created. It isn’t solely about gaining efficiencies or cutting costs—instead, the focus is on making the lives of customers, employees and everyday users better. Transformation-focused companies believe in the promise of technology advancements, but they believe that it also can make operations smoother, customer relationships more meaningful and increase revenue when implemented with the right combination of skills, disciplines and organizational buy-in over time. It’s those companies who will thrive in this new era.

September 7, 2021
How DevOps Can Address CX Challenges

Delivering a seamless customer experience (CX) has become a top priority for companies undergoing digital transformation initiatives, as 85% of buyers are willing to pay more for a great customer experience. However, customers aren’t only willing to pay more for a positive experience–they’ll go elsewhere if their experience isn’t positive. In fact, 33% of customers will leave a brand they previously loved after just one bad experience, and 92% of customers will completely abandon a company after just two or three negative experiences. So, delivering a positive CX has become a major priority for companies that want to retain their current customers while winning over new prospects from competitors.

To assure CX quality for customer-serving technology products and services, established DevOps processes and strategies should be applied to the unique aspects of customer experience software. DevOps for CX enables the delivery of software where the customer’s experience is paramount and quality is imperative. However, there are six major pitfalls in deploying DevOps for CX that customer-serving organizations must overcome.

What is DevOps for CX?

To understand the challenges, we must first understand the purpose of DevOps for CX.

DevOps for CX refocuses the DevOps software methodology on the unique aspects of CX software to enable greater efficiency and quality. The constant delivery of expanded CX capabilities through new software developments and features has become a priority in organizations undergoing digital transformation. But when it comes to software products for CX and customer services, quality cannot be sacrificed for speedy development. At the same time, companies must still meet the demand for rapid innovations and tight deadlines on software delivery.

Customers have higher expectations than ever before. These days, there aren’t any second chances when it comes to a customer’s experience. Social media has empowered customers to broadcast CX failures for the whole world to see. Due to the visibility of CX mishaps and negative customer interactions, a brand’s CX reputation depends on flawless execution from the customer’s first impression.

The customer is always right; so, the customer’s perspective must be the primary consideration in software development and testing. This puts significant demand on the DevOps solutions and processes specific to user experience (UX) design, as well as CX testing and monitoring. Software must be designed, developed and continuously tested and monitored in real-time. Companies need to know all the different ways a customer might use the software to accomplish their goals and quickly identify and fix any potential issues before the customer experiences them.

6 Potential Pitfalls of DevOps for CX

Underinvestment in Executive Sponsorship and Cultural Evolution

For CX transformation initiatives to succeed, they must be empowered by an executive leader who can champion the need to drive cultural change and strategic investments. An executive leader is necessary because CX initiatives typically span multiple departments: Operations, development, marketing, sales and services, for example.

Whether the leader taking on this responsibility is an existing executive or a brand new position will depend on the company’s organizational structure. Some companies assign this duty to the COO, CIO or CMO, while others create an entirely new chief CX officer role so that the leader can give their full attention to the CX transformation initiatives at hand. Regardless of the DevOps for CX champion’s title, they must have a broad authority over budget, people and processes to make their role effective.

Competing and Misaligned Incentives

DevOps is a multi-team effort. Ensuring that the teams’ objectives and incentives are aligned is key to ensuring that DevOps for CX projects are executed harmoniously. Each team should have objectives that fit their team function but do not oppose other teams’ objectives, such as speed or a low defect rate on the development side and high reliability for the operations side. These functional team objectives should be centered around respective business objectives for customer satisfaction.

Unclear Key Performance Indicators (KPIs)

Adopting DevOps forces organizations to take on a more collaborative mindset. Due to the multi-team, collaborative nature of DevOps for CX initiatives, it’s critical that KPIs are clearly communicated, widely understood, and monitored across teams. KPIs should also be widely distributed so CX can be viewed at an operational level.

Lack of DevSecOps Prioritization

Many organizations fail to recognize the importance of DevSecOps from different aspects of DevOps. Not only must customer data be protected, but larger organizations that operate globally must also ensure they are complying with regional data privacy regulations. Organizations that don’t comply with regulatory requirements risk fines and other punitive setbacks.

You must be able to test security features in production to protect both customers and your organization itself. Unfortunately, security is too often one of the last DevOps aspects to be discussed.

Different Configurations Across CX Delivery Environments

Shifting between development, quality assurance, staging and production is a major source of frustration for DevOps teams, as the environments are often configured differently. As code moves through the software life cycle and different environments, having a consistent approach to the solutions and environments via deployment automation will prevent wasted time fixing bugs that suddenly pop up when the code is moved.

Errors Introduced by Manual or Outdated Processes

Manual processes introduce opportunities for human error, causing delays and defects that result in unplanned work. Performing software testing manually is a sluggish process that not only causes quality issues and delivery delays but also reduces the amount of time developers have to execute any unplanned work or rework that must be done post-testing. Automating the CX systems’ testing results in higher quality and reliability at faster speeds, providing more time post-testing for developers to ensure the product meets quality requirements.

DevOps for CX enables companies to innovate CX rapidly by delivering high-quality software and maintaining exceptional customer interactions. As CX leaders innovate new products and services through software, DevOps for CX practices will continue to be honed over the coming years. In the meantime, following the best practices outlined here to avoid the six major pitfalls of DevOps for CX will ensure customer experiences are maintained at an elevated level.

August 26, 2021
Report: Lots of Room for Continuous Delivery Improvement

A report published by the Continuous Delivery (CD) Foundation suggests that, in terms of achieving that goal, most organizations still have a long way to go. Based on analysis of the Developer Nation survey data collected by SlashData, nearly two-thirds of developers said it takes at least one week to go from code committed to code successfully running in production. Only one in 10 developers are deploying code in a production environment multiple times per day.

On the plus side, half of developers reported that they restore service from an unplanned outage in less than a day.

The survey identified the top programming languages being employed as shell scripting languages, Go/Golang, JavaScript, PHP, Scala, Dart, C#, Ruby, Python and Java.

Surprisingly, the vertical industry furthest along in terms of achieving continuous delivery is the retail sector that has embraced digital business transformation, while the furthest behind is the telecommunications sector.

Tracy Miranda, executive director for the CD Foundation, noted that even after more than 10 years of advocacy, DevOps adoption of CD best practices remains nascent. Many organizations have adopted so-called continuous integration/continuous delivery (CI/CD) platforms, but they are mainly used to drive a set of CI best processes. CD, in comparison, has proven to be a more elusive goal to achieve mainly because each platform on which an application is deployed tends to have unique attributes. Automating the delivery of applications across multiple platforms has, as a result, been difficult to achieve and maintain, she noted.

Nevertheless, with the arrival of cloud-native container-based applications destined to be deployed on Kubernetes clusters that expose a consistent set of application programming interfaces (APIs), the prospects for more widely achieving CD are improving. Each platform that has a Kubernetes cluster running will expose the same API to a CD platform.

In the short term, however, Miranda noted that many IT professionals are still somewhat intimated by both Kubernetes and CD best practices. Too many organizations still tend to think of CD as a platform to acquire rather than a set of processes and skills to be defined and nurtured, she added.

One way or another, however, the CD challenge will need to be addressed as more organizations realize how dependent they are on software to deliver a differentiated customer experience. The rate at which that customer experience improves will determine the level of customer affinity that organizations will be able to attain and retain. That’s doesn’t mean every organization has to be as proficient as, for example, Netflix when it comes to implementing DevOps best practices, Miranda added. However, she said, it’s already apparent most organizations will need to improve how they deliver software to drive multiple digital business transformation initiatives. The opportunity lies in reviewing those processes now with an eye toward creating a culture squarely focused on continually improving the customer experience, she said.

It may still be a while before most organizations truly master CD, but, as is the case with most journeys, the most important thing is to simply take that first big step.

August 2, 2021
Digital Customer Experiences: The Future is Modular

With the proliferation of microservices and APIs, will UIs go modular too? Some technologists note a rising trend around smaller, intent-based customer experiences that more directly mirror API endpoints.

I recently met with Adam Evans, co-founder and CTO of Airkit, to better understand what’s broken with today’s digital customer journeys and how they need to evolve. He predicted that single-purpose experiences will become more pervasive in the future. In the process, we’ll likely encounter fewer native apps and fewer downloads. To enable all this, he’s putting faith in low-code to bring easier integration and automation patterns to more developers.

The State of Digital Experiences

Digital customer experiences are becoming increasingly connected and web-based, and at times, disconnected from the core service. In headless environments, end users are engaging with companies through more and more abstraction layers, such as chat, SMS, voice or email notifications. These interactions are increasingly modular and event-driven, noted Evans.

Increasingly, user encounters are the result of trigger-based patterns activated when user action is required. Not only is the communication style changing, but new devices and platforms have emerged, further making a case for a decoupled development approach. B2C apps become more modular in this transition, presenting experiences built around specific tasks and closely reflecting the specialized microservices or APIs that drive them. Consider the rise of the single page application (SPA) style or AWS Lambda as evidence.

As more automation and subscription models enable a “set and forget” attitude to commercial software, Evans predicted we’ll likely see more intent- and event-driven workflows emerge. He said these reimagined UIs would shroud platform complexity and, instead, focus on single, specialized actions, like submitting an insurance claim, checking the status of a package or updating your coffee subscription.

A Broken Customer Journey

So why would end user digital experiences evolve into more intent-driven applications? Well, complex digital platforms can get feature-bloated very quickly. Bulky applications with many menus are difficult to navigate, thus impacting user experience.

As Evans describes, generic interfaces often display tons of information irrelevant to the task at hand. “Don’t make me go through generic interfaces to help me do something specific,” he said.

Clunky interfaces are at odds with small digital tasks that involve an attention span of 20 seconds or less. Evans describes these as “micro touchpoints in our daily lives where you don’t need traditional, large applications.” These actions could be, for instance, looking up COVID-19 infection rates, checking your credit card balance or updating a streaming subscription, he said.

Organizations have other imperatives to improve user experience, too. For example, if a platform isn’t self-service, it can increase support calls, which can cost a company significant resources. Plus, if the service isn’t event-driven, users must routinely check in of their own accord, which could waste time and encourage tech anxiety.

Single Page Applications

In the age of modular microservices, the days of bulky apps and “manual polling” may be limited. To Evans, the solution lies in expressing the “minimum way to represent the transaction of that interface.”

“How do we keep moving smaller divisions from the back end to the way interfaces are built?” Evans asked. Similar to the way microservices architecture separates domains, Evans noticed UIs segmenting attention along API endpoints. He envisioned more single-purpose experiences being constructed that extend APIs and microservices with a user interface.

Technically, this may result in more single page applications being developed. Niche UI layers that map APIs would likely carry a data model, Evans described, so that micro apps are delivered with data for entering fields into API calls. As they are web-based, asynchronous single-purpose experiences could also transcend the barriers of app stores and third-party marketplaces.

Potential Benefits of Modularity

More intent-based workflows mean less overhead for the user, bringing quicker, more convenient access to the problems they want solved. Sure, users still register with a core service, such as their bank, coffee subscription service or insurance agency for centralized account management. But, users frequent account centers less often, as the periphery of interactions around them continues to grow.

“The future of apps will look more like individual, intent-based micro apps,” Evans reiterated. These would reflect a metronome of touchpoints Evans called “little moments of delight.”

Pinging users only when action is required could reduce check-ins, thus reducing digital anxiety. Aside from the user benefits, deployment and maintenance for small applications may be easier to support, said Evans. Lastly, more isolated intentional customer experiences increase engagement, response rates and sales, he added.

Using Low-Code For Customer Experiences

Connected digital experiences are relying more and more on APIs. Yet, API integration can be difficult, even for experienced programmers. So, how do we make it easier for people to build interfaces to hit these APIs? Building user-facing layers on top of APIs will require great developer experience, says Evans.

Lately, low-code has been dominating these discussions. With greater emphasis on visual-driven development, low-code is empowering non-technical employees. To Evans, low-code capabilities will be essential to influence how future customer journeys are constructed.

Evans noted how low-code “changes the whole game around how apps are built.” For example, branded experiences often require reusable code and common libraries, all of which low-code platforms excel at. In addition, when working with APIs, a “layer over REST design is essential to maintain state and enable long-term processing,” he said.

Will The New Digital Journey Go Micro?

Complex interfaces seem to work for conglomerate giants like Amazon. But other scenarios may benefit from more single-purpose workflows. As platforms become more extensive, the user interactions need to become leaner to avoid added stress. As a result, Evans predicts that micro, trigger-based B2C touchpoints will become more common in the coming years. In this paradigm, better UI extensions of common APIs could help bring people into the equation.

“We’ll see a lot of cool stuff in the next decade,” he said. “Future apps won’t look like what past ones looked like.” As IT moves to support new, multiple channels, such as chat, voice, web and VR/AR, our perception of what an application is also will inevitably alter.

In tomorrow’s “great unbundling of apps,” as Evans called it, “if you don’t use it every day, there’s a pretty good chance it doesn’t need to be there.”

There are many schools of thought on the best methods to retain quality user experiences. Do you think modularity is the answer? What do you think tomorrow’s digital experiences will look like? Feel free to let us know in the comments below.

June 8, 2021
The Role of APIs In Digital Transformation

Digital transformation is increasingly propelled by rapidly changing user expectations. Release frequency is increasing, as is the need to connect a growing number of applications and digital experiences. As a result, 83% of IT specialists consider API integration critical to their business, found the State of API Integration Report.

Application programming interfaces (APIs) hold powerful sway in tech discussions of late. Building API-first could increase internal reusability. APIs have become a standardized machine-readable mechanism for connecting partners. There is also a hot market for API startups, meaning APIs are becoming products in their own right.

APIs are also enabling change for large enterprises. I recently connected with Bernd Gross, CTO at Software AG, to get his perspective on the role APIs and integrations are playing within the new wave of enterprise digital transformation. Below, we’ll see how connected customer experiences, digital business excellence and a new ecosystem-driven economy are driving the emergence of more API-based strategies.

Three Drivers of the Connected Enterprise

Businesses continue to transform into more connected enterprises. Once relegated solely to improving back-office efficiency, digitalization efforts are being applied across the board — to employee management, assets, machines, partners and the supply chain at large, said Gross.

Amid rising digitalization, connectivity is the glue that unites disparate elements and tools. A fully connected world is “the new flavor of digitalization,” said Gross. To his point, ‘connected experiences’ is a crucial driver for 68% of platform providers, The State of API Integration Report found.

So, how are APIs fueling the new connected enterprise? Gross identified three key reasons why integration is now fundamental to enterprise digitalization initiatives.

Software AG Marketecture, used with permission.

1. Connected Customer Experience

Many organizations “want to transform into a technology and software company,” said Gross. To participate in the connected digital economy, organizations are striving to create advanced 360-degree customer experiences. Today’s technology needs to “look beyond a PC application,” Gross said. These experiences must cater not only to desktops and smartphones but also to IoT devices and physical assets.

For example, he explains how one large elevator company architected an embedded connected experience, incorporating digital touchpoints within elevators to showcase signage, entertainment and ads, opening new monetization possibilities. This change was so radical that the mechanical engineering company pivoted its mission statement, reimagining itself as a “vertical transportation company.” Soon, their AI-enabled elevators will predict behaviors and optimize travel times, so they are always on the right floor, waiting for human riders.

Intelligent building technology is similarly being applied by digital-savvy hotels, Gross explained, which is especially important for contactless visits during the pandemic. A fully digitalized customer experience could involve automated check-in, a room access code sent to a smartphone, an online billing system, physical sensors and more. Enabling a seamless digital hotel experience sounds easy, but it’s technically quite challenging — there are endless integration requirements to connect. In some cases, it would take 24 integration points, noted Gross.

2. Digital Business Excellence

Gross recognized the high expectations for modern digital experiences. He described a “new trend of business excellence in delivering more of an end-to-end digital experience.” This means data can no longer be locked up; even traditional companies must transition to platforms to offer software and data to their end users. In the process, interesting things may occur — your customers could become partners, Gross adds.

He described how one medical company, a leading centrifuge producer, sought to build more digital experiences to complement their hardware. Though the machine functioned seamlessly, there was no easy way to port data results to other applications. This inhibited initiating the fully digitalized workflow required for a smart lab experience.

In this case, APIs were imperative to opening up back end cloud services to enable smooth user interfaces and end-to-end workflow automation. “Intuitive user interfaces must integrate all services, including cloud and on-premises services, to create and automate workflows,” Gross explained. “To do this, you need integration.”

3. Ecosystem-Driven Economy

The network effect of platforms is that they enable an ecosystem to form. And, according to Gross, involving partners in this new digital experience matrix is imperative for success. For example, the API gateway is one area where partnerships help an integration strategy; “You need an API gateway for security and governance reasons,” he stated.

Throughout his experience overseeing APIs on many projects, Gross often noticed a naïveté associated with defining the ecosystem. “When [clients] engage in the first phase of these projects, they think they know how to do it, but they typically don’t,” he said. Potential API providers often don’t fully realize their monetization strategy, the security implications or the complementary software providers necessary to support a working model. “Partnerships often facilitate a value-add to customers — they enrich the total offering through APIs and ecosystems,” said Gross.

Similar to how a machinery company may embed a bill of materials into the product they sell, digital partnership ecosystems can open up data so partners can access and innovate with it, Gross said. Frequently, ecosystem partnerships make a lot of sense, as they can better meet consumer expectations. For example, Gross suggested that integrating a ticketing system into a conditional monitoring system would bring compelling value.

The Next Stage: Self-Service Integration With APIs

According to the report, 40% of companies said that digital transformation is driving their need for app integration. Truly connected enterprises must embrace digitalization and integration across all aspects of the business. As a result, this is forcing a business shift toward more open ecosystems.

But building these systems will require newfound knowledge dissemination around developer experience and self-service capabilities. “Self-service has become fundamentally important,” said Gross. It’s not enough to simply open interfaces — you have to also add self-service capabilities to integration tools, he added. This could mean offering low-code options alongside APIs — such drag-and-drop UIs would help facilitate integrations for more citizen developers. A self-service approach to digital platformification is an emerging trend, yet one that’s “not fully at mass market,” described Gross; it’s still in its early stages.

Open ecosystems are guided by consumers, who often desire connections between your tool and external partners. But, opening up data isn’t just helpful for partner integration; it could also benefit internal use. As Gross described, time-series industrial analytics could empower operators on the shop floor or production facility to make sense of local data. “You need self-service analytics tools to give them that ability,” Gross said.

Building new customer experiences to cater to various devices and platforms is a big driver for API adoption. As a result, headless styles are emerging to address multi-platform requirements. For these reasons and many more, APIs are fueling new digital transformations across enterprises, powering innovative customer experiences and hiding complexity in the back end. With APIs, smart processes, smart machines and smart partners can all come together.

May 13, 2021
Transforming Your Digital Transformation

Change is difficult, so most companies pull the bandage slowly, hoping to avoid the hard, painful part – especially with regard to digital transformation. But in the corporate world, cautious change inevitably leads to entropy. Progress gets made in one department at a time, at the expense of others. Leaders turn over, priorities shift, plans fall apart and the desired results never happen. The bandage never really comes off.

I see this happen a lot in companies that say they want to transform their digital customer experience – across all industries we work with. The board or the shareholders might not embrace a truly digital-first strategy or understand what the end-state transformation goal actually is. Instead, they end up digitizing the past, refreshening a longstanding brand with a new storefront in a doomed effort to maintain business-as-usual.

These companies start with a well-meaning internal innovation team. They preach agility, then spend months researching the problem and consulting internal stakeholders, all the while trying to stay close to their comfort zone of existing practices. They write reports, they create roadmaps, run design-thinking workshops and come up with a solution … and then throw it over the wall to IT and wash their hands of it. Nine months later, the team is busy executing the new plan, but, with no internal champion, it can’t innovate. Due to the chaos and complexity of the project, the company burns through its budget and the project becomes a sad statistic. In fact, 95% of corporate digital transformations fail outright or produce diluted results, according to one recent study.

Shrink the Transformation Timeline

If a company really does want to digitize for the future instead of the past, it needs to turn that approach on its head. It needs to drastically shrink the timeline for digital transformation, which means starting with a digital operating model and putting the end clearly in sight.

The result is a digital operating model that continuously delivers and measures value. It’s not a project. It’s not a product. It’s an operating model that puts teams close to the market and customer, and makes them responsible for finding and delivering innovative, high-value customer experiences.

Get the Team Right

This approach requires a team that knows how to embrace ambiguity and takes responsibility for creating the solution, not just designing it or building it – both of which fail when done in a silo.

It needs to be a small, multifunctional team with the authority to implement things quickly, with the fewest possible hoops to jump through along the way. And when the inevitable organizational friction arises, the team and its goal needs to be seen as a transformation opportunity, not a barrier to be avoided.

Companies assume they can do this work in-house, but it’s next to impossible to form the right internal teams because, typically, they don’t have enough experience with this model.

These internal teams don’t quite have the right training for the job, but more importantly, they don’t have the right permission and agency. Some are risk-averse or can’t break through organizational silos. Some simply aren’t given the agency to do the work. Organizations with a lot of experience evolving, that give their employees this agency as a matter of course, might have success in-house. But it’s a tough ask for older, established firms.

Don’t Design – Execute

To their credit, many companies see this and outsource their transformation leadership to a consultancy firm. But you can’t outsource a transformation. You can’t teach a transformation. You need to implement transformation.

Both internally and externally led transformations fail to grasp what really makes transformation work: agency and delivery.

Instead of researching, planning and announcing, the team needs to roll up their sleeves and start executing. They have to drive the evolution of the company’s software toward the identified goals, break down any organizational silos or challenges that get in the way and deliver – quickly. They have to work together with the IT team, and anyone else who needs to understand what they’re doing, but execution needs to be top of mind at all times.

The solution isn’t insourcing or outsourcing. It’s a joint venture, where the transformation is within the company’s core business unit, working together with a consultancy or partner to complete the digital transformation faster by focusing on a smaller slice of the business. With this foundation, an organization can be pulled through a rapid transformation in nine to 18 months, rather than three to five years.

In fact, in under six months, a tiny transformation team of five to seven people can scale up to a transformed organization of 120 people, quickly delivering the desired digital-first customer experience. All it takes is a team that has done it successfully, multiple times. And the best thing about this is that transformation is measurable by the ability of teams to continuously deliver and evolve experiences across multiple digital channels.

Digital moves too fast, and is too complicated, to be managed by traditional processes and approvals. If it does, whatever change your company sets out to enact is at risk of being dead on arrival. Agency plus delivery is the formula for a successful digital transformation.

February 3, 2021
Shifting to Product-Centric Work in Utilities
Large organizations across the services spectrum are transforming from project-centric operations to product-centric way of working. Customer centricity is driving this transformation, as product-centric organizations put customers at the center of everything they do. Such a transition is largely dependent on how information technology solutions are deployed in the said organization.

This article looks at the importance of a product-centric way of working for utilities organizations, particularly the power sector, which is looking to transform customer interactions by revolutionary use of new digital technologies and solutions such as smart metering and smart homes.

At the onset, power utility organizations should focus on shifting to a product-centric way of working in areas that show promise to deliver innovation and digital enterprise such as customer analytics.

Fig. 1: Current State of Play in Most Power Utilities

Fig. 1 outlines the current state of play at most power utility companies, where organizational silos and application silos lead to customer challenges in understanding the products and services offered, as well as productivity losses and an increase in reaction times to changes demanded by business and regulation.

In most power utilities, silos exist in business units which are reflected in how the applications supporting those business units are organized and managed. This leads to duplication of effort, work and applications, as well as a waste of time and resources. Customers are often confused about multitudes of service offerings and various channels. There is also an inherent delay in responding to challenges thrown by changes to regulation and/or business environment.

This is changing, though, and one can look at the “meter to cash” processes for a reflection of market realities and customer empowerment.

In our experience, there are four key drivers of a move toward product-centric model:
- Digital Core – to evolve, innovate as well as leverage cloud, DevOps and agility to support the business.
  - DevOps practices and agility from ideation to sunset.
  - Encourage innovation.
  - Digital ready systems.
  - Focus on Product value.
  - Lean planning and maintenance.
- Intelligent Enterprise – to optimize the cost and delivery of services and encourage innovation.
  - Automation to support business agility of the power utility.
  - Autonomous operations to support power distribution and customer management.
  - Decisions based on insights drawn from customer and market data.
  - Focus on the innovation of products, services offered and customer engagement.
- Experience Quality focused on improving customer experience.
  - Product centric service delivery.
  - Business agility.
  - DevOps practices.
  - Experience centricity.
  - Product and experience-focused metrics.
  - Command center that is aligned with the business.
- Service Management and integration for scalability and unification of service delivery in the power utility while retaining a multi-supplier ecosystem as needed.
  - Continuous improvements.
  - Standardized deployment and integration management.
  - Collaboration in a multi-supplier scenario.
  - Service lifecycle management.
  - Information technology service delivery performance management.
This transformation to a product-centric organization ensures that processes, people, workflows and decisions power the power utility’s ability to:
- Customize services and offers.
- Improved and faster response to customer requests.
- Consistent and distinguished cross-channel experience for customers.
- Boost productivity.
- Eliminate waste.
Shifting to a Product-Centric Model

The product-centric model of delivery uses Agile, DevOps and Lean principles for strategic planning to ensure uncertainties and lack of information do not derail the delivery of services to end customers. A product-centric model places importance on relatively shorter horizons of budget and effort planning over massive planning at the beginning of a financial year. This is important, as a power utility is likely to be able to plan better for a quarter at a time rather than a complete year, particularly in the current economic climate. This not only ties well with the goal of business agility but also ensures improved planning and budgeting, as there is more information available about business goals a quarter at a time. The new teams organized around business capabilities, as shown in Fig. 2, then plan the product backlog, execute, test and deliver business value
to business and customers continually.

Fig. 2: Shifting from technology to business-aligned value streams or product-centric organization

Power utilities also need to change and improve their technology-centric solutions to help with forecasting and data analytics. The product-centric organization helps with this goal by identifying gaps for closure and aiding the creation of self-organizing teams that then take on the goals of the organization to address all the identified gaps, including in areas of forecasting and analytics.

Fig. 3: Organization design – a product-centric organization

Fig. 3 shows a sample organization design for the product-centric model. The figure also shows the breakdown of the structure from business function to value steams to products or product groups and, finally, applications delivering value—all the while ensuring that the goal of customer-centricity is at the center of every decision.

Governance and Metrics

A very important part of creating and adopting a product-centric model of functioning at a power utility includes focusing on the governance of the transformation process, as well as business results accrued from the transformation. The acceleration and adoption of Agile and DevOps practices on the technology side can be tracked through qualitative adoption measures. This leads to product level performance improvement, resulting in better products and faster delivery, with the product delivery mindset focusing on customer-centricity, leading to trends in:
- Faster time to market.
- Improved business satisfaction.
- Improved quality.
- Reduced information technology cost.
Other than this, following metrics and measures be focused upon:
- Adoption Measures.
  - Adoption maturity.
  - Competency/skill index.
  - Operational excellence.
- Product Team Level Measures – measured at team level per sprint.
  - Productivity measures such as team velocity and throughput.
  - Stakeholder satisfaction measures such as product owner demo satisfaction.
  - Quality measures such as percent automated unit test coverage and test effectiveness.
  - Business effectiveness measures such as business value delivered per feature and requirement readiness cycle time.
- Product Group Level Measures – measured at product family level per month or quarter.
  - Lead time to change.
  - Cost of requirement change.
  - Release frequency.
  - Cost of rework.
  - Mean time to recover.
  - Application stability.
- Portfolio Level Measures – measured at portfolio level per quarter or half-year.
  - Delivery satisfaction index.
  - Customer satisfaction index.
- Team Satisfaction Metrics.
  - Team happiness index.
- Coaching Effectiveness.
  - Coaching feedback.
- Team’s Self Organization Quotient.
  - Product ownership.
  - Sprint health.
  - Team health.
  - Technical health.
Potential Areas of Benefit for a Power Utility

There are at least four core areas in which a power utility can expect to experience quantifiable benefits by transforming to a product-centric model of operations. They are:
- Budget and Plan
  - Cost and time are the most valued commodities in a tightly run power utility.
  - A product-centric model ensures money, effort and time are allocated based on the validation of investment already made in an initiative.
  - Improvement in prediction of timelines, effort and benefits of an initiative because of cadence and timeboxing inherent to the product-centric model.
- Managing the Capacity
  - The key focus is on alignment with business and continuous delivery of business value.
  - The cost of delay and the cost of waiting are also reduced.
  - Focus on value delivery with quantified business benefits.
- Governance of Programs
  - The governance in product-centric organizations is about the exercise of control on the quantification of benefits.
  - The focus in a product-centric organization is on “building the right things the right way.” Rationalization of cost, elimination of waste and focus on business value are direct by-products.
- Managing the Demand
  - Continuous visualization and management of demand is an area where benefits are accrued as needs and ideas flow into the strategy filter continually from several sources.
  - The product-centric model allows the continuous elaboration of light use cases to ensure value is correctly calculated and assigned to each use case.
  - The program, portfolio and product backlogs are continuously evaluated to ensure that there is a cost-benefit sense to each item.
Conclusion

Some of the benefits of a product-centric model usage at power utilities are stated below:
- Customized electricity plans for efficiency, cost or comfortable consumption.
- Improvement in reliability.
- Creation of environmentally sustainable renewable programs of power for the more aware customers.
- Incrementally move toward a “business as usual (BAU)” relationship with regulatory changes.
A product-centric model at power utilities can also help bridge the data divide to improve data and analytics usage and enable creation programs in the following areas:
- Services and products that the customers are most probable to use.
- Optimized collection and prediction mechanisms to create plans to encourage timely payments.
- Create pre-paid services.
- Plans for direct control of load which allowed the utility to reduce air conditioning kind of machinery during peak usage and in return recompense customers.
- Improve pattern recognition for delinquency and fraud management.
- Cross-selling opportunities.
- Targeted sales and marketing campaigns.
This article was co-authored by Anurag Choudhry, Enterprise Architect, Manufacturing & Utilities BG at Tata Consultancy Services.

— Anshu Premchand
August 3, 2020