How a Slack App MVP is Informing Product Roadmap Decisions

Helping a Top 4 Professional Services Firm with MVP Slack App Design and Development

Have an idea for a new or improved offering? That’s a great place to be! But whether you want to build a new app, an AI-powered chatbot, or reimagined digital experience, there’s still a long road ahead and a lot of questions to ask. How do you know if that idea will work? How will you test it? When will you seek feedback? And how will you bring everyone else on board? Robots & Pencils supports clients at every stage of product design and development, including advising you on what ideas to test and how. Then, we help you get those ideas out into the world as minimum viable products (MVPs). By doing so, you can gather early feedback that will guide your future direction. Below, we share how we helped a major professional services firm test their idea with a Slack app MVP.

Recognizing the Power of Slack

One of the best things about Slack is its ability to bring together people, systems, and processes all in one place. If your organization uses Slack but doesn’t integrate other technology and workflows into the platform, you’re missing out on opportunities. Being able to interact with your systems right from Slack to get the information you need is a huge win. It benefits the employee experience and the entire organization by making work faster and more efficient.

Knowing the potential and promise of Slack, a top 4 professional services firm approached us with an idea. They wanted to give users of their Salesforce-based supplier lifecycle management solution access to the tool’s features inside Slack. This access, they hypothesized, would allow users to work more efficiently and effectively. Now, they wanted to build a Slack app MVP so that they could test the theory and demonstrate the benefits of integrating the two systems.

Creating a MVP Slack App to Test with Potential Customers

An experienced Slack services provider and longtime Slack partner, Robots & Pencils was well equipped to help our client. We provided expertise for the product strategy, UX/UI design, documentation, and development for the proof of concept Slack app. For this app, the team honed in on two important employee use cases: onboarding suppliers and collaborating on tracking issues.

In the resulting Slack MVP app, users can easily access and share new supplier details and onboarding statuses from Salesforce in Slack. Depending on their needs, users can share supplier info in channels or conversations. For issue tracking, our developers set up the integration so that new incidents added in Salesforce automatically post in Slack. As issues arise, users can discuss and collaborate on problems in real time. After an issue posts in the incident channel, users can also share it to other channels and conversations. Additionally, the Slack posts contain links that users can click on to see more details about the supplier or incident in Salesforce.

Robots & Pencils also assisted in configuring Slack and Salesforce to automate the app deployment process to the client’s internal AWS environment. Now, the client is demoing the MVP to customers and potential stakeholders to gauge interest in the app and its features. Already, the process has provided valuable insights for improving their product and refining their roadmap.

How to Get Started on Your Product Idea

If you’re ready to take the next steps on your product idea, Robots & Pencils is here to help. Early on, we’ll leverage stakeholder and user interviews combined with quantitative studies to uncover unmet needs and opportunities to innovate. In design and product vision workshops, we’ll align your team on goals, plans, and priorities. When you’re ready, we’ll partner with you to conduct technology and creative experiments to test the feasibility of your ideas and how they resonate with users. Of course, we also assist with agile product development, from designing and building products to measuring performance and learning in ways that power continual improvement and growth. Rounding it out, we deliver change management strategies and services that maximize business impact.

Want more information? Contact today!

Training Artificial Intelligence with Real Heart: Legitimize, Confirm, Reinforce

Insights for training AI chatbots

Written by DJ Moody, Client Strategy Analyst at Robots & Pencils

“Alright listen, Sparky…”

My father tends to be laid-back. However, there are clear indicators when he’s getting frustrated. These are so predictable that the whole family knows when a customer experience goes awry. First, he refers to the person as “Buddy”. If the situation doesn’t improve, they become “Sport”. With each step down this path of names, the chances the agent will keep the business drop precipitously. The final moniker is “Sparky”. No one comes back from Sparky.

It’s a familiar experience. A customer service discussion goes poorly. We get frustrated. If it’s bad enough, we decide to spend our money elsewhere. After those conversations, our opinion of the company changes. We blame the business. The same isn’t true with static content. If we can’t find the answer in an instruction manual, we get a little annoyed, but our view of the company rarely shifts. Yet when we talk with a person who doesn’t have the answer, frustration bleeds over into our impression of the company in a much different way. A human failing tells us the company failed. The company doesn’t care. The company is bad.

More rare, but more powerful, is the successful customer service conversation. The one where you feel heard, where the other person takes time to understand your need and works to get it addressed. Even if you don’t get the answer you want, you gain a positive perspective on the company. The experience tells us the company is good; they put resources into their customers. They care about us. Reading helpful documentation doesn’t offer that same gut-level reaction.

It takes a person for something to feel personal. 

Chat-based AI attempts to mimic a conversation with a person. This brings with it many of the benefits of having a human involved. It is an opportunity to show the customer you care and to develop a personal connection. This also opens up a lot of the dangers. It takes a person for something to feel personal, and we are creating a digital facsimile of a person. So the question becomes, how do we make our fake person seem genuinely caring?

Artificial intelligence, real heart

Experiences can be designed, whether on a website, in an app, or with a healthcare provider, sales professional, or customer service agent. The major difference between a digital product experience and a human experience is flexibility. The former we expect to be relatively static. It’s primarily up to us to find the right page or tool. The latter we expect to change based on our actions. If we’re angry we expect a person to show empathy and change their approach. We don’t expect an app to understand us; we do expect that of a person.

As with all programming, what you get from a chat experience depends on what you put into it. We tend to focus on training AI chatbots with the right data. We want them to have the correct answer to any question they might be asked. That might be enough if users interacted with them as they do a static resource. However, we want the benefits of AI accuracy and efficiency with the personal connection of human interaction. Just as the best human communicators have training in both information and interpersonal skills, we need to include the same when training AI.

3 takeaways for training AI chatbots from the intersection of science and the humanities

1. Legitimize the need.

We want customers to know we care. Just like compassionate humans, our chatbots can show this care by simply acknowledging there is a need and a desire to help. We don’t have to promise we can solve the problem, just make it clear we know there is one. If sentiment analysis is available, adding that detail is even better.

Standard – All businessBetter – legitimize the needBest – legitimize with sentiment analysis
What solution do you want?I understand that this is a problem for you and would like to help.I can see that you are frustrated and would like to help.

2. Confirm and clarify.

Great human communicators reflect back to the customer what they understand about a request and ask questions to clarify. Communication is messy and questions clean it up. Our bots need to do the same.

Standard – problem statementBetter – clarifying questionBest – confirm and clarify
I don’t understand.Can you clarify your question for me?I understand you want information about your widget. Can you tell me more about what you are trying to do?

3. Set and reinforce next steps.

One of the more frustrating parts of customer service, for both the consumer and agent, is when a solution is offered but missed steps cause it to fail. We can reduce this likelihood by summarizing the discussion, including all steps, before signing off.

Standard – problem statementBetter – restate the solutionBest – reinforce and confirm understanding
Thank you for your question.Thank you for your question. Remember, your next steps are to turn off the router, wait at least 10 seconds, and turn it back on again.I appreciate your inquiry. To recap, your next steps are to turn off the router, wait at least 10 seconds, and turn it back on again. This will reset the system and help you get back online.
Do you have any questions about those steps, or is there anything else I can help you with today?

Developing and training AI solutions for your customers

These are just a few of the many ways your AI solutions can reflect the care and compassion you have for your customers. In order to fully accomplish our goal of more human interactions between AI and customers, each solution must be carefully considered from all sides. Poor communication can make even the most well-informed agent–human or bot–seem cold and uncaring. Conversely, bad data means even the best-behaved agents will be useless. For truly effective agents, those who can increase both customer knowledge and sentiment, we need to live at the intersection of science and humanity. 

Every team developing a chatbot should include specialists in data science and AI as well as experts in communication, user experience, and customer care. In the case of Robots & Pencils, our Robots handle the code, our Pencils ensure an excellent experience, and our Ampersands bring it all together. To learn more about how Robots & Pencils helps organizations approach AI technology with a human-first approach, check out our AI & data science page or drop us a line at

How to Win Big with Your Customer Experience

It’s all about the customer journey!

In a world where customers are demanding value for every penny and the economy is challenging to say the least (recession? best job market ever? both?!), your edge isn’t just in top-notch products or services. It’s in unforgettable experiences that turn heads and open wallets. Remember this: In today’s fierce market, leading with customer experience isn’t just a good strategy; it’s the golden rule.

Schools, stores, banks, name any type of business — targeted, personalized experiences are central to the success of every online, in-person, or hybrid offering. And personalization can’t happen without truly knowing your customers and users. You have to start with understanding their journeys. Examine everything from their vital tasks, preferences, and pain points to their moments of happiness and delight. Effective personalization and engagement is impossible if you don’t know what your customers are doing or how to meet their needs as they move throughout each day.

To increase engagement, start with…

Providing a holistic journey-driven customer experience

As you look to differentiate your brand, widen your view to consider the whole user journey associated with your offering. You may find overlooked opportunities early or late in the life cycle. At these touchpoints, you may be able to do more to build ongoing (perhaps even lifelong) engagement and advocacy.

To create a stand-out customer experience, some organizations are integrating with other services, offerings, and products — even those from outside organizations. For example, I appreciate that my favorite hotel chain has updated their app so that in addition to accessing hotel services, I can use their app to find nearby restaurants, book a reservation, and schedule an Uber pick-up to get them there. Is it that hard to copy and paste into the Uber app? Of course not. But, when on the go, these little conveniences inspire disproportionate gratitude and brand loyalty. Financial transactions are another place I see companies use this tactic, offering products that enable easy options like buy now, pay later at the point of purchase.

As you work to create holistic, frictionless user journeys, team and departmental silos inside of organizations often slow change makers like you down. Beyond trying to break down those barriers, you can also look to build (or buy) a digital experience layer that wraps around organizational silos and their disparate systems, such as providing single sign on and a consistent but personalized customer experience.

Adapting to new customer preferences

Everywhere I look, customer preferences and expectations are evolving. Chief among these changes is that customers expect products and services to be accessible whenever and wherever they want them. This goes beyond simple mobile and digital offerings. “Buy online, pick up in store” has become table stakes. Now, the point of purchase / point of sale is moving towards the customer’s house, whether through virtual consultations and support, Uber eats delivery, or in-home health care concierge services.

I’m also seeing growing demand from consumers to manage their own relationships with businesses and schools. In many ways, increasing self-service can be a win for all. Customers get what they want, and organizations can cut IVR/customer support costs and free up staff to focus on higher-level problems.

Personalizing products and services

As mentioned earlier, one-size-fits-all products and services no longer cut it in education, retail, healthcare, or anywhere. Customers seek unique products and personalized offerings. Of course, you’ll need to balance new feature development with cost. The choices you make here must be driven by the customer. Increasing personalization usually also requires selecting and investing in new (often automated and/or intelligent) technologies and configuration tools. This in turn requires developing and launching new policies. To ensure they’re maximizing and accelerating ROI, many organizations are looking to outside technology consultants and change management experts like my team at Robots & Pencils for guidance on these strategic decisions.

Strengthening relationships through content & communication

Outstanding content and timely communications are another way to build brand loyalty, engagement, and community. The first step in creating this content is understanding what info users need. You also want to get clear on when and how to present it during their journey to catch their attention. The final part is figuring out how to deliver this content at scale while maintaining personalization and localization. Automation and data and system integration will be a key focus of any project in this space. This data capture also helps to enable the adoption of new AI solutions that are creating huge impact throughout the organizations embracing them.

Want to talk more about the customer experience? Join us as we explore all of today’s top business and tech trends!

Request an invite to an upcoming Digital Trends Executive Roundtable, where innovators and industry leaders will join together to discuss their biggest priorities and challenges!

—PS: You may have noticed that this blog echoes my recent post about employee experience and efficiency. That’s intentional! I see massive overlap in consumers and employees looking for easy-to-use tech that meets their needs exactly when and where they arise. The companies that will excel most are the ones that care about both the employee AND customer experience.

This CEO report was written by Tracey Zimmerman, President & CEO of Robots & Pencils.

Employee Efficiency Accelerators

The Power of Empathy, Automation, and AI

In boardrooms, exec touch bases, and nearly every client call I’m on, everyone’s thinking about how to supercharge employee efficiency and reduce costs. Organizations are on the hunt for tools and processes that let them accomplish more without pushing employees to the brink or blowing their budgets. Every good solution I’ve seen has started with an empathetic view of the employee experience. Which tasks are unnecessarily hard? What bottlenecks slow people down? What can you automate and streamline to help your team? Where can AI scale human potential and cut spend? The answers to these questions will point the way to powerful savings and efficiency opportunities.

(This is blog 3 in a series on key priorities for business and tech leaders. In my last blog, I talked about digital modernization, including integrating data and systems–which everything I’m about to discuss will 100% require!)

Reimagining experiences around employee needs

Outdated tools and processes that were built largely around organizational silos are hurting productivity. But it’s not as simple as replacing old tools with new ones. First, you have to understand what your employees actually need!

This requires looking at how different types of team members spend their days. What are their most important tasks and how are they getting those things done? Sometimes, you’ll find a need as simple as additional training or upskilling. In other cases, you might find opportunities to improve communications, tweak processes, or introduce new tools. One need I see frequently (with our clients and as a consumer) is more flexible, user-friendly tools for employees in the field. Your workers should be able to access and share information and complete critical tasks wherever they are. Whether on a remote job site, at a retail counter, meeting with a potential customer, or simply working from home, everyday duties shouldn’t require extraordinary effort!

On the flip side, better understanding how your employees work can reveal where you’re wasting time and money on tools your employees don’t actually benefit from. Frequently we find two (or more!) systems where only one is needed. Eliminating and consolidating systems can be an easy way to directly improve your bottom line.

Once you address and focus on your team’s real needs, you’ll quickly see cost savings and employee efficiency rise. Gains in engagement, productivity, and retention will follow. Ultimately, you’ll be helping your employees to ensure better customer and student experiences, providing a win all around.

Empowering employee efficiency with self-service tools

After so much frustrating supply chain disruption and constantly fluctuating prices, consumers are paying super close attention to product and service reliability and pricing. This means we as leaders must focus attention on internal predictability and employee efficiency. Yet, I still come across employees unable to complete routine activities without assistance or permission from management, IT, or other overburdened departments. These employees require increased self-service features. While a real need for oversight or access limitations can exist, unnecessary permission bottlenecks have to go. From employee-led shift swapping to going beyond dashboards and reports to insights and suggestions, your employees need easy-to-use technology that allows them to take ownership of their work and operate without constant disruption.

Automating processes to free up teams for higher level work

In many organizations, highly manual (and painful!) workflows have led to incoherent data and inconsistent results. These problems requires an intentional shift towards repeatable processes with automation at the forefront. When you free employees from these time-intensive tasks, they can refocus on higher value work that benefits your business and customers.

Automation can also reduce acquisition costs and increase the long-term value of each connection. Education specifically has a large need to increase marketing efficiencies and automate communications across the student journey. Rather than relying on overloaded staff (particularly for straightforward messages and reminders), institutions can use automation to deliver the right information to the right learners at the right time in their journey. But watch out! Carefully designed, these automated flows can be delightful. When done poorly, it can cost you the trust of your customer, which is never cheap to rebuild.

Initiating AI-human partnerships

New AI tools are launching at a whirlwind pace, and I’m so excited to see businesses putting them to use! AI-human partnerships promise to accelerate product development, helping with everything from sorting user feedback, to writing Jira tickets, to coding with GitHub’s copilot.

Scaling support services and monitoring customer sentiment is another huge opportunity for using AI to increase employee efficiency. By strategically moving customers from FAQs to an AI chatbot to human support, organizations can scale support services while managing quality and cost as well as directing employee focus to advanced problems.

As for education, there’s ample potential for AI to accelerate staff processes and workflows in areas like:

  • Creating personalized custom experiences (1:1 content) for students
  • Reducing the costs of course design via AI authoring & modules
  • Accelerating presentation creation
  • Delivering student support services with less labor
  • Doing predictive modeling of student outcomes

In every industry, leaders need to think creatively and seriously about AI to stay ahead of the curve. As an internal team or with the support of outside experts, you need to start identifying use cases, setting up governance plans, and working with security and architecture departments to implement intelligent solutions that support teams across the business.

Want to share your thoughts on topics like employee efficiency, AI, and self-service?

Learn more about today’s business and tech trends — and join the discussion at an executive digital roundtable!

This CEO Report was written by Tracey Zimmerman, President & CEO of Robots & Pencils.

How to Drive Innovation With User-Centered Design and Agile Development

Perhaps this story is familiar to you…

Your team has been tasked with designing and building a groundbreaking software product that focuses on putting the end user — the person who will use the product — at the center of the design and development process. The stakeholders want it delivered within 12 months.

Six months into the project, the hunger for innovative, user-centered features seems to wane.

The delivery team adopts a rapid agile cadence that values predictable delivery dates and velocity rather than experimentation to find the best solution for the user.

The design team attempts to get ahead of development in order to ensure user insights lead the build of new features, but priorities shift after each deployment, and much of that work gets thrown away.

Over time, a chasm forms between user-centered advocates and delivery — their ideas are just too risky and unpredictable for the mission: get the next release out the door.

An all too familiar tale, but with an ending we can change. I think there is a way to get the most out of the user-centered design and Agile processes while keeping to budgets, timelines, and a consistent delivery cycles.

First, though, why is this tale all too familiar?

A bias towards reliability and predictability

We’re naturally inclined to have a bias towards reliability, predictability and reducing risk. And Agile development does this by design.

The sprint-based nature of Agile development makes its output extremely predictable — yielding releases every couple of weeks. But it works best when requirements are understood upfront and can be accurately estimated.

New features and unfamiliar technical challenges are often overestimated to account for the delivery uncertainty, and this results in the most predictable features being prioritized over the most innovative ones.

In contrast, user-centered design focuses on the people who will use the software, and how they can easily and efficiently achieve their goals. It leverages primary research — actually getting insights and feedback from future users — to discover previously unknown friction points in the user experience. It seeds the invention of new experiences that offer that far better way.

While some of the ideas that come from this process can offer a 10x improvement in the experience, they are also unproven and often unfettered by technical and business process constraints. The discovery-driven nature of the process makes the output impossible to predict.

An incompatible match

The issue is that user-centered design and Agile development are incompatible.

  • User-centered design aims for maximal astonishment — let’s see if our users can tell us something we didn’t know.
  • Agile aims for minimal astonishment — let’s have as few surprises in our development process as possible.

To steal a concept from physics, user-centered design prioritizes voltage — a measure of potential energy, while Agile development prioritizes amperage — a measure of the flow of current.

And in the same way that you wouldn’t want to plug your TV into a high-voltage power line, the friction between Agile and user-centered design comes when you directly connect the two methodologies.

While the results might be less spectacular than an exploding TV, the failures are just as predictable:

  • Innovative ideas lag development timelines and create project delays.
  • Innovative ideas get chopped in favor of timelines.
  • Through long hours, a talented team squeezes in a couple of extra features deemed “top priority.”

In all three cases, the drive for innovation eventually wanes:

  • Unmet delivery promises undermine organizational and investor trust in the team’s ability.
  • Continuous cutting of new ideas demoralizes the team into a “good enough” mentality and opens up questions about the ROI of exploring innovative ideas to begin with.
  • Unsustainable hours create organizational churn and the talent carrying the greatest load walk out the door.

Still in order to successfully invent new user-centered solutions AND deliver them, we need the strength of both. We need a way to convert the high potential energy output of user-centered design into the high current that the Agile process demands.

Treat user-centered design as investigation, not validation

User-centered design is a process that requires a lack of preconceptions and an open mind. The goal is to understand the root causes of user behavior in order to formulate a new, better approach. Keeping a hypothetical solution in mind through the process creates a cycle that reinforces our original assumptions and often blinds us to other opportunities.

So, when a request comes in to “redesign an app,” start by abstracting that request into the underlying goals that the user accomplishes while using the app. Then, use primary research to validate that those goals are real and dig into how they are accomplished today. You may learn that users don’t care about what you think they do. You might also learn that an app isn’t even the right enabler for their goal.

At the end of this process, you will get a list of things to build that will improve the user’s experience… they just might not be the ones you expected.

Only feed de-risked features into the Agile process

In order to keep the Agile delivery process moving efficiently, ensure that any proposed features/stories are well understood both in terms of their requirements as well as their technical complexity.

Before ever estimating a feature, you should know:

  1. That implementing the feature will generally increase user perception of the experience
  2. The way to solve any key technical or data hurdles
  3. Confidently, how long the feature will take to build

If a feature doesn’t meet all of those criteria, then it could easily derail the predictability that is the key benefit of Agile development.

De-risking features enables teams to estimate without fear because the basic how of implementation is already well understood.

Use experimentation to connect user-centered design and Agile

The un-vetted output of user-centered design makes it a poor input into an Agile process that works best with low risk requirements. To bridge the two, we need an intermediary process that takes fledgling ideas and systematically de-risks, prioritizes and roadmaps them at a program level.

This middle phase — experimentation — acts as the glue.

Prototype, test and rapidly iterate on proof of concepts (POCs) with users to ensure that your features will have the desired impact on the user experience. These experiments provide a view into the potential ROI and, by providing a clearer picture into the new experience, can generate investment interest at the executive level.

Similarly, technology experiments (often referred to as technical design spikes) can be used to de-risk complex technical and data problems. In this phase, the priority is not delivering a minimum viable product, but taking the riskiest assumption and exploring the solution space.

At the end of experimentation, these pre-vetted features can be fully story-mapped and prioritized for delivery — the perfect input to the Agile delivery phase.

Run all three phases concurrently as an innovation program

While the experimentation phase ensures compatibility between user-centered design and Agile, it is important to note that these methods run at different speeds.

  • User-centered design takes a long time to conduct, but yields a high volume of opportunities.
  • Experimentation can be done quickly but the output may or may not produce viable results.
  • Agile generates small chunks of production-ready functionality at a regular pace.

To keep all processes operating at full speed, allow each of these phases to run independently and concurrently over time. Each phase generates a queue of work for the next — user-entered design creates a queue of experiments and experimentation creates a queue of user-vetted, de-risked features for implementation.

With a never-ending list of to-dos in all three work streams, the program will operate at full efficiency. And innovative, user-centered features will flow like clockwork into your products and experiences.

Tyler Klein is the Executive Experience Director at Robots and Pencils. Physics major turned HCI specialist, he uses what’s new to build what’s next and offers far better ways to interact with the world around us. Special thanks to Chris Chew, Jamie Reid, Mike Greening, Reid Sheppard and Aaron Slepecky for their contributions.

From Chaos to Clarity: The Journey to Modernization

“Barely controlled chaos in a highly complex environment with fragmented innovation solutions”–that’s how one of our clients recently described their organization. I hear versions of this all the time, so if that’s how you feel, trust me–you’re not the only one!

We’re in a time when adaptability and speed are make-or-break, but fragile infrastructure and fragmented data, tools, and processes keep tripping up plans. I see it over and over. It’s why digital modernization is so important. Organizations need a stronger foundation that makes it easier to extract insights that can really make a difference to business results, to adopt new tech, and to deliver products and services at scale. But building that foundation won’t be a quick or straightforward fix. I’m talking about consolidating your current tech stack, plus introducing new implementations, integrations, and system improvements. It’s a lot! To succeed, 3 areas in particular are going to demand your attention and planning–unlocking data, improving (or replacing!) aging infrastructure, and increasing interconnectivity.

(BTW: This is blog 2 of 5 in a series on key priorities for business and tech leaders. My prior blog intros these priorities and other influential marketplace trends.)

Unlocking hidden insights by unifying fragmented data

Most companies struggle with disconnected data and insights spread across systems and departments. When we come into an organization, we routinely find departments trying to solve problems on their own with off-the-the shelf systems (including Excel). While everyone has good intentions, what happens is that they create tech and data silos across the organization. Eventually, a dozen disconnected applications are capturing (but not sharing!!) similar data. The other challenge many of our clients face is the sheer volume and complexity of data collected for personalizing customer or student experiences. Data winds up scattered across different teams, files, websites, and systems, stored in ways that are too painful to query or analyze. Yet all this powerful data is just waiting to be unleashed!

As the purse strings tighten, leaders can’t afford to leave those insights untapped or to support disparate systems. And we definitely shouldn’t be missing out on sharing valuable data across teams, where combined with the power of human creativity, new ideas can emerge; aggregating data so that it is easily accessible is a must! Organizations need to integrate and scale solutions that work, and ditch the rest. So often I see people throwing good money after a bad solution that’s not working for their business. If you don’t have the expertise in house, find a partner who can help centralize your data and transform this goldmine of information into actionable insights.

Increasing flexibility by addressing aging infrastructure

Tech debt and aging patchwork infrastructure are a real roadblock to innovation and growth. Perhaps the problems resulted from a merger or acquisition, siloed planning, or moving fast while addressing pressing issues (like responding to shifting customer behaviors in a pandemic for example!). Whatever the cause, aging and disjointed systems are holding companies back. It’s time to address that tech debt and say goodbye to archaic systems in favor of more resilient, flexible infrastructure. But know that lack of clarity around ownership and questions around the impact of system deprecation is almost certain to cause problems. To minimize issues, start by gathering and documenting this info, and be sure to always have a super detailed and thorough change management plan!

(A tip from our robots: API layers can help you transition aging tech stacks. Rather than fully reengineering a tech stack from scratch, you can leverage APIs as an intermediary to create consistent access and replace the systems behind the scenes piece by piece, allowing your organization to deal with the change in more manageable chunks.)

Preparing for the future by increasing interconnectivity

One huge positive is that everyone now sees the power of connected data, systems, and “things”. Companies recognize that data surrounds everything, and that data models should be planned intentionally from the start of a project. They’re asking the right questions, like: How will we use integration to connect this data to that data? Can we use sensors to track movement of physical items? How will we ensure data integrity across systems? How do we extract those juicy insights to become a more data-led organization? I’m so glad to see leaders doing this planning up front!

In some cases, I see interconnectivity extending even further as companies expose APIs to products and experiences outside their organizations. For users, this opens the door for highly curated end-to-end experiences that cut across multiple tasks and organizations. Of course, creating these experiences is not without challenges, including dealing with data and API inconsistencies. Using AI to translate data between different formats could be a game-changer, benefiting both companies and users alike, so keep an eye on advancements in this area!

Learn more about today’s business and tech trends — and join the discussion at an executive digital roundtable!

Next up, I’ll explore how automation and journey-centered experiences can help with cost reduction and efficiency. Later in the series, I’ll talk about trends in personalization and engagement, plus discuss when it makes sense to seek outside expertise and guidance on your initiatives.

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This CEO Report was written by Tracey Zimmerman, President & CEO of Robots & Pencils.

CEO Report: Maximizing Impact and Future-Proofing Your Business in an Ever-Changing World

By Tracey Zimmerman, President & CEO, Robots & Pencils

As CEO at Robots & Pencils, I have the amazing privilege of supporting leaders on everything from bringing game-changing new ideas to market to optimizing products and services that have been at the heart of companies for decades. Over the last few years, together, we’ve navigated everything from lockdown, to an influx of customer spending and “growth at any cost” strategies, to preserving cash as we brace for a looming recession. In financial services, education, travel, healthcare and so much more, my team and I have helped to shape tech and business strategy for everyone from fledgling startups to F500 companies amidst a sea of constant change. With no end in sight–and even more acceleration of technology and societal shifts on the horizon, I wanted to highlight what’s influencing decisions today–and call attention to 4 strategic areas with the biggest opportunity for organizational impact.

The State of the Marketplace and Technology

Let’s start with what I’m seeing and hearing from friends and clients on the front lines.

  • Limited Funding: Money is increasingly hard to access. With consumer spending down, interest rates up, and boards and investors focused on operating margin and profitability, every initiative needs a strong business case and clear ROI. Because guaranteeing growth through better and more customer engagement is extra challenging right now, securing funding for those projects has become trickier. Internal efficiency gains are easier to justify investment due to perceived greater ability to control the levers that are needed for impact.
  • Rapid Change: With the daunting speed of change, companies are struggling to select future proof strategies and technology. Further, many companies rapidly selected dozens or more tools during the pandemic to keep business going–and now aren’t sure how to rationalize what to keep, what to cut, or where to reassess the solution space.
  • Increasing Need for Flexibility: To provide a runway for business to innovate, iterative approaches are needed that flexibly adapt to change. It’s easier to swap out a small thing than a big one–and only make big changes after something is proven to work. Whether its technical architectures, business processes, key partnerships, workforce and talent management (think the gig economy), and even stackable education credentials that may add up to a degree, or not, the desire for flexibility is pervasive.
  • AI Acceleration: AI is a rapidly emerging tech that has been in the periphery, but suddenly everyone has questions about it thanks first to the release of ChatGPT and now new tools launching literally on a daily basis. Wherever you look, both uncertainty and excitement about its potential are high. (We’ll get into this more in coming blogs!)

Top Business Priorities for Maximizing Outcomes & ROI

Given these trends, there are 4 areas that I think leaders need to focus on today and into the future to maximize ROI. I’ll intro them here, and, in the coming weeks, devote a full post to each one.

1. Digital Modernization

Companies have launched new tools left and right in recent years, but too often we see projects happening in isolation. Leaders need to take a step back to improve the underlying infrastructure and address fragmented data, tools, and processes. But it’s not easy! Getting everything in one place and systems working seamlessly won’t be a walk in the park, but the payoff is the ability to effectively extract business insights and keep pace with the latest tech advancements.

2. Cost Reduction & Efficiency

Good luck finding a leader not thinking about efficiency right now! Everyone’s looking to automate processes, decrease internal costs, and hit targets without over taxing our teams or budgets. A huge opportunity lies in designing employee tools based on a deep understanding of their experiences and on-the-job needs (and perhaps backed by AI-human partnerships!). These efforts will help you both boost productivity and shift focus to the highest value activities.

3. Personalization & Engagement

It’s all about the user! To meet customer expectations and boost loyalty, companies need more unified and personalized experiences across platforms and touchpoints. To succeed, these initiatives must stem from an understanding of the user and have clear ties to revenue and business outcomes. In a similar vein, schools need better, more connected tools to attract students, keep them engaged with personalized content throughout their educational journey, and turn them into lifelong learners and active alumni.

4. Expertise & Guidance

With so much moving at lightning speed, it’s tough to plan for the future while avoiding costly short-term mistakes. From keeping up with user trends to prioritizing tech investments to maximizing ROI on new products, maintaining the expertise to make all these high-value decisions and plans alone just isn’t feasible. Leaders who seek guidance and support at crucial moments will be better equipped to stay ahead of market change and disruption.

Stay tuned for a deeper dive into these strategic priorities — and join the discussion at an upcoming executive digital roundtable!

In my next blog post, I’ll explore how fellow leaders are approaching digital modernization–and the proven methods I’ve seen to navigate the roadblocks along the way. Later in the series, I’ll talk about internal cost reduction & efficiency strategies, approaches to product personalization & engagement, and where organizations are finding outside expertise and guidance most useful.

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The Burden of Ignored Tech Debt — and a Better Path Forward for POs

Technical debt 🏦 is often accumulated and ignored in software projects that are struggling with quality, timelines, and expectations. Instead, teams focus on fixing bugs, adding new features, and building quickly. However, technical debt is like a monster 👹 that the business knows exists but that it is afraid to talk about 🫣 or treats as an urban myth. Technical debt only becomes a priority when it becomes a blocker or costs more money. Until then, the business assumes that the team will simply learn to live with it.

The engineering team 🤹, in the meantime, works on a superficially stable 😵‍💫 product, patching up 🩹 and building new features 🏗️ on an already leaky product. The team may say they cannot build features X, Y, and Z due to technical debt and can only deliver X1 and Y1. Product Owners (POs), who feel the pressure or act for personal reasons, may find an alternative path to squeeze the set of features into the release, thinking they achieved the impossible 🥳. However, this is a 🧨 mistake as it ignores feedback from the team. Ignoring technical debt not only lowers a team’s morale and trust but also leads to an unhappy 😖 and less motivated team.

As POs, we prioritize the customer experience, but our responsibility extends beyond users 🧑 and the business to our engineering team 🤹 and other stakeholders. Once you put everyone in the frame, you will notice the rough edges and gaps. We must assess the gaps 🎢 in our process, discuss and create a plan 📝 to address the immediate and larger gaps, and set timelines to address others. The earlier we resolve these problems, the better.

I have come to realize by focusing on the collaborative product experience, including all primary stakeholders, and not just the customer experience, we can create a better outcome 📈 for all. We must set aside time on our roadmap 🌎 to review and address technical debt. Give time between releases for teams to recharge themselves 🏖️, reflect on their work, and come up with ways to improve the collaborative product experience 💡. It’s possible that tech debt is not the monster 👻 we always thought it was. Or, perhaps worse, we’ll find that by ignoring tech debt for so long that it was us who made it into a monster 👹. You will never know until you look.

If you want to know the type of monster you are dealing with, please continue reading. Here are some steps I suggest.

Begin by allowing the development team to conduct a technical audit to identify and compile a list of tech debt items. This process can be time-consuming, especially for teams that work on legacy infrastructure, products with stability concerns, or those that have not been actively managing tech debt. Product owners can help to focus the team’s efforts by providing specific goals for the next few releases or for the year ahead, allowing the development team to review connected pieces and identify potential blockers.

Once the team has identified tech debt items, work together to understand and categorize their business impact, development impact, and cost of fixing. Use a simple scale, such as small, medium, large, and extra large, to categorize the debt. Development impact refers to the effect of tech debt on the product from a technical point of view, the development team’s job satisfaction, and the team’s morale. You may also consider other factors relevant to your development team.

Map the tech debt items on a chart against business and development impact. The size of the circle should correspond to the cost of fixing. This will help you to prioritize which tech debt items to address first.

Prioritize addressing tech debt with high business and high development impact first. For example, this could be an app or site that not only frustrates users and leads to lost revenue, but also slows down the development team. Everyone should be motivated to eliminate small and medium-size circles within the current development cycle, but larger circles may require a conversation. Collaborate with the business and development teams to understand the impact of tech debt and determine if larger circles can be split into smaller ones. Resolve as much tech debt as possible while meeting release goals, and ensure everyone understands the cost of delaying or not fixing tech debt. Develop an action plan and timeline for revisiting remaining tech debt and make space for these items on the product roadmap.

Prioritize tech debt items with low development impact but high business impact based on their potential impact on the user experience or business goals. An outdated payment processing system is an example of such tech debt, which may not directly affect the development team but can cause users and the business to suffer. These tech debt items may surface in the future as feature requests, so it’s crucial to address them sooner when the impact is smaller rather than later. Categorize and prioritize these items based on their impact on the business and development, and create an action plan to address them.

Next, focus on the tech debt with high development impact but low business impact. While these items may not directly affect the business goals, they can have a significant impact on the development team’s ability to deliver quality products. Examples of such tech debt include code refactoring, code optimization, and writing unit tests. To prioritize these items, work with the development team to understand their impact and estimate the cost of fixing them. Then, identify a use case or scenario that demonstrates the value of addressing the tech debt, and present it to the business stakeholders. For example, you can show how refactoring a particular piece of code can improve performance and reduce the risk of defects in future releases. It’s important to approach these conversations with empathy and understanding and to help the business stakeholders see the long-term benefits of addressing the tech debt. By investing in the development team’s productivity and morale, you can help them deliver better products faster with higher quality and confidence.

Lastly, you have low development and low business impact tech debt to address. While these items may seem trivial, they can still add up and create technical debt. For example, the unused code or feature in the product clutters the codebase and might make it difficult to maintain over time. For this category, evaluate each item and consider its long-term impact on the product. For those that are strongly connected to the product roadmap and goals for the year, knock them off. For the remaining items, analyze and understand what happens if these tech debts are not fixed in a year. If the answer is little to no change in size and impact, then carry them over to the next year. But if ignoring the debt increases its impact, prioritize and create an action plan.

Remember, it’s important to regularly review and address tech debt as part of your product development process. This helps maintain the health and stability of your product and ensures that the development team can work efficiently and effectively. By prioritizing and addressing tech debt, you can create a culture of continuous improvement and quality, and ultimately deliver a better collaborative product experience. Ultimately, a positive and motivated team is essential for the success 🌟 of any project, and it is our responsibility as POs to ensure this. Do the right thing for your people and product.

This post was contributed by Rushi Pol, the Product Owner Craft Steward at Robots & Pencils.

3 Stages of Learning a New Technology

This article describes my strategy for learning new technologies, refined over the decade or so that I’ve been working in tech. As with any advice based on one developer’s experience, you may find that it’s obvious or that it doesn’t apply to you, but I hope it’s useful as a guide, a checklist, or even just a starting point for reflecting on your own learning process.

When I talk about learning a technology, I mean something pretty concrete. I would apply this approach to:

  • programming languages
  • data stores
  • libraries and frameworks
  • tools (git, Docker, Regex, etc.)
  • platforms (Linux, AWS Lambda, Google AppEngine etc.)

I wouldn’t apply it to:

  • methodologies (TDD, agile, effective writing, etc.)
  • high-level concepts (parsing, ML, IoT, serverless, etc.)
  • low-level details (virtual memory, garbage collection, etc.)

Here’s an overview of my strategy: when I’ve got a new technology to learn, I think about going through three broad phases:

  1. Consuming documentation
  2. A learning project
  3. Application

Phase 1: Consuming documentation

My first stop when approaching any new technology is documentation, especially intro docs or tutorials. I do love a technology that comes with good documentation, but this phase might also include courses, blog posts, or other third party material.

Beyond actually learning the technology, in this phase I’m looking for:

  • Points of comparison: Is this technology similar to something I already know?
  • Unique features: What are the ways this technology is different or surprising? Where might I apply it instead of something I already know?
  • Integration points: What kind of projects could I use this technology for? Will it let me leverage things I already know, or does it require me to discard my usual toolbox?

The objective is obviously not to learn everything there is to know, but to create connections to my existing knowledge so that I can start using the technology and find my way to answers in the future.

Some examples of great material for this phase:

Phase 2: A learning project

Once I’ve read the introductory documentation and got myself situated, I try a little project using the new technology. I aim for something small, but not trivial where I can safely apply the skills I’ve just (supposedly) learned but also something that will challenge me and expose any gaps in my understanding.

Note that this isn’t learning on the job or building tools to scratch your own itch (though those are important skills in their own right); it’s a project that’s conceived, planned, and executed with learning as a primary goal.

I try to find a project that:

  • Highlights the new technology: I won’t learn much about a new database if I’m struggling to get my front-end code just right. If I want to try out that auto-documentation feature, I should make something that I’d want to document.
  • Is just beyond what’s comfortable: Getting frustrated with advanced features isn’t productive, but neither is retreading material from the tutorial.
  • Doesn’t have too much instrumental value: If I set out to build something, I might overlook a new technology’s failings if I want the thing badly enough.
  • I can put some polish on: The point is to learn a technology well; it’s good to have some time to polish, review, or get feedback.
  • Above all, I want a project that’s small: A tight scope helps me keep focus and leaves me free to fail fast if the project isn’t working.

The objective is to discover all the things that the new technology’s documentation didn’t address:

  • How difficult is it to install/build/operate?
  • Can I integrate it with my existing tools (languages, editors, source control, packaging and deployment, etc.)?
  • Does it still feel elegant and useful when I’m using it on an original problem (and not a carefully chosen example)?
  • Did I actually learn it well enough to turn an idea into a reality?
  • Am I confident that I’m using this tool correctly? Idiomatically? Sustainably?

My experience has been that these kinds of questions aren’t always addressed very well in documentation or are addressed more with hype than with facts. If, after putting in a genuine effort, I can’t get a new technology to work for me, it’s an indication that the tech might be immature, my understanding might be flawed, or that it might not be a good fit for what I’m after.

Some examples of projects that I’ve done in this space:

I also find it helpful to write up a little experience report when I’m finished to capture and clarify my impressions of the new technology and to have something to share with others.

Phase 3: Application

Once I’ve done my learning project, I’ve hopefully got a good sense of where a new technology fits and whether or not I want to keep working with it. At this point, it stops being a target for deliberate learning. If I’m trying to further develop my expertise, I look for:

  • Opportunities to use it professionally: Perhaps I have a work project where the new tech is a good fit or is already a going concern.
  • Side projects: This can be bigger and more instrumental than a learning project while still being a safe place to experiment.
  • Complementary technologies: Sometimes it might be appropriate to start this process over with a related technology (e.g. learn Elixir then Phoenix, or Rust then WASM).

Naturally, I’m always looking for opportunities to go deep on a technology (heck, I’m still learning things about Python after nearly 10 years!) but I’ve found that further expertise comes much easier with study and experience than it does from studying alone.

This post was contributed by Nat Knight, one of Robots and Pencil’s principal developers.

5 Reasons Why Your Digital Transformation Strategy is Underperforming

Future-minded businesses are rapidly adopting digital transformation. Are you one of them?

It’s not enough to decide you want to digitally transform and start picking new technologies. You need a strategy and the support of your team members to gain the digital transformation results that you read about.

When functioning properly, digital transformation can bring about higher levels of employee satisfaction, customer engagement, business innovation, sales, workflow efficiency, and more!

Be mindful of not rushing your digital transformation process. It’s a big undertaking and involves a lot of time. So being prepared and realistic is the biggest piece of advice we can give you. However, even with time and a documented strategy — your digital transformation strategies may be underperforming. In fact, you should constantly be auditing your strategy to see how well it’s working. As you assess your results, consider the following 5 reasons why your strategy might not be as effective as possible and revamp it accordingly.

Lack Of Internal Participation

Many professionals think digital transformation means adopting new technologies, but that’s only part of it. Digital transformation also requires a formulated strategy and employee adoption of both the technology and strategy.

In fact, resistance from employees to digital transformation is the number one reason that these efforts fail. 70% of companies report that employee resistance accounts for the underperforming of their digital transformation strategies.

Not Utilizing the Right Technology Stack

No matter what your goal is with digital transformation, strategically using technology can help any business of any size to grow and transform. Regardless of your industry, you’ll quickly find that you can’t make headway digitally unless you use technologies like:

  • Cloud computing
  • Mobile apps
  • Automation tools
  • Data analytics

Another thing to note about digital transformation and technology is that you shouldn’t add a new tool just because it’s new and flashy. Be sure that it fits in with your overall strategy and that the money you invest in it will lead to revenue growth.

Choosing the Wrong Partners

Deciding on digital transformation is not enough. Afterall, 78% of brands who initiate digital transformation fail. That’s why you may want to consider an agency partner to build, guide and implement your strategy.

When choosing a digital transformation partner, check out their past work, ask for references, and take them up on a free consultation. Basically do your research so that you don’t become one of the 78% of brands who attempt digital transformation but fail.

Neglecting to Map Out Your Strategy

It’s easy to get ahead of yourself and dive into a new digital transformation strategy before you’ve really thought everything through. However, this type of work requires a strong foundation in order not to crumble later. So before you start purchasing technologies and training your employees, map out your entire strategy. This should include things like:

  • Do a business and user needs assessment
  • Research industry trends
  • Analyze what your competitors are doing
  • Define goals
  • Assess budget
  • Make a plan for getting employees onboard and trained

Digital transformation isn’t just about the future, it’s also rooted in the past. To succeed, it’s essential that you use data from your past initiatives to inform your future strategy.

Misunderstanding the Business Need or Opportunity

If you thought your digital transformation strategy would increase productivity but the needle hasn’t moved, maybe you’ve been focused on the wrong thing.

With the right digital transformation strategy, you should see an increase in productivity when it comes to customer communications, sales and internal communication.

If that’s not what you’re seeing, it might be time to revisit the thinking and plan behind your strategy. Doing more in-depth business and user research can help you to better understand the opportunity at hand or the real cause of the problem you want to solve. Before you roll out a digital transformation strategy across the company, it’s also imperative that you get feedback and test your ideas with the people who will be impacted.

Could your digital transformation strategy be stronger? Do you need help building out your digital roadmap or conducting user research? Contact us today for a free consultation!