Category Archives: Technology

Why Qualitative Data is the Soul of Innovation

Beyond the Dashboard

LAST UPDATED: November 16, 2025 at 09:36PM

Why Qualitative Data is the Soul of Innovation

GUEST POST from Chateau G Pato

In today’s business landscape, “data-driven” has become the mantra. We are awash in dashboards, metrics, KPIs, and algorithms, all designed to give us a clear, quantifiable picture of performance. And rightly so—quantitative data is essential for measuring results, optimizing processes, and identifying trends. But what if I told you that in our relentless pursuit of the “what,” we are often missing the much more powerful “why”?

The truth is, true innovation—the kind that creates new markets, delights customers in unexpected ways, and genuinely changes human behavior—rarely springs from a spreadsheet. It emerges from deep empathy, nuanced understanding, and the ability to connect seemingly disparate observations. This is the domain of qualitative data. It’s the soul of innovation, breathing life into the numbers and revealing the human stories behind the trends.

For human-centered change leaders, mastering the art of qualitative inquiry isn’t just a research technique; it’s a foundational leadership skill. It’s about listening more deeply, observing more keenly, and seeking the unspoken needs that dashboards simply cannot illuminate.

What is Qualitative Data?

Qualitative data describes qualities or characteristics. It is collected through methods that explore underlying reasons, opinions, and motivations, providing insights into the “why” and “how” of phenomena. Unlike quantitative data, which focuses on numbers and statistics, qualitative data deals with words, meanings, interpretations, and experiences.

Key Characteristics of Qualitative Data

To truly appreciate its power, understanding the fundamental characteristics of qualitative data is essential:

Exploratory: It seeks to understand concepts, opinions, or experiences rather than to measure them.
Contextual: It provides rich, in-depth understanding of a situation, problem, or human experience within its natural setting.
Interpretive: It relies heavily on the researcher’s interpretation of observations and conversations, seeking patterns and meanings.
Non-numerical: Its focus is on descriptions, narratives, and meanings, rather than statistical analysis.
Emergent: Key themes, hypotheses, and insights often surface organically during the data collection and analysis process, rather than being pre-defined.

Key Benefits for Innovation

Embracing qualitative data moves innovation from a mechanistic process to a deeply human one, unlocking several crucial benefits:

Uncovering Unmet Needs: It reveals pain points, desires, and behaviors that customers can’t articulate or that quantitative data masks. This is where breakthrough ideas truly lie, often in the subtle nuances.
Deep Empathy: Direct observation and conversation build a profound understanding of users’ lives, motivations, and emotional drivers, which is critical for designing truly human-centered solutions.
Contextual Understanding: It explains why a dashboard metric is fluctuating, or how a process is actually being used (or circumvented) in real-world scenarios, providing the “story behind the numbers.”
Idea Generation & Validation: Qualitative insights fuel powerful ideation, providing concrete human problems to solve, and then allow for rapid, iterative validation of concepts with real users.
Sense-Making in Complexity: In complex, ambiguous situations, qualitative data helps make sense of divergent perspectives and synthesize them into coherent pathways forward, offering clarity amidst chaos.
Building Organizational Stories: Human stories gleaned from qualitative research are far more powerful for galvanizing teams and stakeholders around a shared vision than charts and graphs alone, fostering engagement and buy-in.

Case Study 1: Re-imagining the Commute Experience

Challenge: Stagnant Public Transportation Ridership

A metropolitan transit authority was seeing stagnant ridership despite investments in new train cars and minor schedule adjustments. Their dashboards showed ridership numbers, peak times, and route popularity, but offered no insights into why people chose not to ride or why existing riders were sometimes dissatisfied.

Qualitative Intervention:

Instead of relying solely on quantitative surveys, the authority deployed ethnographic researchers. They rode trains and buses, interviewed commuters during their journeys, observed behavior at stations, and conducted in-home interviews about daily routines. They specifically looked for “un-articulated needs” and “workarounds.”

The Human-Centered Lesson:

What emerged was fascinating. Dashboards highlighted efficiency, but qualitative research revealed an emotional dimension: stress. Commuters felt a profound lack of control, from unpredictable delays to confusing information displays, to the anxiety of missing connections. One key insight: many commuters loved their “third space” (headphones, reading) but hated interruptions. This led to innovations like clearer real-time digital signage inside the cars, predictive arrival times on personal apps, and even small, quiet zones. These changes weren’t about speed, but about alleviating stress and increasing a sense of control and predictability—factors the numbers alone never revealed. Ridership subsequently increased, driven by an improved “emotional experience” rather than just functional efficiency.

Case Study 2: Understanding Small Business Lending Friction

Challenge: Low Adoption of Digital Lending Platform

A large bank launched a sophisticated new digital platform for small business loans, expecting high adoption. While dashboards showed a few initial users, conversion rates were low, and traditional loan applications still dominated. The quantitative data only indicated a problem, not its root cause.

Qualitative Intervention:

The bank’s innovation team conducted in-depth interviews with small business owners, observed them attempting to navigate the new platform, and even shadowed them during their busy workdays. They engaged in “contextual inquiry” to understand their daily challenges beyond just financial needs.

The Human-Centered Lesson:

The qualitative insights were striking. The digital platform was designed with a “big business” mindset, asking for detailed projections and complex financial statements that many small business owners, especially sole proprietors or new ventures, didn’t have readily available or structured in that format. They weren’t “digital averse”; they were “complexity averse” and “time-poor.” The qualitative research revealed their deep fear of making a mistake, of being judged, and the overwhelming feeling of paperwork. The solution wasn’t just to simplify the platform, but to introduce a human element: a “digital concierge” chatbot backed by human support, designed to guide them through the process in plain language, pre-populate forms with existing bank data, and reassure them at each step. This blended approach addressed the human anxiety, leading to a significant increase in digital platform adoption, proving that even a digital solution needs a human touch based on qualitative understanding.

Beyond Metrics: Cultivating a Qualitative Mindset

Integrating qualitative data means cultivating a new mindset within your organization. It means valuing stories as much as statistics, curiosity as much as certainty, and empathy as much as efficiency. It requires leaders to:

Get Out of the Office: Actively seek opportunities to spend time with customers, employees, and partners in their natural environments.
Ask “Why” (Five Times): Don’t settle for surface-level answers. Probe deeper to uncover root causes and underlying motivations.
Practice Active Listening: Hear not just words, but emotions, hesitations, and unspoken needs. Truly listen to understand, not just to respond.
Embrace Ambiguity: Qualitative data is messy; it doesn’t fit neatly into charts, but that’s precisely where the richest, most transformative insights reside. Be comfortable with uncertainty as you explore.

Dashboards show us the health of the body, but qualitative data reveals the beating heart and the dreams within the mind. To truly innovate in a human-centered way, we must look beyond the quantifiable surface and connect with the profound, often unstated, human truths that qualitative inquiry uncovers.

“Numbers tell us how many people clicked. Stories tell us why they might click next time.”

Your first step towards qualitative insight: Identify one critical customer journey or internal employee process that is currently under-performing or causing frustration. Instead of immediately diving into metrics, schedule five 30-minute, open-ended conversations with individuals who experience that journey or process daily. Ask them to describe their biggest challenges, unexpected moments, and what they secretly wish could be different. Just listen, without judgment or interruption, and take diligent notes. The insights you gain will be invaluable.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

Image credit: Dall-E

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Innovation or Not – The Trackless Train

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A Human-Centered Analysis

LAST UPDATED: November 13, 2025 at 1:23PM
Innovation or Not - The Trackless Train

GUEST POST from Chateau G Pato

In the urban mobility landscape, China’s Autonomous Rail Rapid Transit (ART) — colloquially known as the trackless train or trackless tram — has emerged as a major disruptive force. Operating on rubber tires guided by optical sensors and GPS along “virtual tracks” painted on the road, it mimics the capacity and ride quality of a light rail system without the immense cost and disruption of laying physical rails. The critical question for city leaders is: Does this technology satisfy a true Human-Centered Change imperative, or is it merely an aesthetically pleasing substitute?

Innovation, in my view, is defined by solving a problem with a solution that delivers orders of magnitude greater value to the end-user or the system. The trackless train is a powerful example of systemic innovation because it challenges the trade-off that has defined urban transit for a century: high capacity equals high infrastructure cost.

It sits squarely in the “mid-tier transit” niche, providing the capacity (up to 300-500 passengers) that traditional Bus Rapid Transit (BRT) often lacks, while avoiding the exorbitant cost ($100M+ per kilometer) and multi-year construction timelines of Light Rail Transit (LRT). This cost differential is the fundamental disruptive innovation, making high-capacity transit accessible to thousands of previously underserved cities.

The Three-Axis Innovation Test

To assess ART’s true innovative nature, we must evaluate it against three critical axes of change:

1. The Cost-Reduction Axis (Systemic Innovation)

The primary systemic innovation of the trackless train is the elimination of fixed steel rails. This massive reduction in civil engineering cost — with proponents suggesting installation for as little as $10M per kilometer compared to $130M per kilometer for LRT — is transformative for medium-sized cities globally. This enables cities previously locked out of high-capacity transit due to budget constraints to deploy a solution quickly. This is innovation by subtraction.

2. The User Experience Axis (Human-Centered Innovation)

For the passenger, the value proposition hinges on ride quality and reliability. ART leverages stabilization technologies borrowed from high-speed rail to offer a smoother, quieter ride than a standard articulated bus. Furthermore, its guidance system and dedicated lane operations (where implemented) ensure a higher level of punctuality and predictability than mixed-traffic buses. The rail-like aesthetic also positively impacts land use, encouraging development around stations much like traditional rail. The faster deployment time also means citizens get access to improved transit sooner, a key human-centered benefit.

3. The Operational Flexibility Axis (Adaptive Innovation)

Unlike fixed-rail systems, ART offers greater adaptive flexibility. The vehicles are bi-directional and, crucially, can temporarily leave their virtual track to navigate around accidents or construction, a capability impossible for LRT. This allows the system to remain resilient to unexpected urban disruption, delivering a less frustrated customer experience.

The Challenge: Critics argue that this flexibility undercuts its benefit, as it still operates in mixed traffic and lacks the legal permanence that fixed rail offers to developers for long-term investment guarantees.

Case Study 1: Yibin, China – The Speed and Cost Imperative

Challenge: Rapid Urban Expansion vs. Traditional Rail Cost

Yibin, a city in Sichuan, China, experienced rapid population growth and needed a mid-capacity transit solution quickly to connect the old city center with its new high-speed rail network. Traditional LRT was deemed too expensive and time-consuming for the required 17.7km line through dense urban areas.

ART Intervention:

Yibin adopted the ART system (Line T1). The line was constructed and made operational in less than a year at a cost estimated around $13M/km — significantly less than the cost of conventional light rail. The short deployment time was critical to connecting the new high-speed rail station to the city’s commercial hubs almost immediately upon its completion. The ART was able to deliver a rail-like experience — speed (up to 70kph) and capacity (300 passengers per train) — at an accelerated timeline, thereby redefining the transit delivery schedule constraint.

The Innovation Takeaway:

This case demonstrates the value of Time-to-Market Innovation. The ART solution allowed Yibin to unlock the economic benefits of its high-speed rail investment years earlier than a conventional project would have allowed. The combination of speed and cost proved to be the transformative change agent.

The Gadgetbahn Critique: Is it Just a Fancy Bus?

A significant, rational critique from the transit community dismisses ART as a “gadgetbahn” — a glorified articulated bus. Critics point out that the system still requires reinforced concrete guideways to handle the multi-axle steering and rubber wheels repeating the same trajectory, which can cause significant differential road wear and compromise the promised low disruption and quick deployment. This addresses a critical flaw in the infrastructure savings claim.

However, the innovation lies not just in the hardware, but in the integration of technologies — high-speed rail stabilization, sensor-fusion guidance (GPS, Lidar), and multi-car articulation — that collectively push it into a new capacity and ride-quality tier. It’s an example of combinatorial innovation, where existing technologies are synthesized to solve a previously intractable systemic problem. It is a bus platform elevated to a new class of service, offering a viable, lower-cost step between high-quality BRT and full LRT.

Case Study 2: Perth, Australia – The Policy Barrier Test

Challenge: Certifying a New Mid-Tier System in a Developed Market

Perth, Western Australia, was one of the first Western cities to commit to implementing ART. Their challenge was not technical feasibility, but rather overcoming the rigid, decades-old regulatory framework that recognizes only two categories: fixed rail and road vehicles (buses/cars). ART fits neither.

ART Intervention:

The Perth initiative received funding for certification and demonstration of the ART vehicle. The focus of the trial was less on performance and more on addressing the policy and safety assurance gap. This involved proving how the vehicle’s unique steering, braking, and guidance systems met stringent public transport safety standards, essentially forcing a regulatory body to create a new transit category. The investment here is in demonstrating the integrity of the system to a skeptical, risk-averse regulatory environment.

The Innovation Takeaway:

The Perth case highlights that Innovation is often a Policy Problem. The ART forces cities to rethink urban transit categories, creating a viable regulatory precedent for mid-tier transit globally. The innovation is the ability to adapt to, and ultimately change, the institutional environment required for mass-scale adoption.

Conclusion: Redefining the Rail Niche

The trackless train is more than a clever bus. It is a powerful disruptive innovation because it provides a high-value trade-off for urban planners: high capacity and quality at a fraction of the cost and time. While it will not replace subways or traditional high-density light rail, it creates a new, accessible rail niche for the thousands of medium-sized cities worldwide that need a step up from BRT but cannot afford LRT. It provides the capacity necessary to drive urban regeneration without the financial burden, fundamentally changing how we approach city-shaping.

“True innovation eliminates the impossible trade-off. The trackless train removes the ‘rail-or-bust’ constraint for millions of urban citizens.”

Your first step toward systemic innovation: Identify one systemic problem in your organization currently constrained by a high cost/high time trade-off, and challenge your teams to find a combinatorial solution that eliminates the cost barrier entirely, much like the trackless train.

Image credit: Pexels

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Poking the Box for Innovation

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Poking the Box for Innovation One of the best ways to challenge people’s thinking and get a group moving in a direction towards innovation is to get the group to define the box.

Of course a million and one innovation and creativity consultants will endlessly drone on about thinking outside the box, but how can think outside the box if you’re not first clear on what the box looks like that you’re trying to think outside of?

When I speak about poking the box, I’m not doing so in the Seth Godin ‘take a risk’ sense, but from the perspective of wanting people to visualize themselves standing in the box, giving a voice to what each of the six main sides are for the context in which you’re trying to innovate.

Start by making a list of the top six assumptions/constraints that we all make in this context:

Assumption/Constraint
Assumption/Constraint
Assumption/Constraint
Assumption/Constraint
What does success look like in this context? — or alternatively, another Assumption/Constraint
What does failure look like in this context? — or alternatively, another Assumption/Constraint

I’d like to thank innovation colleague Ton Verbeek for sharing the following video which looks at the ‘box’ of ground transportation and what happens if you shift from a 2D approach to ground transportation to a 3D approach:

So, what are the assumptions in ground transportation?

What are the constraints?

What does success look like in ground transportation?

What does failure look like in ground transportation?

How has the designer who created this video poked the box?

How has the designer explored the walls of the box and proposed pushing some of them outwards?

Which other assumptions or constraints could be challenged in ground transportation and what characteristics would potential solutions have in order to push a particular wall outwards?

As an example, I would say that the assumption the designer has challenged here in the context of ground transportation is the following:

— Must make efficient use of land to transport the maximum amount of people and goods

What other walls of the ground transportation box could and what would that look like?

Accelerate your change and transformation success

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Who is the Innovator? Amazon or Kroger?

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Kroger ClickList

Now, first of all, Kroger is a Cincinnati-based company not a Seattle-based company, so it is only natural that I should hear more about the things Amazon is experimenting with than those of Kroger, owners of a portfolio of grocery brands, including: Ralphs, Fred Meyer, QFC, Kroger, fry’s, Food4Less, King Soopers, Harris Teeter, and more.

Amazon has been making a lot of noise with some of their experiments lately, including a convenience store concept where eventually you will be able to pick up what you want to buy and then automatically be charged for your acquisitions on the way out the door. It is called Amazon go and is currently being tested in an employees-only store. Here is what it looks like:

And then of course Amazon has been experimenting with the last mile experience in grocery retailing for a while now with Amazon Fresh grocery delivery business in a few U.S. states along with London, Berlin, and Tokyo. Now they are also experimenting with a grocery pickup service. You can pickup your groceries in as little as 15 minutes after ordering. It’s available exclusively for Prime members in a testing phase beginning in Seattle.

Now, the past couple of weeks I’ve been noticing at one of my local Fred Meyer’s and one of the neighborhood QFC’s some workers doing some construction projects and I wasn’t sure exactly what they were up to, but today it became clear that they’ve been busy prepping for to enable Kroger ClickList at those locations, which is basically the same thing as AmazonFresh Pickup, EXCEPT that Kroger started doing this TWO YEARS AGO and scaled it to 500 locations in less than 17 months. If you’re curious, here is what Kroger CLickList looks like:

And yes, Walmart, not to be outdone, also has a grocery pickup service as well (which they started a little over a year ago).

For what it’s worth, if these companies were to combine this service with improved ready-to-eat meal offerings like we used to regularly utilize from Waitrose and Tesco so that people can pickup their groceries and a dinner they can eat right when they get home and this will really catch on. Now for those of you who haven’t experienced ready meals in the UK, then check out the following links to get a tastier idea:

— Waitrose Ready Meals
— Tesco Ready Meals

Waitrose Lasagne

So, Amazon is getting a lot of buzz around their Amazon Go and AmazonFresh Pickup experiments, but they are just that at this point. Meanwhile, Kroger and Walmart have already scaled some of these experiments, so who is the innovator here?

Just another reminder that anyone can innovate, that it is customer insight not technology that drives innovation, and that every company is a technology company whether they like it or not.

Keep innovating!

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Consulting Industry Faces Threat From Artificial Intelligence

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Consulting Industry Faces Threat From Artificial Intelligence

by Braden Kelley

Previously I explored the value of eminence and thought leadership to consulting firms, and how unfortunately the power of inbound content marketing has a dark side that forms part of a three-pronged attack on the consulting industry.

Meanwhile, the tireless invention and innovation efforts of research teams in companies around the world have helped to keep the pace of technological advancement in computer processing power at or above Moore’s Law for several decades. This has given technology companies the ability to put more computing power than the entire Apollo space program into the pockets of more than a billion people around the world.

It seems like everything has become digital, including music, books, and even movies. Increasingly intelligent digital technologies and mercurial customer expectations threaten both people and enterprise at every turn. With all of this technological change, the last few decades have been an amazing time for consultancies, full of revenue and opportunities. Clients desperate for solutions to help them cope with these challenging times helped management consulting firms grow in size and scale, expanding to cover multiple technology, and even marketing, specialties.

But the same technologies that have led to the growth of consulting companies over the last couple of decades, will begin to lead to a shrinking of those same consulting firms. The increasing diversification of the large global consultancies into other specialties is the first step to what is an inevitable shrinkage forced upon the industry by the three factors I detailed in my last article titled Consulting Industry Caught in the Crossfire.

The same forces that are causing a feeling of disequilibrium for the firms that consultancies serve are also causing the same unease, trepidation and challenge for the consulting firms themselves as they find themselves attacked on three sides from:

1. Increasingly Available Intellectual Property
2. Internal Consultants
3. Artificial Intelligence

In my previous article on the Consulting Industry Attacked on Three Sides I looked at each attack in turn, but in this article I would like to dig a bit deeper into the final threat.

Artificial Intelligence

Roboadvisors, chatbots, and other implementations of artificial intelligence have captured people’s imaginations and led to both an increase in the number of articles written about artificial intelligence, but also in the practical implementations of artificial intelligence. People are becoming increasing comfortable with artificial intelligence thanks to the recommendation engines on Amazon and Netflix and IBM Watson’s appearance on the game show Jeopardy and battles against chess grandmasters.

But what does consulting have to fear from artificial intelligence?

Perhaps viewing this short video might give you a glimpse:

In the short run, maybe consultants don’t have as much to fear from artificial intelligence as workers in transportation, retail, or manufacturing. But, in the grander scheme of things, over time enterprising technology vendors will inevitably build upon publicly available artificial intelligence frameworks made publicly available by companies like Microsoft and Google (who are seeking to increase the sale of cloud services) to automate some of the tasks that recently minted undergraduate analysts or Indians perform now for the large consulting firms.

What we are starting to see is exactly what Roger Martin described in his landmark book The Design of Business, from which I would like to highlight one of the key concepts called The Knowledge Funnel highlighted in the image from the book below.

Is Jack White's Lazaretto Ultra LP a Vinyl Innovation? Source: The Design of Business by Roger Martin

The key point here is that as we understand our business and our interactions with our customers well enough, what was once a mystery we start to identify patterns inside of (heuristics), which then eventually allows us to create algorithms that can be captured in Standard Operating Procedures (SOP’s) and then eventually in code. The power of artificial intelligence is the ability to move the role of the machine to the left in The Knowledge Funnel, away from pure manual coding by a human, to computer programs that write themselves and eventually to heuristic identification and algorithm creation at some point in the near future. This is what crowd computing, machine learning and deep learning ultimately make possible, and which I explored in a previous article titled Welcome to the Crowd Computing Revolution in more detail. The fact remains that as computer programmers and the artificial minds they create become more adept at watching the work that consultants do and recognizing the patterns in their recommendations, the pressure on consultancies will build.

Conclusion

These are challenging times for large consultancies and small independent consultants as consultancies are forced respond to these attacks from three sides. Part of that three-pronged attack will come from a growing legion of automation engineers taking to cubicles around the world to design people out of jobs. In the same way that mechanical engineers build robots to replace our human muscles with machine muscles, automation engineers are computer programmers tasked with creating inexpensive machine minds with sufficient artificial intelligence to replace our more expensive human minds. Professions like that of the automation engineer will attract increasing numbers from workforces around the world, but not nearly enough to offset the losses in job opportunities that these individuals are tasked with eliminating. Only time will tell how quickly and how broadly artificial intelligence (AI) threatens the core business of consultancies.

If you are in the consulting industry, what is your strategy for responding to this threat?

Because, make no mistake, the threat is real. The only question is how quickly it will materially impact your bottom line.

BONUS:

You might enjoy this interview with David Cope, the creator of Emi (Emily Howell) the algorithmic composer, whom he later killed:

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Consulting Industry Being Attacked on Three Sides

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Consulting Industry Being Attacked on Three Sides

by Braden Kelley

The worlds of employment and business are becoming increasingly turbulent as the stability of the enterprise grows ever shorter, the loyalty of the enterprise to its people faces extinction, and the wealthy countries of the world stand at a precipice of overhanging debt. Increasingly intelligent digital technologies and mercurial customer expectations threaten both people and enterprise at every turn.

One would suppose that this would be an amazing time for consultancies, full of promise and opportunities. One would imagine that clients desperate for solutions that help them cope with these challenging times would be banging down the doors of consulting firms outbidding each other to the firm’s next client.

But that is not the reality…

Because, the same forces that are causing a feeling of disequilibrium for the firms that consultancies serve are also causing the same unease, trepidation and challenge for the consulting firms themselves.

The fact is that the consulting industry is being attacked on three sides:

Increasingly Available Intellectual Property
Internal Consultants
Artificial Intelligence

Let’s look at each threat in turn:

1. Increasingly Available Intellectual Property

In my last article, “Thought Leadership Builds Firm Value”, I wrote about the importance of thought leadership in today’s digital age and its role in helping to drive inbound sales leads.

Hiring a consultancy, even for a small project, is a big expenditure for most companies, something that requires several levels of approval before the project can begin. Given that, company employees take to the Internet to build their consideration set and to do their research into how each company thinks and who seems to be the leader in the space where they need help. For help with building an innovation or digital transformation strategy or process, often they find me.

The way that company employees find the companies they will include in their consideration set, and the individual (or firm) they will ultimately hire, is by finding and evaluating thought leadership created by consultants like myself who are good at creating frameworks and other tools aimed at simplifying complex concepts (referred to as eminence by some firms).

Because the discovery and evaluation of thought leadership by potential customers is a key way that independent consultants and advisory firms attract new business, and because it is easier than ever to create and share thought leadership while simultaneously becoming an increasingly important factor in the buying process, independent consultants and advisory firms are creating more pieces of thought leadership and eminence than ever before.

On the plus side, thought leadership and eminence help independent consultants and advisory firms to win business. The down side however is that in much the same way that kids in Hawaii have learned how to become professional surfers by watching YouTube videos, as advisory firms create more thought leadership and make it publicly available to win new business, they also stand to lose an accelerating amount of new business as well. The reason is that the proliferation of eminence and thought leadership will inevitably lead to:

Increasing numbers of line managers feeling that they know enough to tackle the challenge themselves that they might have otherwise outsourced to a consulting firm
Increasing numbers of senior leaders deciding that someone inside their company could spin up and lead an internal consulting group

2. Internal Consultants

Let’s face it, whether we like it or not, an increasing number of senior leaders are becoming fed up with spending $500/hr on newly minted MBA’s from McKinsey, Bain, BCG, etc. when they could hire them on full-time for $75-100/hr by taking one of their promising senior leaders and having them spin up an internal consulting group.

Many companies have already created internal consulting groups to handle the bulk of their strategic project work in order to either:

Save money
Increase responsiveness
Increase speed to market
Keep the knowledge gained from such projects readily accessible
Create and retain a competitive advantage

For me, reason number five is potentially the most compelling reason because it is impossible to expect any large consulting firm to unlearn the insights they acquire on one consulting project and not leverage them on a subsequent project with a competitor somewhere down the line. Doing projects with your competitors is how a great deal of industry expertise is gained by large consultancies, and this expertise is one of the primary reasons that managers hire a consulting firm.

3. Artificial Intelligence

But what does consulting have to fear from artificial intelligence?

In the short run, maybe not a lot. But, in the grander scheme of things, over time enterprising technology vendors will inevitably build upon publicly available artificial intelligence frameworks made publicly available by companies like Microsoft and Google (who are seeking to increase the sale of cloud services) to automate some of the tasks that recently minted undergraduate analysts or Indians perform now for the large consulting firms.

Conclusion

These are challenging times for independent consultants as they respond to these attacks from three sides. Only time will tell how quickly and how broadly artificial intelligence (AI) threatens the core business of consultancies. The internal consultancy threat is real and growing in scope and threat. What may have started in Project and Portfolio Management (PPM), Six Sigma, Lean and Agile practices in some organizations, is quickly expanding into other Operational Excellence areas and even into Innovation, Digital Transformation, and traditional Strategy. Increasingly available intellectual property poses a Catch-22 for consultancies as a refusal to participate in the creation of eminence and thought leadership will lead to less business in the short-term, but doing so will certainly over time lead to an overall reduction in the size of the market for consulting services. Some consultancies are responding by diversifying their service offerings, attempting to create consulting superstores. What will be your response to this attack from three sides?

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FedEx Not Keeping Pace

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FedEx Not Keeping Pace FedEx took the shipping world by storm about forty years ago, growing to become the defacto shipping leader, unseating UPS and DHL. But, then after thirty years of strong growth they began to lose their mojo. In 2003, in a reaction to UPS’ acquisition of Mail Boxes Etc., FedEx announced they were buying Kinko’s, a large United States based copy center chain. For me this showed that FedEx was beginning to lose its way, and it appears their connection to customer expectations and the current capabilities of technology is failing. For a company based on the promise of speed, FedEx is becoming increasingly slow.

Increasingly frustrated with the performance of FedEx, Amazon has increasingly turned to the United States Postal Service to deliver its packages, striking a special deals with USPS to even deliver packages on Sunday. And now, Amazon is beginning to buy trailers so they can potentially contract directly with truck drivers to help them move inventory from one distribution node to another.

And for me, my latest FedEx misadventure is a perfect example of why FedEx is now in trouble and at risk of falling from its perch. Here’s what’s happened so far.

I ordered a new laptop from HP that was supposed to arrive in three (3) days on Saturday, July 9th
On Saturday, July 9th I received no contact from FedEx or estimate for when my package might be delivered
On Saturday, July 9th FedEx attempted to deliver the package when we weren’t home
For some reason FedEx then determined they were going to wait THREE DAYS before attempting re-deliver the package
On Tuesday, July 12th I received no contact from FedEx or estimate for when my package might be delivered
On Tuesday, July 12th FedEx despite someone being home nearly all day, FedEx attempted to deliver the package when we weren’t home
On Wednesday, July 13th I received no contact from FedEx or estimate for when my package might be delivered
On Wednesday, July 13th FedEx despite someone being home nearly all day, FedEx attempted to deliver the package when we weren’t home
On Thursday, July 14th I received a missed call and voicemail from FedEx
On Thursday, July 14th I attempted to call the FedEx number given and nobody answered the phone, got voicemail and left message
On Friday, July 15th the Web site indicated that package would be delivered again that day, but no delivery came
On Friday, July 15th I called FedEx and got voicemail
On Friday, July 15th I called FedEx again and got a person, hooray! But, the person said my only option was to drive a fair distance to come pick it up or have it delivered to a FedEx location near me.
On Friday, July 15th I chose to have the package delivered to my local FedEx location (a Kinko’s about 5-10 miles away) under the impression it would be available Saturday, July 16th at this location for my pickup and that they would probably call me after it arrived
On Saturday, July 16th I went to the Kinko’s around 7pm figuring that it must be there by that time (How long could it take to ship a package 15-20 miles from one FedEx location to another?)
On Saturday, July 16th at the Kinko’s the employee was unable to find the package
On Saturday, July 16th at the Kinko’s the employee was unable to get any information from their systems because they were down for maintenance
On Saturday, July 16th at the Kinko’s the employee was able to call and using a voice response system get a Tuesday, July 19th delivery estimate to their location
On Monday, July 18th I received a postcard from FedEx saying they had tried to deliver my package three times and to contact them (NOTE: this was a very confusing postcard, not obvious what to do)
On Tuesday, July 19th I received a phone call from the FedEx Kinko’s store saying they had my package, and I picked it up a few hours later after they used my name (no technology) to search a pile of packages in the back

VERY BAD EXPERIENCE – I got my package TEN DAYS AFTER I was supposed to get it, and nearly two weeks after I ordered the laptop.

Inaccurate information on the web site, poor customer service, bad technology, slow resolution…

These are all signs that this logistics company has gone off track and has not kept pace with the capabilities of technology today.

There is no reason why FedEx shouldn’t have been able to:

Show me online exactly where my package is
When FedEx is estimating it to be delivered based on the packages loaded on the truck and the planned route
Offer me the opportunity to select an alternate delivery time or date or location if the likely delivery time doesn’t work for me

This would be customer service.

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Microsoft’s Seeing AI Glasses

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Microsoft Seeing AI Glasses

Saqib Shaikh lives is blind, lives in London, and is a core Microsoft developer. He lost the use of his eyes at age 7. Saqib found inspiration in software development and is helping build Seeing AI, a research project helping blind or visually impaired people to better understand who and what is around them. The app is built using intelligence APIs from Microsoft Cognitive Services.

Pretty amazing that an app can use a camera to capture an image or a video feed, and using artificial intelligence, to analyze the scene and vocalize to the user what it sees. In this example this is being done for the benefit of a human user, but imagine what could be possible if one computer program is used to serve instead, another computer program as the user of the analysis. What might that make possible?

How might you or your organization make use of technology like this?

What direction do you think technology like this will take?

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What April Fool’s Day Teaches Us About Innovation

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What April Fool's Day Teaches Us About Innovation

April Fool’s Day was this week. Did anyone have a good prank played on them or come across a good corporate April Fool’s?

My favorite this year was from my alma mater, the University of Oregon. Go Ducks!

We try to think a little differently at the University of Oregon and specialize in helping the world run a little faster (and more comfortably), and with some of Nike’s founder behind the football team, why shouldn’t they have the world’s most advanced field, say, an LED field?

Watch the video:

The best corporate April Fool’s Day pranks are the ones that are believable and almost seem feasible.

What does this tell us as innovation professionals?

The insight is that the best corporate April Fool’s Day pranks find a resonance point, a place where the outlandish intersects with what people are ready for, what they may actually desire, and what they believe should be possible soon.

Consider asking your innovation teams to design their own April Fool’s Day prank and see where it takes you.

Ask yourself questions like these about their designs:

What must be true for this to be possible?
What stands in the way of this being possible?
What would it take to remove the barriers that are preventing this from being possible?
Are our customers truly ready for this?
What would it take to prepare them for it?
What capabilities do we need to build to prepare for this eventuality?
Is this idea more feasible in a different context? (i.e. basketball courts instead of football fields)
Etc.

One final thought…

Is there any reason why the field shown in the University of Oregon LED field video couldn’t become a reality?

Why couldn’t it be built out of some of kind of fiber optic material that maintained both the sports performance characteristics and the multi-color transmission capabilities?

Would it be easy to design such a thing? No. But it seems possible, and that’s where innovation begins…

Keep innovating!

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Service Redesign – Lost T-Mobile Smartphone

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Service Redesign - Lost T-Mobile Smartphone

Given the health risks of carrying a smartphone (or any kind of mobile device) too close to the body for extended periods, I try to always remove electronic devices from my pockets whenever I can. For ten years this has never caused a problem until Saturday. This marked the first time in more than a decade that I walked off and forgot my smartphone.

Now I’ve had the joy of reporting my lost phone to T-Mobile and getting a less than helpful response. Not because the agent I spoke with didn’t try to be helpful, but because the customer service representative was trapped inside of a service experience that wasn’t designed to meet the goals of the customer.

First I must mention that I don’t have a find my phone type app installed on my phone because I don’t like the idea of someone tracking me all the time. Second, yes, I know that even with location awareness or GPS turned off that my phone is being tracked anyways, but I still like to maintain the illusion that my every move isn’t being tracked. So, please humor me.

The fact is that T-Mobile could tell me exactly where my phone is even without such an app, but then they would have to breach the illusion and admit that they’re always tracking where every phone is at all times. Not such a good customer experience.

Redesigning the Lost Smartphone Experience

I’m only one person so this list won’t be as good as if I was working on this with a small team and prototyping with customers, but let’s ignore that for now and try to come up with a list of customer goals (and thus opportunities to delight) in the lost smartphone scenario:

I don’t want someone to use my phone after I lose it to make calls that I’ll have to pay for (international calls, premium calls, etc.)
I don’t want someone to buy anything (apps, music or other content that I’ll have to pay for)
I don’t want someone to call my contacts
I don’t want someone to use my apps and make in app purchases
I don’t want someone to use my texting function (SMS) – read, send, etc.
I don’t want someone to use my email – read, send, etc.
I don’t want someone accessing my photos
I don’t want someone to steal information about my contacts
I want to be able to call my phone to try and speak with the person who found it so I can try and get it back
I want the person to be able to call me or T-Mobile to let me know that they’ve found my phone

In short, I don’t want someone who finds my phone to be able to do anything other than contact me to let me know when and where I can come pick it up.

But, when I called to T-Mobile to report my phone lost the only option was to have the phone disabled. Prior to doing so, calling my phone was going straight to voicemail, and maybe I should have left a voicemail, but I didn’t, I thought I would try again later. After they disabled my phone, instead of getting voicemail I got a message saying the phone has been reported lost and that I wouldn’t be able to leave a voicemail. This is partially helpful, but not completely. Now I can’t call the phone and if someone has found the phone, they can’t try to contact anyone to arrange a pickup.

T-Mobile has met goal #1 (and possibly #2-4), but likely they could access #5-8 (able to read but probably not to send).

But, there are many other goals that have not been met. Most importantly, T-Mobile has actually made it less likely that I will get my phone back because I have no way of communicating with the person who may have my phone.

What could T-Mobile do to make this experience better?

Simple.

When a phone is reported lost, T-Mobile should make it so that the phone can only call T-Mobile. If the person calls, then T-Mobile knows which number is calling, can get information from the caller to connect the two parties to arrange a pickup, and pass on the contact details to the subscriber via pre-arranged methods.

Second, T-Mobile should allow designated numbers to call the phone, so that the subscriber can try to get in touch with whoever found the phone.

Third, T-Mobile could call the phone every 15-30min with a robot until someone answers and connect them with a T-Mobile representative.

These three small changes to their lost phone service design would make an immediate positive impact in the customer experience for thousands of customers.

How else could T-Mobile make the experience better?

Image credit: easyhacker.com

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