Experience Digital by Mike Kent

Transformation with a capital T – Why transformations fail and how to do it right

Companies must be prepared to tear themselves away from routine thinking and behaviour.

dig-transImagine. You lead a large basic-resources business. For the past decade, the global commodities supercycle has fueled volume growth and higher prices, shaping your company’s processes and culture and defining its outlook. Most of the top team cannot remember a time when the business priorities were different. Then one day it dawns on you that the party is over.

Or imagine again. You run a retail bank with a solid strategy, a strong brand, a well-positioned branch network, and a loyal customer base. But a growing and fast-moving ecosystem of fintech players—microloan sites, peer-to-peer lenders, algorithm-based financial advisers—is starting to nibble at your franchise. The board feels anxious about what no longer seems to be a marginal threat. It worries that management has grown complacent.

In industry after industry, scenarios that once appeared improbable are becoming all too real, prompting boards and CEOs of flagging (or perhaps merely drifting) businesses to embrace the T-word: transformation.

Transformation is perhaps the most overused term in business. Often, companies apply it loosely—too loosely—to any form of change, however minor or routine. There are organizational transformations (otherwise known as org redesigns), when businesses redraw organizational roles and accountabilities. Strategic transformations imply a change in the business model. The term transformation is also increasingly used for a digital reinvention: companies fundamentally reworking the way they’re wired and, in particular, how they go to market.

What we’re focused on here—and what businesses like the previously mentioned bank and basic-resource companies need—is something different: a transformation with a capital T, which we define as an intense, organization-wide program to enhance performance (an earnings improvement of 25 percent or more, for example) and to boost organizational health. When such transformations succeed, they radically improve the important business drivers, such as topline growth, capital productivity, cost efficiency, operational effectiveness, customer satisfaction, and sales excellence. Because such transformations instill the importance of internal alignment around a common vision and strategy, increase the capacity for renewal, and develop superior execution skills, they enable companies to go on improving their results in sustainable ways year after year. These sorts of transformations may well involve exploiting new digital opportunities or accompany a strategic rethink. But in essence, they are largely about delivering the full potential of what’s already there.

The reported failure rate of large-scale change programs has hovered around 70 percent over many years. In 2010, conscious of the special challenges and disappointed expectations of many businesses embarking on transformations, McKinsey set up a group to focus exclusively on this sort of effort. In six years, our Recovery & Transformation Services (RTS) unit has worked with more than 100 companies, covering almost every geography and industry around the world. These cases—both the successes and the efforts that fell short—helped us distill a set of empirical insights about improving the odds of success. Combined with the right strategic choices, a transformation can turn a mediocre (or good) business into a world-class one.

Why transformations fail

Transformations as we define them take up a surprisingly large share of a leadership’s and an organization’s time and attention. They require enormous energy to realize the necessary degree of change. Herein lie the seeds of disappointment. Our most fundamental lesson from the past half-dozen years is that average companies rarely have the combination of skills, mind-sets, and ongoing commitment needed to pull off a large-scale transformation.

It’s true that across the economy as a whole, “creative destruction” has been a constant, since at least 1942, when Joseph Schumpeter coined the term. But for individual organizations and their leaders, disruption is episodic and sufficiently infrequent that most CEOs and top-management teams are more accomplished at running businesses in stable environments than in changing ones. Odds are that their training and practical experience predominantly take place in times when extensive, deep-rooted, and rapid changes aren’t necessary. For many organizations, this relatively placid experience leads to a “steady state” of stable structures, regular budgeting, incremental targets, quarterly reviews, and modest reward systems. All that makes leaders poorly prepared for the much faster-paced, more bruising work of a transformation. Intensive exposure to such efforts has taught us that many executives struggle to change gears and can be reluctant to lead rather than delegate when they face external disruption, successive quarters of flagging performance, or just an opportunity to up a company’s game.

Executives embarking on a transformation can resemble career commercial air pilots thrust into the cockpit of a fighter jet. They are still flying a plane, but they have been trained to prioritize safety, stability, and efficiency and therefore lack the tools and pattern-recognition experience to respond appropriately to the demands of combat. Yet because they are still behind the controls, they do not recognize the different threats and requirements the new situation presents. One manufacturing executive whose company learned that lesson the hard way told us, “I just put my head down and worked harder. But while this had got us out of tight spots in the past, extra effort, on its own, was not enough this time.”

Tilting the odds toward success

The most important starting point of a transformation, and the best predictor of success, is a CEO who recognizes that only a new approach will dramatically improve the company’s performance. No matter how powerful the aspirations, conviction, and sheer determination of the CEO, though, our experience suggests that companies must also get five other important dimensions right if they are to overcome organizational inertia, shed deeply ingrained steady-state habits, and create a new long-term upward momentum. They must identify the company’s full potential; set a new pace through a transformation office (TO) that is empowered to make decisions; reinforce the executive team with a chief transformation officer (CTO); change employee and managerial mind-sets that are holding the organization back; and embed a new culture of execution throughout the business to sustain the transformation. The last is in some ways the most difficult task of all.

Stretch for the full potential

Targets in most corporations emerge from negotiations. Leaders and line managers go back and forth: the former invariably push for more, while the latter point out all the reasons why the proposed targets are unachievable. Inevitably, the same dynamic applies during transformation efforts, and this leads to compromises and incremental changes rather than radical improvements. When managers at one company in a highly competitive, asset-intense industry were shown strong external evidence that they could add £250 million in revenue above what they themselves had identified, for example, they immediately talked down the proposed targets. For them, targets meant accountability—and, when missed, adverse consequences for their own compensation. Their default reaction was “let’s underpromise and overdeliver.”

To counter this natural tendency, CEOs should demand a clear analysis of the company’s full value-creation potential: specific revenue and cost goals backed up by well-grounded facts. We have found it helpful for the CEO and top team to assume the mind-set, independence, and tool kit of an activist investor or private-equity acquirer. To do so, they must step outside the self-imposed constraints and define what’s truly achievable. The message: it’s time to take a single self-confident leap rather than a series of incremental steps that don’t lead very far. In our experience, targets that are two to three times a company’s initial estimates of its potential are routinely achievable—not the exception.

Change the cadence

Experience has taught us that it’s essential to create a hub to oversee the transformation and to drive a cadence markedly different from the normal day-to-day one. We call this hub the transformation office.

What makes a TO work? One company with a program to boost EBITDA1by more than $1 billion set up an unusual but highly effective TO. For a start, it was located in a circular room that had no chairs—only standing room. Around the wall was what came to be known, throughout the business, as “the snake”: a weekly tracker that marked progress toward the goal. By the end of the process, the snake had eaten its own tail as the company materially exceeded its financial target.

Each Tuesday, at the weekly TO meeting, work-stream leaders and their teams reviewed progress on the tasks they had committed themselves (the previous week) to complete and made measurable commitments for the next week in front of their peers. They used only handwritten whiteboard notes—no PowerPoint presentations—and had just 15 minutes apiece to make their points. Owners of individual initiatives within each work stream reviewed their specific initiatives on a rotating basis, so third- or fourth-level managers met the top leaders, further increasing ownership and accountability. Even the divisional CEO made a point of attending these TO meetings each time he visited the business, an experience that in hindsight convinced him that the TO process was more crucial than anything else to shifting the company’s culture.

For senior leaders, distraction is the constant enemy. Most prefer talking about new customers, M&A opportunities, or fresh strategic choices—hence the temptation at the top to delegate responsibility to a steering committee or an old-style program-management office charged with providing periodic updates. When top management’s attention is diverted elsewhere, line managers will emulate that behavior when they choose their own priorities.

Given these distractions, many initiatives move too slowly. Parkinson’s law states that work expands to fill the time available, and business managers aren’t immune: given a month to complete a project requiring a week’s worth of effort, they will generally start working on it a week before the deadline. In successful transformations, a week means a week, and the transformation office constantly asks, “how can you move more swiftly?” and “what do you need to make things happen?” This faster clock speed is one of the most defining characteristics of successful transformations.

Collaborating with senior leaders across the entire business, the TO must have the grit, discipline, energy, and focus to drive forward perhaps five to eight major work streams. All of them are further divided into perhaps hundreds (even the low thousands) of separate initiatives, each with a specific owner and a detailed, fully costed bottom-up plan. Above all, the TO must constantly push for decisions so that the organization is conscious of any foot dragging when progress stalls.

Bring on the CTO

Managing a complex enterprise-wide transformation is a full-time executive-level job. It should be filled by someone with the clear authority to push the organization to its full potential, as well as the skills, experience, and even personality of a seasoned fighter pilot, to use our earlier analogy.

The chief transformation officer’s job is to question, push, praise, prod, cajole, and otherwise irritate an organization that needs to think and act differently. One CEO introduced a new CTO to his top team by saying, “Bill’s job is to make you and me feel uncomfortable. If we aren’t feeling uncomfortable, then he’s not doing his job.” Of course, the CTO shouldn’t take the place of the CEO, who (on the contrary) must be front and center, continually reinforcing the idea that this is my transformation.

Many leaders of traditional program-management offices are strong on processes but unable or unwilling to push the CEO and top team. The right CTO can sometimes come from within the organization. But one of the biggest mistakes we see companies making in the early stages is to choose the CTO only from an internal slate of candidates. The CTO must be dynamic, respected, unafraid of confrontation, and willing to challenge corporate orthodoxies. These qualities are harder to find among people concerned about protecting their legacy, pursuing their next role, or tiptoeing around long-simmering internal political tensions.

What does a CTO actually do? Consider what happened at one company mounting a billion-dollar productivity program. The new CTO became exasperated as executives focused on individual technical problems rather than the worsening cost and schedule slippage. Although he lacked any background in the program’s technical aspects, he called out the facts, warning the members of the operations team that they would lose their jobs—and the whole project would close—unless things got back on track within the next 30 days. The conversation then shifted, resources were reallocated, and the operations team planned and executed a new approach. Within two weeks, the project was indeed back on track. Without the CTO’s independent perspective and candor, none of that would have happened.

Remove barriers, create incentives

Many companies perform under their full potential not because of structural disadvantages but rather through a combination of poor leadership, a deficient culture and capabilities, and misaligned incentives. In good or even average times, when businesses can get away with trundling along, these barriers may be manageable. But the transformation will reach full potential only if they are addressed early and explicitly. Common problematic mind-sets we encounter include prioritizing the “tribe” (local unit) over the “nation” (the business as a whole), being too proud to ask for help, and blaming the external world “because it is not under our control.”

One public utility we know was paralyzed because its employees were passively “waiting to be told” rather than taking the initiative. Given its history, they had unconsciously decided that there was no advantage in taking action, because if they did and made a mistake, the results would make the front pages of newspapers. A bureaucratic culture had hidden the underlying cause of paralysis. To make progress, the company had to counter this very real and well-founded fear.

McKinsey’s influence model, one proven tool for helping to change such mind-sets, emphasizes telling a compelling change story, role modeling by the senior team, building reinforcement mechanisms, and providing employees with the skills to change. While all four of these interventions are important in a transformation, companies must address the change story and reinforcement mechanisms (particularly incentives) at the outset.

An engaging change story. Most companies underestimate the importance of communicating the “why” of a transformation; too often, they assume that a letter from the CEO and a corporate slide pack will secure organizational engagement. But it’s not enough to say “we aren’t making our budget plan” or “we must be more competitive.” Engagement with employees and managers needs to have a context, a vision, and a call to action that will resonate with each person individually. This kind of personalization is what motivates a workforce.

At one agribusiness, for example, someone not known for speaking out stood up at the launch of its transformation program and talked about growing up on a family farm, suffering the consequences of worsening market conditions, and observing his father’s struggle as he had to postpone retirement. The son’s vision was to transform the company’s performance out of a sense of obligation to those who had come before him and a desire to be a strong partner to farmers. The other workers rallied round his story much more than the financially based argument from the CEO.

Incentives. Incentives are especially important in changing behavior. In our experience, traditional incentive plans, with multiple variables and weightings—say, six to ten objectives with average weights of 10 to 15 percent each—are too complicated. In a transformation, the incentive plan should have no more than three objectives, with an outsized payout for outsized performance; the period of transformation, after all, is likely to be one of the most difficult and demanding of any professional career. The usual excuses (such as “our incentive program is already set” or “our people don’t need special incentives to give their best”) should not deter leaders from revisiting this critical reinforcement tool.

Nonmonetary incentives are also vital. One CEO made a point, each week, of writing a short handwritten note to a different employee involved in the transformation effort. This cost nothing but had an almost magical effect on morale. In another company, an employee went far beyond normal expectations to deliver a particularly challenging initiative. The CEO heard about this and gathered a group, including the employee’s wife and two children, for a surprise party. Within 24 hours, the story of this celebration had spread throughout the company.

No going back

Transformations typically degrade rather than visibly fail. Leaders and their employees summon up a huge initial effort; corporate results improve, sometimes dramatically; and those involved pat themselves on the back and declare victory. Then, slowly but surely, the company slips back into its old ways. How many times have frontline managers told us things like “we have undergone three transformations in the last eight years, and each time we were back where we started 18 months later”?

The true test of a transformation, therefore, is what happens when the TO is disbanded and life reverts to a more normal rhythm. What’s critical is that leaders try to bottle the lessons of the transformation as it moves along and to ingrain, within the organization, a repeatable process to deliver better and better results long after it formally ends. This often means, for example, applying the TO meetings’ cadence and robust style to financial reviews, annual budget cycles, even daily performance meetings—the basic routines of the business. It’s no good starting this effort near the end of the program. Embedding the processes and working approaches of the transformation into everyday activities should start much earlier to ensure that the momentum of performance continues to accelerate after the transformation is over.

Companies that create this sort of momentum stand out—so much that we’ve come to view the interlocking processes, skills, and attitudes needed to achieve it as a distinct source of power, one we call an “execution engine.” Organizations with an effective execution engine conspicuously continue to challenge everything, using an independent perspective. They act like investors—all employees treat company money as if it were their own. They ensure that accountability remains in the line, not in a central team or external advisers. Their focus on execution remains relentless even as results improve, and they are always seeking new ways to motivate their employees to keep striving for more. By contrast, companies doomed to fail tend to revert to high-level targets assigned to the line, with a minimal focus on execution or on tapping the energy and ideas of employees. They often lose the talented people responsible for the initial achievements to headhunters or other internal jobs before the processes are ingrained. To avoid this, leaders must take care to retain the enthusiasm, commitment, and focus of these key employees until the execution engine is fully embedded.

Consider the experience of one company that had realized a $4 billion (40 percent) bottom-line improvement over several years. The impetus to “go back to the well” for a new round of improvements, far from being a top-leadership initiative, came out of a series of conversations at performance-review meetings where line leaders had become energized about new opportunities previously considered out of reach. The result was an additional billion dollars of savings over the next year.

Nothing about our approach to transformations is especially novel or complex. It is not a formula reserved for the most able people and companies, but we know from experience that it works only for the most willing. Our key insight is that to achieve a transformational improvement, companies need to raise their ambitions, develop different skills, challenge existing mind-sets, and commit fully to execution. Doing all this can produce extraordinary and sustainable results.

About the author(s)

Michael Bucy is a partner in McKinsey’s Charlotte office; Stephen Hall is a senior partner in the London office; Doug Yakola is a senior partner of McKinsey’s Recovery & Transformation Services group and is based in the Boston office.

Experience Digital by Mike Kent

Mobile ads in 2016: Big data meets the big idea

Aurelie Guerrieri is vice-president of global marketing solutions at Cheetah Ad Platform

Mobile Advertising meets Data Analytics

Mobile advertising has reached a point where big data is beginning to line up with the big idea: native ads and content exquisitely targeted to the mobile user’s data signals, screen and circumstances.

The key to success is a focus on in-app behavioral signals to determine if the user is a candidate to make a mobile purchase, and of what type, and when. But sorting out which of the mobile native’s millions of data signals have the potential to yield the greatest return, then using technology to action that intelligence at scale, is tricky.

The haystacks are large, the needles are few and unique

At the time of writing, there are about 2 billion mobile internet users on the planet. As you can imagine, all that activity produces an enormous amount of data, a lot of it from inside of apps where data signals contain behavioural information of tremendous value to advertisers. The problem is that mobile users generate so much data that it is impossible for anyone to make sense of it all.

For advertisers to get down to what matters in engaging the mobile native, they first need to adopt a less is more approach and commit themselves to concentrating only on the signals that are indicative of what moves me down the path towards a transaction. Let me emphasize the word ‘me’ in the last sentence, because even if 10,000 other women around the world are interested in buying the same Burberry Brit trench coat as me, if you want my business, you’re going to have to find a message and a moment that are just right to get me to buy, not just repurpose a generic ad and drop it on my screen whenever you feel like it.

It takes good quality data to get good results

First-party data is essential – there is zero point attempting to create targeted native content from third-party data with no behavioural value that relies on ‘bucket think’ approaches to segmentation.

It’s also imperative that the data advertisers use is fresh. You don’t want to put someone in a category as a ‘great potential buyer’ based on data that’s old and may not really be indicative of anything about the me of today. So what if I downloaded Candy Crush six months ago? Maybe I downloaded it to entertain one of my kids on a long car trip. Don’t make a mistake of painting me with the label of ‘casual gamer’ just because that fits some easy marketing definition.

Algorithms tend to come in a black box

As I addressed above, marketers have little ability to parse how good somebody else’s data is. In the same vein, it is virtually impossible to know how good another person’s algorithms for targeting or latching are.

A quick analysis of my personal data would reveal I like to play online poker games. Typically, that’s an activity that marketers associate with men. So, if you were using an algorithm to select targets for your new poker app, the technology would probably assume that I’m a man and serve me up an ad with a buxom girl, or colour and font combinations that I’d find garish, to try and get me to download, and that will fail miserably.

There are data verification tools and strategies out there to help brands validate third party data and algorithms, but those solutions are nascent and unproven.

Moments matter, context is king

In order to meet each of these challenges, it’s important for brands that want to succeed in mobile—and in m-commerce in particular—to develop the skills to leverage in-app data. Because, even more importantly than raw behavioural data, in-app data provides the advertiser with the context required to understand my total experience as a mobile native.

I did play a poker app for 25 minutes last night before bedtime. I did open and close the app twice while responding to messages from friends on Facebook, and I did click on an ad for the elusive trench coat that I’m looking for while I was on Facebook. If the advertiser isn’t working from a position of having my fresh, in-app mobile data signals in hand, how would they ever know any of that?

Amazon Prime has the right idea

Recently, Amazon introduced Prime Now, an app that combines shopping, entertainment and everything else all-in-one. Anything that you ever see on Amazon—on desktop, mobile web or in-app—is accessible from Prime Now.

It’s nice that I don’t need to go back to my desktop or another app to shop, but it’s even nicer that I don’t need to make a trip to the store to buy groceries. I don’t even need a shopping list. I just open my Prime Now, drop things in my shopping cart and it’s at my house an hour later. This is a real-life use case of a brand with a heavy stake in the future of m-commerce using a combination of data signals, algorithms and slick native calls to action to make my life better and earn a bit of my money in the process.


The big idea in mobile native advertising boils down to using small parts of user’s mobile data signals to provide calls to action that are delivered at just the right moment, in just the right context, to inspire an m-commerce transaction.

Where before this was just an idea or wishful  thinking, the confluence of trillions of first party in-app data signals, the technology to interpret what they mean, and the commitment to treat each mobile native like the unique individual we are is starting to make advertiser’s big ideas for big data a reality.

Experience Digital by Mike Kent

Why are marketers moving their advertising business in house?

Article from the Drum

Moving advertising in-house


The UK’s leading brand-side marketers are increasingly unhappy with their agencies over their ability to handle the growing demands of cross-screen campaign management, as ad tech issues increasingly occupy their minds, and some even threaten to take their search and CRM acitivities in-house.

Widespread discontent among the ISBA membership was aired recently when the trade body, frequently reffered to as the voice of British advertisers, hosted an event where attendants were encouraged to share both best practices, and concerns, over the growing role of ad tech.

Here the trade body’s members were encouraged to candidly share experiences with peers with those present explaining that some of those present explained they felt “despondent” with their agency’s performance.

Many had expressed an interest in bringing online marketing functions such as search and CRM in-house – a tactic that many industry observers state will help them co-ordinate their campaign activity across screens.

“One of the questions many people where asking is: ‘how do you make it work if you are to bring all of this in-house?’,” recounted one source present.

However, the same meeting also demonstrated that those marketers eager to increase the scale of how they use automated media buying technologies are often hindered by a lack of understanding over the benefit of employing such technologies among their wider organisation.

Simply put, the complexity (including the jargon that has grown up in the sector) as well as the upfront costs associated with of the technology mean advertisers are currently often reluctant to agree to implement the technology.

Paid-for search advertising still counts as the single-largest digital ad unit in the UK, with over £2bn spent on the ad formats in the fist half of this year, according to the latest IAb figures.

The emergence of automated media buying technologies has prompted widespread discussion over whether or not they can equip brands to handle their  media buyingactivity independent of their media agencies.

However, such discussions were also had last decade when search advertising began to form a major part of advertisers’ digital strategy, with long-time industry observers claiming that many of those brands that did so later regretted it.

Experience Digital by Mike Kent

Marketers should be ‘customer experience designers’

The role of a marketer should be redubbed a “customer experience designer”, according to Merlin Entertainment’s group marketing director, Emma Woods, who said the ability to deliver good consumer experiences is even harder in a tech-driven world where things can easily go wrong.

Woods, speaking at Experian’s client summit in London today (30th September), said that the window for delivering customer experiences is narrowing and the correct use of data is ever more important.

“The world of marketing is changing and we have to think about ourselves as customer experience designers,” she said. “Part of that design responsibility is also being guardians for when things go wrong. The second thing is that… in the future your customer data will inform that customer experience and my challenge to marketers is that you have a responsibility to collect it, use it and nurture it.”

A recent step to improve the various customer touch points at Merlin Entertainment – owner of Legoland, Alton Towers and Madame Tussauds – is the release of a new Legoland app which directs visitors to attractions with fewer queues, the nearest restaurant and delivers real-time information about queuing time.

Since its roll out in July Woods, who was brought on board in 2013 to broaden the digital journey of the company’s 55 million guests, said that 15 per cent of visitors have downloaded the app and reported a less stressful experience, particularly on extremely busy days.

“We need to be meticulous about understanding all the customer touch points and thinking about what is the experience that the customer wants and how can we facilitate that through great service or technology?” She added.

Also speaking was Jon Wilkins, executive chairman at Karmarama, who lamented the advent of data companies which he said have caused a “problematic” relationship with creativity, which he likened to a “straight jacket”. He used the example of Netflix-created House of Cards where at a data conference the streaming site’s chief executive Reed Hastings told producer David Fincher that he should consider a data insight for future shows that showed a certain point where viewers switched off.

“His response was ‘never tell me that again’ and that’s a standard discussion between data and creativity,” said Wilkins.

To ease the friction creativity should be “tech driven rather than tech led”, an idea that connects with the role of data and how it can inspire creativity.

Experience Digital by Mike Kent

There is a real need to develop a solution for Personalised Discovery


Personalised Discovery - Can it truly exist?

What do you do when you don’t know what you want to read, watch, listen to or do next? What do you do if you don’t know what to search for? Or can’t describe clearly what you’d be interested in next?

There are so many great choices available in the digital realm, and new stuff is pouring in every second. Many times we feel helpless in front of such an abundance of endless possibilities.

Nevertheless, so far no one has created a solution that would automatically bring all the interesting options to your fingertips without you asking for it. A universal personalized Discovery solution doesn’t exist yet. Why?

Personalized Discovery Today

There have been various attempts and approaches to crack personalized Discovery — at least partially.

StumbleUpon has been around for a while. The app provides content based on selected categories and other “Stumblers” you follow. Flipboard’s personalized magazine has transformed into a social news platform. You personalize your own experience by curating content sources and following people. Pinterest, too, has a follow model for people, their content and topics. Its Guided Search with combinable keywords works as an additional interface alongside the curated feed.

Pocket recently released its Recommended section that provides content based on the things that you saved for later. Google Now delivers useful information based on your previous actions and historical data. And Facebook is just entering the game with its M that supposedly recommends actions and content.

Finding the right dynamics for personalized Discovery could be the key for creating more human-centered and diverse digital experiences for all of us.

Most of today’s Discovery solutions resemble social media’s friendship or follow paradigm. You follow people and their content or you follow selected keywords and categories to personalize your own experience. However, this paradigm tends to reinforce our existing information silos. By directly customizing things for ourselves, our social and personal biases restrict the way we expose ourselves to new information.

Additionally, it becomes hard to estimate how much personalization actually happens automatically and how it helps us in discovering things. The wider the pool of information, the more we have to work to detect the signal from the noise.

At the same time, the user experience of a purely machine-powered approach hasn’t still crossed the “uncanny valley.” A machine telling us what we should be seeing and doing next has a dystopian aura, even in very mundane circumstances. Many times the algorithmic suggestions that don’t directly reflect our social environment or past interactions appear to be too obtrusive or outright ridiculous. Indeed, machine-powered Google Now focuses on delivering useful information instead of new explorative choices.

Discovery currently exists as a category of Internet services and apps, as well as a functional feature in some content-specific platforms (e.g., Spotify and Snapchat). But no one has come up with a universal Discovery paradigm for the mainstream audience.

The Unsolved Discovery Puzzle

There are five main challenges faced by the universal Discovery solution:

Clear Value Proposition And Use Case. Universal Discovery lacks a clearly defined value proposition, and thus a crystal clear use case. Why do you need universal Discovery in the first place? In Search we are looking for specific and relevant answers. In Social we’re connecting and communicating with other people. But how do you define a universal value proposition and use case for something so highly subjective and contextual as Discovery?

People don’t think consciously that they are “discovering” something. They might not even recognize a need for “discovery.” On the contrary, a discovery happens often as a by-product of some other activity.

Frictionless User Experience. Current mainstream user interfaces and experiences haven’t been designed, developed or optimized for Discovery. For example, the news feed and its variations provide a very linear and limited way of presenting information. Personalized Discovery requires a new design approach because finding interesting choices includes potential effort and friction.

Trial and error can form a significant part of the exploration process. Friction emerges when we encounter unexpected choices or when we need to wait for something to happen. Additionally, the experience should proactively pique our curiosity, simultaneously outweighing our personal and social biases.

Technologies For Adaptive Personalization And Content Presentation. Creating a universal Discovery solution brings together two major technological challenges: unobtrusive personalization and sleek content delivery. Adaptive personalization requires an unseen level of automated customization based on our intricate selves. To achieve this, the system needs to be able to capture our meaningful interactions and utilize our diverse personal data.

Current applications of personalization using human curation, algorithmic systems and machine learning methods — or their combinations — don’t yet learn or deliver fast enough, nor do they let us express ourselves as unique individuals. Concurrently, the various forms and types of digital content are messy, and require a lot of sophisticated processing to be presented fluently in various screens and devices.

Accessible Data And Content. The almost infinite sea we call the Internet has become a collection of confined ponds with their own walls and rules. Platforms build their own understanding of you, and usually they don’t let you control how your data could be used for your own benefit in other places.

Simultaneously, an increasing amount of content is becoming platform-exclusive. Major social platforms are becoming content silos, enabling exploration on their own terms and only inside their own boundaries. Media houses are locking their content behind specific access points.

Our social and personal biases restrict the way we expose ourselves to new information.

Discovery Paradox. Additionally, there’s an inherent tension in combining personalization and Discovery. Personalization is about customizing your experience, guiding your choices and serving information based on your needs and personal preferences. Then again, discovery refers to the things that are somehow new and surprising. Indeed, discovery can be as much about questions as it is about answers. It can be as much about irrational and serendipitous as it is about rational and relevant.

The things that you recognize as meaningful discoveries aren’t necessarily what you expect them to be. You might encounter something you didn’t know you wanted or you didn’t even know existed. A discovery can be very personal and context-specific, thus being meaningful only to you.

So, is there a way to overcome this multitude of complex challenges? Or is the universal Discovery solution just a Fata Morgana of the early age of personalization?

How Could Personalized Discovery Work?

A truly smart universal Discovery system makes sense. The amount of information is exploding, and we need better methods to make sense of it. At the same time, the current tools provide only a restricted access to the information that is beyond our personal and social bubbles.

Personalized Discovery can find a balance between relevance and serendipity, as well as rewards and friction, by creating favorable discovery conditions for you as a unique individual. The system understands your articulated and ambient interests by mapping the unique connections you see around you.

A universal Discovery system provides choices instead of the one specific answer. By understanding your interests, the system can expose you to things that you find surprising, even challenging. Simultaneously, it provides meaningful information in easily digestible chunks that let you choose your preferred level of engagement. The presentation is modified based on content form, type and context. To serve content from diverse sources, the Discovery system taps into the free as well as paid content pools on your behalf.

As the amount of potentially discoverable information is almost infinite, human curation and algorithmic methods are used to complement each other. Curation can be made a seamless part of the basic Discovery flow. Your actions curate content for other people and educate the system at the same time. The nuanced human assessment of quality is thus interwoven to the machine-powered dynamics such as prioritizing recommendations and presenting information.

A universal personalized Discovery solution doesn’t exist yet. Why?

In Discovery, goal-driven and casual experiences can coexist. The system brings together various content and action categories such as books, music, movies, travel, food, dating and news. By understanding your preferences with movies and the latest pop culture news — and being able to detect your current mood — the Discovery system recommends new interesting music choices. Also, it can surface interesting weak signals and unseen opportunities. By understanding your daily activities, it can serve a surprising micro-eureka moment when you get trapped in your mundane routines.

Maybe Discovery itself is an ambient system. It’s present and available in the background, only activating when it makes sense to you. Time-consuming complex stuff is hidden under the hood. The system notifies you when something is happening or already waiting for you. Such a Discovery solution is your never-sleeping intelligent extension that doesn’t need continuous actions from your part.

This would be more in tune with our natural experience of discovering new, interesting things almost coincidentally. When digital and physical become more and more entangled, ambient Discovery can be the new user experience paradigm for VR.

However, could any Discovery technology help us to find anything truly new and meaningful if we’re not open to exploration ourselves? Maybe a well-tuned Discovery system could educate us to be more open toward diversity and serendipity. And, potentially, finding the right dynamics for personalized Discovery could be the key for creating more human-centered and diverse digital experiences for all of us.

Experience Digital by Mike Kent

Nescafé lost faith in dotcom; now betting big on Tumblr

Nescafé has consolidated its global portfolio of websites and moved it on to Tumblr, declaring the dotcom is dead as it eyes content collaboration with millennials.

Nescafé betting big on TumblrNescafé lost faith in dotcom; now betting big on Tumblr

The Nestle-owned brand is hoping the move to Tumblr will engage it with a younger demographic and open it up to more user-generated content in a way that the traditional website doesn’t allow for.

The refreshed strategy will see Nescafé move away from traditional social media brand pages and what it has described as their ‘rented relationships’ with consumers. Instead it wants to focus “on creating real life conversations with people.”


tumblr_nuozru5oXJ1uzpzg5o1_1280Speaking to The Drum as the new platform rolled out, Michael Chrisment global head of integrated marketing at Nescafé said the brand is looking to engage in ‘owned media territory’.

“The dotcom is reflection of us talking to people; this approach is dead. It should be much more inclusive and allow conversations,” he said. “[Tumblr] is fostering that possibility to co-create.”

While Nescafé is promising the fully transactional site will serve “as a source of inspiration and connection with suggestions for new coffee creations, multi sensorial flavours, and the coolest coffee experiences”, it’s hoping fans will populate it with their own coffee-related content.

And the options of what form that takes on Tumblr are seemingly endless. From text, photos, quotes, links, music and – thanks to a significant investment from parent company Yahoo – a plethora of video options, the content can all be housed on Nescafé’s page. From there, users can share on other networks or reblog to their own pages within the Tumblr ecosystem.

To build out the proposition, Nescafé is now considering how it will work with Tumblr’s Creators Programme, which launched earlier this year as an in-house agency promising to connect brands with Tumblr artists.

“Because they have a crowd of really creative people, as we look to produce more content more often we will look outside of our traditional partners,” explained Chrisment.

Chrisment is in the minority of marketers currently backing the micro-blogging platform. According to 2013 data, only 31 of the top 100 brands in the US were on Tumblr. Attention for the majority has instead focused on getting to grips with Facebook and Twitter’s ad tools as well as the likes of Instagram and Pinterest; similar in the visual elements but more restricting in the way brands and users interact.

Chrisment admitted that while small in comparison, he was attracted to Tumblr’s growing user base and that it can boast higher organic reach than some other social platforms. According to Tumblr data from 2014, the average post gets reblogged about 14 times while the average sponsored post will be reblogged 10,000 times.

The move will subsequently see a shift in how Nescafe’s marketing budgets are allocated as user-generated content that attracts attention is monitored and further amplified.

“We’re putting owned first and will look at what it takes and how it elevates earned and then promoting it through additional paid media,” he said.

Over the coming year, the learnings from the investment in Tumblr and ‘owned-first’ strategy will be potentially applied to other traditional platforms, including TV, radio, and press.

Experience Digital by Mike Kent
Experience Digital by Mike Kent
Experience Digital by Mike Kent
Experience Digital by Mike Kent