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Remote Working Hints & Tips

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As companies start implementing work from home policies, the key question that emerges is how to do this effectively. Teams that are used to face to face contact and meetings need to be taught new ways of working together to maintain effectiveness.

The good news is that work from home can often lead to an increase in productivity once these ways of working are mastered.

Through DYDX’s experience with working with companies across Europe and Africa on “future of work” and building team behaviours to support digitisation, there are a range of tips we can share.

The most important one is taking some time to set up new working agreements. This may seem arbitrary but changing how you work requires new agreements between people working together, to avoid unnecessary frustration and communication breakdowns. This is because a physical space provides a lot of social and spatial queues that we don’t have in virtual spaces or in remote working.

Nevo Hadas, Partner at DYDX, unpacks key areas that if not implemented successfully will lead to breakdowns.  The opportunity is for the team to discuss and agree, thereby improving teamwork while remote:


  1. Immediacy:  you are used to walking up to somebody to get an answer and now you sent them a message or an email and … nothing. Reaching an agreement regarding how long people will take to respond before you escalate and how to deal with urgent requests helps clear up a lot of frustration in the team.
  2. Shared Schedules:  just because you can’t see people being busy doesn’t mean they aren’t. Team members should be good at sharing calendars of when they are at meetings or working on a document/project and should not be disturbed or won’t respond. This helps everyone understand what availability is. This also means that you should check a member’s calendar before calling them, if it’s urgent, send them a message and wait for a response.
  3. Economise your time: You will have a lot more calls now that you are remote, but not everything needs to be one hour. Think about the meeting structures and agendas carefully and allocate shorter periods of time. You would be surprised what can be achieved in 15/20 minutes of focused conversation.
  4. Agree on working hours. While there is the legislated time of work but that does not convert as effectively into virtual work as you would think. Now that you don’t have to commute, don’t use that time instinctively for working or sleeping.  Develop a routine to use that time effectively, either exercising, reading or online study. While we may think that having calls/meetings for more hours is increasing productivity it’s actually not, there is a limit to how long you are effective in these mediums. Allocate time for deep-work (i.e. don’t disturb) versus meetings if possible.

Work from home

Video/Voice Call etiquette and format

Video or voice call etiquette is a real thing.  These elements always trip people up:

  1. Share the call location (i.e. dial-in number/links etc) on the meeting request
  2. Prepare the platform. If you don’t have the right software, download it before the meeting starts (see the tech section for more on that.)
  3. Have a good headset that is either plugged into your laptop or phone.
  4. Be in a quiet space.
  5. Mute when you aren’t speaking. Background noises can be very distracting.
  6. Have a clear agenda (just like a physical meeting).
  7. Use video if you have the bandwidth or at least for a couple of minutes to say hi, there is nothing wrong with doing voice only.
  8. Decide a meeting cut-off time i.e. if you haven’t joined the meeting in 10min, please don’t join late.
  9. Not all calls have to follow the same format. You can choose or create a variety of call formats that will increase productivity for the type of meeting. i.e. a decision-making forum could use individual voting (many online tools have this) and then a discussion.
  10. Checkin/checkout – what is done visually after a meeting by looking for discomfort in attendees needs to be done more consciously in virtual meetings. Take the time to ensure that everyone is on board by checking-in when closing a meeting.
  11. Distractions are a real challenge on calls and it is easy to lose people’s attention in key moments. Etiquette agreements can make this clear i.e. don’t respond to your emails while in the meeting.
  12. Having fun is still important. Create channels and spaces where people can share silly gifs or other jokes. Allow people to still enjoy communication but also agree on how to bring it back to the topic.

Sharing Information

How will you share information and progress, is there a common folder everyone can work in, is there a directory structure? While these are obvious to many people the need to have a common space that you can use increases with remote working.

Personal workspace

Take breaks throughout the day and recognise them as breaks, the fear is people will think you are slacking off but very few people actually work non-stop for 8 hours a day. Grab a coffee, take a walk, chat to a friend.

Different zones in the house may be useful, i.e. morning versus afternoon spaces, as long as they are quiet with low background noise or conference calls become a nightmare.


Choose tools that work for your teams i.e. don’t let IT dictate things that just don’t function for you. Experiment with different tools before deciding. Agree on the tools you will use and make sure everyone has them and knows how they work. If you have people who are new to remote working, dedicate some time to onboard them into how the new tools work. It only takes a few minutes but saves a lot of frustration.

Collaboration tools provide a new way of working together. Everything from slides to diagrams can now be done using these tools. You may find that you need more than one tool depending on what you are doing.

Here is our list of tools, though it may not be right for you:

  1. G-Suite (Google) – this is our basic workspace i.e. slides, docs, sheets (excel), storage, email all live here and allow us to collaborate on work done.
  2. Slack – this is our communication space. We have channels per project where teams discuss issues and share document links (the documents live in G-Suite)
  3. Asana – task management to ensure people are on track. Each person can update their own tasks which is a big plus and reduces unnecessary status calls and stand-ups.
  4. Lucid-chart – this is what we use for diagramming complex flows for designing working processes
  5. Pipefy – this is what we use for expense and invoice management and it is integrated with
  6. Xero – which we use for accounting.
  7. Zoom/Hangouts/Slack – is what we use for calls, but varying call quality may make us switch from time to time.


Even if you are highly experienced in working remotely, the practice of experimenting with new ways of working can improve your effectiveness and overall experience. Experiments don’t need to be anything big (e.g. today we will try a quick check-in before starting or a check-out at finishing), but do introduce some novelty and re-engage your team, it provides an active learning mindset that can build a team’s cohesiveness.

The most important factor for remote teams to be effective is not the productivity tools they choose, nor is it how smart they are. The most important factor for success in distributed teams is a common set of behaviours – an agreed team culture. Backed-up by research, our own experiences with global clients, and common sense, along with the Dutch government, we created the Culture Canvas: Making culture actionable to help you shape your team’s culture.

We have also created a 10-minute “Remote Team Maturity” assessment designed to benchmark remote working capabilities and quantify team effectiveness, and a free ebook, – Remote Team Management, where we provide recipes and formulas on creating an effective Team Working Agreement with your remote team.

You can find it and download the free eBook here.

Why Nick Cave knows more about AI than futurists do

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Yuval Harrari, in his book 21 Lessons for the 21st Century, speaks about an AI knowing us so well, that it knows how to write the perfect song for us to enhance or change our mood. While the science and technology sound intriguing and potentially possible, the very idea of it seems to miss the point of what music is about.

We love songs for the stories they convey, but the stories are often subtle and filled with social cues that go beyond melody and harmony. The story of the artist imbues a song with depth, a song about heartbreak can fill us with even more compassion as we hear the artist’s story writing the song versus just the lyrics. Think of “Dance Me to the End of Love” by Leonard Cohen; it’s a beautiful song made more beautiful by its story of his decades-long love affair with Marianne Ihlen.

Songs are also not solitary or personalised (other than maybe for the artist). It is about a shared experience of the human condition. Other fans provide us with a sense of belonging, sharing music we love with friends makes us feel more connected. Personally, I love it when my kids go to see the Pixies, which is my favorite band. It brings us closer together versus each having our own set of music that is personalised to the point that it has no common meaning.

Nobody says this better than Nick Cave in his response to the question by a fan. Could an AI have written “Smells like Teen Spirit”? Maybe… could it have had the same tragic delivery, frustration and ultimate suicide that give the song its meaning beyond the chords? No. We confuse the aesthetic with the outcome – but that’s not how humans work.

Read his letter below, it’s well worth it:

Nick Cave, answering a Slovenian fan’s question: ‘Considering human imagination the last piece of wilderness, do you think AI will ever be able to write a good song?’

Dear Peter,

In Yuval Noah Harari’s new book 21 Lessons for the 21st Century, he writes that Artificial Intelligence, with its limitless potential and connectedness, will ultimately render many humans redundant in the workplace. This sounds entirely feasible. However, he goes on to say that AI will be able to write better songs than humans can. He says, and excuse my simplistic summation, that we listen to songs to make us feel certain things and that in the future AI will simply be able to map the individual mind and create songs tailored exclusively to our own particular mental algorithms, that can make us feel, with far more intensity and precision, whatever it is we want to feel. If we are feeling sad and want to feel happy we simply listen to our bespoke AI happy song and the job will be done.

But, I am not sure that this is all songs do. Of course, we go to songs to make us feel something — happy, sad, sexy, homesick, excited or whatever — but this is not all a song does. What a great song makes us feel is a sense of awe. There is a reason for this. A sense of awe is almost exclusively predicated on our limitations as human beings. It is entirely to do with our audacity as humans to reach beyond our potential.

It is perfectly conceivable that AI could produce a song as good as Nirvana’s “Smells Like Teen Spirit,” for example, and that it ticked all the boxes required to make us feel what a song like that should make us feel — in this case, excited and rebellious, let’s say. It is also feasible that AI could produce a song that makes us feel these same feelings, but more intensely than any human songwriter could do.

But, I don’t feel that when we listen to “Smells Like Teen Spirit” it is only the song that we are listening to. It feels to me, that what we are actually listening to is a withdrawn and alienated young man’s journey out of the small American town of Aberdeen — a young man who by any measure was a walking bundle of dysfunction and human limitation — a young man who had the temerity to howl his particular pain into a microphone and in doing so, by way of the heavens, reach into the hearts of a generation.

We are also listening to Iggy Pop walk across his audience’s hands and smear himself in peanut butter whilst singing 1970. We are listening to Beethoven compose the Ninth Symphony while almost totally deaf. We are listening to Prince, that tiny cluster of purple atoms, singing in the pouring rain at the Super Bowl and blowing everyone’s minds. We are listening to Nina Simone stuff all her rage and disappointment into the most tender of love songs. We are listening to Paganini continue to play his Stradivarius as the strings snapped. We are listening to Jimi Hendrix kneel and set fire to his own instrument.

What we are actually listening to is human limitation and the audacity to transcend it. Artificial Intelligence, for all its unlimited potential, simply doesn’t have this capacity. How could it? And this is the essence of transcendence. If we have limitless potential then what is there to transcend? And therefore what is the purpose of the imagination at all. Music has the ability to touch the celestial sphere with the tips of its fingers and the awe and wonder we feel is in the desperate temerity of the reach, not just the outcome. Where is the transcendent splendour in unlimited potential? So to answer your question, Peter, AI would have the capacity to write a good song, but not a great one. It lacks the nerve.

Love, Nick

By Nevo Hadas – Nevo is the Founding Partner of DYDX

When Good Culture Becomes Bad

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In 1997’s Boston Macworld, Steve Jobs was BOOed by Mac enthusiasts. 

He had just come back to save the company he loved and told the audience about the adoption of IE as the default browser. The crowd hissed and booed and Steve Jobs broke into an impromptu sermon: “If we want to move forward and see Apple healthy and prospering again, we have to let go of a few things here. We have to let go of this notion that for Apple to win Microsoft has to lose. OK? We have to embrace a notion that for Apple to win Apple has to do a really good job, and if others are going to help us, that’s great, cause we need all the help we can get. And if we screw up and we don’t do a good job, it’s not somebody else’s fault. It’s our fault. So, I think that’s a very important perspective.”

Do not doubt that Jobs had created the culture which led to his booing by building the mythology of apple being better than the rest during his time leading Mac. He needed to shift the companies mindset away from doing it alone to partnering and encompassing others to be successful.

“Culture in many ways define a company’s response to reality because it becomes the unspoken filter through which all information is processed.”

Microsoft under Balmer failed to shift from their bold strategy of “a computer on every desktop” when smartphones came about. Doubling down on a windows centric strategy was Balmer’s downfall and it happened because the company could not accept the change in reality.

That’s the trap of culture, you can’t see your own blindspots because your mental model doesn’t allow them in. We often espouse “culture east strategy for breakfast” but in truth, culture is often an outcome of success. It becomes ingrained because it delivers/delivered results. It is the companies greatest asset until, one day, it’s the biggest liability. The problem is the stronger the culture the less likely you are to see that switch coming.

This becomes ingrained in behavior; the pride that people have in doing a task really well stops them from seeing when the world has changed. And that by doing that task, a digital environment is destroying value for their customer and not creating it (like it used to). This transition happens so quickly, that their key defense is to create elaborate processes to recreate a manual set of tasks that should be eradicated. “What will our people do” trumps “how do we do a great job faster for our customers”.

This is where the role of a leader is so critical; to be brave enough to change the culture by, like Steve Jobs, changing underlying beliefs that everyone has about themselves and fundamentally, what they do to create value.

By Nevo Hadas – Nevo is the founding partner of DYDX and has led the development of “The Culture Canvas”—an open-source framework that makes work culture actionable for businesses to shape their team’s behaviours—as well as the latest ebook “ – Remote Team Management”, which is available for free download, and the 10-minute “Remote Team Maturity” assessment tool designed to help companies measure the effectiveness of their remote teams. 

The obesity epidemic caused by the low-fat era

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In the 90’s the US government proclaimed that unsaturated fat was what made people gain weight. The low-fat category, packed with sugar-laden treats, was launched to help dieters looking for a healthy snack.

All of the research led to a greater variety of low-fat foods being needed because consumers wanted to eat healthy, easily and lose weight. The key underlying assumption was wrong, but everyone took it for granted as a fact. The spiral of research was only looking for answers within the bias i.e. every problem that came up (people are gaining weight) was looked at against the solution of — make more sugary low-fat foods.

A less obvious element, however, is the impact on the entire field of dieting. Diets became hard (or harder). You were eating the right low-fat foods but getting fatter. People became demotivated, the concept of “easy fix” was touted even more, before you know it you have a multi-billion dollar industry that is doing exactly the opposite of what it wasn’t meant to do.

This is the bubble that assumptions cause, they blinker you to the proof around you as you strive forward, researching based on your assumptions versus the outcomes of your actions.

Pragmatically, this doesn’t mean that going against the grain would have been useful. To sell high-fat, low-sugar (which is what occurs today) you need a broader system of belief that supports your product can build on. It does raise the question of what you aren’t asking or taking for granted. What are you assuming to be a given because that is your context that may actually not be true?

For us this came up in a recent study looking at improving the medical care experience for a new healthcare company, SUSU, launching in France & West Africa. The service focuses on delivering better care for patients by improving their medical experience and structuring their treatments more effectively.

One of the common themes was that doctors visits were generally avoided as they were difficult, making treatment more complicated when they did finally occur. On mapping the experience in-country we could see how much friction around payments and general appointment management existed for patients.

Our biased assumption was that western style appointments would work and that arriving at a clinic and waiting for a whole day at the doctor was unnecessary (which is what the current experience is). However, when we dug under the surface we found that many patients found the idea of scheduling an appointment complex and undesirable. In an environment where getting across the city can be complicated (irregular public transport, no consistent street addresses, bad traffic etc) making an appointment that you (or the people before you) may miss is frustrating, as you will just end up waiting anyway. Not making an appointment and arriving to wait your turn seems easier and less stressful.

Just like low-fat diets, we assume the scheduled event is better because that is what we know and have been told. Appointments assume that everyone in the system keeps to them or they fail quickly. Solving the problem becomes choosing between a systemic design challenge (change everyone’s behavior), a transactional design challenge (change behavior just for our clients) or a situational design challenge(change the situation for our clients). Our guiding principle at SUSU is care — which means our solutions were to make the process as comfortable and efficient for the customers as possible.

While we have opted for a situational solution as the best initial approach, the key component is putting in place the benchmarks that test not only the positive feedback i.e. was this a “better” experience, but the actual outcome of the system by looking at the number of doctors visits and attendance. Real metrics that point to success or failure of a solution vs assumptions (number of appointments made).

Uncomfortable in Uncertainty

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There is a useful model that breaks knowledge into:

  • what we know
  • what we know we dont know and
  • what we don’t know we don’t know.

It’s a great reminder of uncertainty and our lack of awareness of all the issues in the problem we are trying to solve, especially in bigger systems. Why is this important? because the most critical part of solving a problem is asking the right question, and to ask “the” right question you need to ask lots  and lots of questions. By answering lots of questions you expand the “what you know you know” and the “what you know you dont know”.

Answers mirror the questions they rise, or fall, to meet

Our business cultures are focused on quick results, quick answers, but sometimes slow is better if it creates a 10x better outcome. By slow I don’t mean “thinking” or “brainstorming” or analyses paralysis , but a systemic process using multiple mental models and research tools that expose different facets of a problem… That make you ask better quality questions.

There are too few workshops discussing what the right question is, and too many workshops glibly power-pointing the same answer that you gave a client last week.

By Nevo Hadas – Nevo is the founding partner of DYDX and has led the development of “The Culture Canvas”—an open-source framework that makes work culture actionable for businesses to shape their team’s behaviours—as well as the latest ebook “ – Remote Team Management”, which is available for free download, and the 10-minute “Remote Team Maturity” assessment tool designed to help companies measure the effectiveness of their remote teams. 

First to Market Myth

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We’ve been unseasonably busy with two new fintech projects and two new media projects for very different markets happening at the same time.

The fintech projects could be disruptive, while the media projects would be exponential opportunities for our client. Neither are first to market, which is a big plus … because very few first to market (and I struggle to think of any) really end up the winners in a disruptive industry or are necessary in an exponential one (actually second or third is best).

There is an interesting distinction in the type of business model you adopt between “disruptive” (which for the sake of cynicism we will re-phrase as demand-side expansion at price points that traditional sector competitors cannot sustainably meet) and exponential (new customers and new revenue opportunities from existing customers) products.

The big difference is the business model… no, not the customer experience (I can already feel the heat from the burning torches, shouts of the mob and threatening glints of the pitchforks waving in the air)  … the underlying way you generate value must be priced differently to unlock a market that previously could either not access these services due to distribution OR increase demand by making it cheaper.

Here are some examples: 

Google – Google was not the first search engine, it was probably the 50th. All it did was do less, faster and appear to do it better (initially, this could have been debated). The cost per click model (which they “borrowed” from another competitor) was what made them so disruptive. Instead of paying for ads served, you paid for clicks delivered and it was an auction (genius). The self service component meant you could place the ads yourself and many small businesses that struggled to afford advertising before, plus large businesses that understood the benefits of paying for clicks vs impressions were on board. Print ads suddenly looked ridiculously expensive and unfairly priced.

Uber – nope, not the first call-a-car service. Initially it was aimed at high-end hotels and car services and “borrowed” the low cost model from Lyft…but they made it really easy to become a driver and opened up the market for “non-licensed” cabs to be added to the service at a lower cost of operation for the cab, which meant a lower price per mile, which meant more customers would use the service. Yes, it’s a great experience… but a great experience at double the cost doesn’t mean disruption and massive consumer adoption.

A great experience with a real price benefit to consumers that existing companies struggle to meet due to their cost base – that’s all kinds of sexy. It means you get existing customers and attract new ones. This leads to a “disruption” as the entire value chain gets up-ended with both new suppliers and customers at a new price point.

By Nevo Hadas – Nevo is the Founding Partner of &Innovation, now DYDX

Taxi sign

Pricing, NOT pretty design, drives digital disruption

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Price*, is the key part of a great experience and fundamental to Customer Experience (though hardly ever part of the design phase). It also indicates a fundamental shift in the underlying business model, especially when the price point shifts significantly for the good/service due to a digital channel being adopted.

At its core, digital disruption is caused by the resetting of price due to a change in distribution models as the customer’s point of purchase evolves.

In economics talk:

Price changes are led by an increase in supply (which has been pent up with no access to market) due to a rapid increase in distribution options without a rent seeking gatekeeper (oligopoly/monopoly), restricting access to the market. The supply side increase pushes down the price to the demand side, creating a groundswell of support for the new distribution channel and increasing demand beyond the new supply levels. Demand, once increased, in turn promotes additional supply often at a lower cost. After a few years the new distribution model benefits from a network effect and gains traction. It attracts significant external capital at a low cost to build a momentum moat. The rest, as they say, is a post-modern rags-to-riches overnight success story of ivy league drop-outs.

Shorter distribution lines = lower price to customer at same margin

From an Economics 101 perspective, it’s a little bit backward, as high prices should attract more suppliers and low prices reduce suppliers into a market. Digital disruption fundamentally changes this assumption due to the lower cost base enjoyed by new entrants, due to newer technologies and reduced distribution channels which reduces the price to the customer. The new supplier’s marginal profit and Return On Equity (ROE) is equivalent or higher than the incumbents, at a lower price point.

Before you leave a comment in BOLD saying that better CX through customer centricity and systems thinking is the reason for this – I agree with you. The disruptors come into the market focusing on the customer and building a ground up experience based on today’s points of purchase and new pricing ,while the incumbents are stuck supporting the old distribution.

When your channel is more important than your customer…

I know this sounds either bizarre or obvious, but many incumbents spend more management time on their channel to market than their products. The channel is where the margin sits and where power comes from – it’s their competitive advantage. This distribution focused myopia leads to good decisions (i.e. focus on the ‘fat middle” of your customer base) killing you over time, because the market you see is the market you have created. You cannot see the size of the outside edges of your customer distribution curve.

False quality signals

Incumbents often limit access to their channels using a “quality” argument. This quality is either legislated, supplier power driven or decided by management. The decisions are focused on the “core customer”, which are often the later adopters or the market segment most serviced by the current offering. It is hard to innovate when you cannot see the problem and have investors screaming for margin improvement.

Walmart, with its “fast, faster, fastest” delivery option is a clear case in this. A complicated offering driven by their internal distribution model limitations rather than trying to build a product for the customer.

Why do incumbents die while their industries boom when they are filled with smart, capable executives?

Some basic examples:

  • Music – there is more music being made today then ever before, and more consumed, and more musicians – but music labels died because they were invested in physical production of music
  • Movie rental?  Blockbuster vs Netflix (selection and long tail vs latest releases focus, physical location & complex late fee structures)
  • Bookstores – remember those? Though Kindle is the real disruptor versus just buying books online (that impact is still coming)
  • Investment Management – financial services industry made up of middlemen is beginning to get a fright. Nutmeg, Motif and a number of other low cost investment managers are gaining traction.
  • Travel was disrupted ages ago (who really uses a travel agent?) but its continuing with accommodation (Airbnb) and transport (Uber/Driverless) as this segment continues to change.

These are industries that are booming, but the traditional middlemen/aggregators are dying, died or starting to have some significant health concerns.

The maths is on the side of the disruptors

A successful digital disruption occurs when there is sufficient momentum in these new distribution models that less than 2% of industry spend moves into these new channels (Google, Amazon, Netflix, Uber, Transferwise, AirBnB all became market disruptors at a fraction of market share, getting free PR that further fuelled their growth). While the percentage may seem small, it is enough to create a significant competitive force in any sizeable market. Disruptors attract far cheaper capital than incumbents, giving them an incentive to grow and no fear of destroying established value.

What is also interesting is that this 2% may not have been traditionally served market by the industry i.e. unmet demand or customers with unique (but trending) usage patterns. AirBnB is a great example of this, as was Amazon, Netflix, Spotify etc..

Does my middle look fat in these jeans?

This is where the focus on the fat middle can really impact incumbents, as they are focusing on a limited audience view led by the products they sell, the channel that they have etc. versus a larger market opportunity – which they literally cannot see from where they are.

Who is prone to digital disruption?

Large industries with convoluted value chains based on distribution, versus the quality of the end product are most at risk. At its core, the internet has changed a couple of fundamental elements:

  1. the product/service is now delivered digitally – this means that different things are good/bad in its design versus previous models of product/service delivery.
  2. high margin value chains:- where there is a lot more money in the value chain versus in the creation of the product/service, keep an eye out for disruption
  3. legislative barriers to entry i.e. restrict competition to manage “quality” – i could write a novella on the myth of legislated quality, but I won’t. These industries have often become legislated to keep competitors out rather than make customers happy.

What do you do as an incumbent?

Transformation is often undertaken as an inward gazing exercise, which is not a terrible approach, especially if you can impact your price point and distribution chain… but a more challenging approach is to find the edges of your customer base and start building products that will meet their need. It’s a very hard ROI discussion to have, and I have personally killed a number of these projects when i was on the side of the incumbent figuring out transformation strategies – so i think the complexity of doing this is under-rated.  Even if you kill the projects at the end, looking at new customers is highly valuable as it gives you ideas into what is coming, versus focusing only on what you have.

Enough rambling from me. Always curious as to what other people think, so please share your thoughts…

*Price does not mean cheap, price speaks to the magic mix between perception and quality that creates “value” in a consumers mind.

By Nevo Hadas – Nevo is the Founding Partner of &Innovation, now DYDX

Rethinking Loyalty & Rewards – elitism vs democratization

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Rewards are easy to promise but hard to deliver because of the emotional resonance of wanting to feel rewarded. While retailers see it as a discount, from a consumer perspective, whatever you got isn’t really enough. Loyalty is even more emotionally complicated. In a recent US survey, 73% of consumers thought that loyalty programs meant that the brand is loyal to them, while 66% of brands thought it meant the customer was loyal to them.

Digital transformation hasn’t changed most loyalty programs much. New behavioral metrics from IoT and increased digitization have been used to apply the same logic but in a more complicated way because it is easier to collect and manage. i.e. more points, more levels, and more frustration.

“You cant get there from here” – Saying from Maine, USA

The shining light in rethinking loyalty is Amazon prime which has chosen simplification over gamification to deliver over 100 million subscribers paying $99 each per year. Prime members spend close to 3 times what non-prime members do and are growing at a rate between 35% to 40% per annum as estimated by Citi. Prime users do not experience emotional satisfaction.

The Amazon insight:- Shipping costs frustrate customers and reduce transactions. If customers pre-pay for a shipping service, their loss aversion to losing the value of their investment will reduce their interest in shopping around and increase their overall spend.

The ease of execution and ability of customers to join makes complex points and levels look like a 1990s solution to a 2020 problem. The program is inherently egalitarian i.e. to be a prime member you just have to pay.

“what i love about coca-cola is that even the president cannot buy a better coke than” – Andy Warhol

Gamification of loyalty programs through points and levels is rapidly losing its allure. This doesn’t mean that customers are any less loyal or more prone to shopping around but rather that the idea of being awarded points for being a “good” customer is getting harder to justify. Loyalty programs have changing rules, cut off times, points expire etc etc etc. They are expensive to maintain needing not only to manage a mountain of potential liability sitting on balance sheets but also a lot of administration to maintain accurate balances, partnership, provide client care and of course, handle complaints.

If airlines adopted Amazon’s model — they would arguably improve their margins and the effectiveness of their programs. Frequent travelers would pay a cash amount in advance for a year’s worth of benefits, discounts, lounge access etc. Even regular business travelers, who current schemes are targeted at, or companies would purchase perks for in return for lower cost flights or just to look after key executives.

Irregular travelers, who are not budget constrained, would continue to buy business class seats which come bundled with all the perks or add on their preferred perks to their low-cost flight (e.g. choosing seats at a premium, business lounge access, arrivals lounge access etc). While most people claim that “free flights” are the reason they want airmiles — very few who have tried to claim their miles have actually had an experience that grows their loyalty versus disappointed them. Rewards are easy to promise but hard to deliver because of the emotional expectation that comes with wanting to feel rewarded.

The lessons from Amazon are:

  1. Changing our perspective by providing preferential experiences at a price versus as an earned status.
  2. Not seeing digital channels as a way to streamline historic complexity (i.e. make collecting points and managing loyalty systems easier) but rather as a way of democratizing valuable experiences and creating new value points
  3. Understanding the low points or friction within your process and turning that into a new product opportunity

By Nevo Hadas – Nevo is the Founding Partner of &Innovation, now DYDX


Are you thinking about pricing incorrectly?

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Renowned investor Warren Buffett has said, “The single most important decision in evaluating a business is pricing power. If you’ve got the power to raise prices without losing business to a competitor, you’ve got a very good business. And if you have to have a prayer session before raising the price by 10%, then you’ve got a terrible business.” 

This sage advice from a man far smarter than 99% of us – may turn out not to be completely right.

Old School Pricing Theory

Pricing theory tried its best to explain large market behavior. Demand elasticity was touted as the answer to price setting, and, in a pre-computer world when it was developed, held some truth. Digital transformation has obliterated this theory and many pricing models build with it as a logical foundation. This means that the idea of a single price is no longer as relevant as it was.

With the advent of online price comparison you would think that the lowest, simplest price would win, in fact – in many instances, prices are more obfuscated by digital transformation than simplified and pricing simplicity does not increase the chance of conversion.

Dynamic pricing is the the next problem, not the next solution

Digital channels allow businesses to price dynamically based on a variety of factors. Value is not just based on utility, brand or comparative cost benefits of a product – it is a range of factors, many of which are external to the product, which can now be dynamically applied to personalize price. This both increases yield and expands the addressable customer segments.

The challenge is not the technology or understanding the concept of personalisation, but developing robust pricing models and the depth of thinking that enables new pricing variables to be created.

Don’t think in a line

When you stop thinking of price as the economic demand/supply curve but rather as a matrix, your entire approach to product design and pricing strategy changes. You are no longer looking for an elasticity curve to best fit your product but rather looking for a pricing strategy that maximizes revenue (and hopefully profitability) over a given time period. A pricing matrix allows you to look at price points in clusters which, inevitably, increases your price/revenue opportunities.

While revenue management is not a new concept (hotels and airlines have been doing it for years), it is often overlooked in many other industries and the role of methodically testing different pricing assumptions is ignored in favor of meeting a customer need. The best example of demand driven revenue management at the moment is by google, who mix demand based auctions and quality scores to ensure they not only push up price via bids, but also maximize revenue by rewarding ads that are clicked on more.

Product managers, in a desperation to have their product adopted, often prefer to have simpler, lower prices. This doesn’t make these pricing models correct – it makes them common and easy to execute.

How to Think About Price

As a childish rebellion against the need to create fancy, complex charts – the sandwich chart is a nice simple view of different layers of pricing. While not as comprehensive as a full matrix.. it highlights some of the key aspects that need to be put into consideration

Some examples of what these items mean:

Affordability vs Price

Affordability of a product is more important than price in many instances.

When South African mobile operator MTN- one of the largest operators globally, initially launching and expecting around 250 000 post-paid monthly subscribers as its total market.

Then they had a revolutionary ides – to do away with the monthly pricing model. To let consumers (generally lower income) pre-pay for usage as they need it. Not only could they charge much more per minute/per MB etc as a pre-paid customer, but the operator isn’t required you to give you credit (i.e. take risk) and gets upfront cashflow. It was a genius pricing insight, a customer segment will pay a premium to be given smaller increments. It also added around 200 million subscribers to their business and unlocked developing markets for all operators as it gained adoption.

The next idea was expiring the airtime i.e. if you don’t use it, you lose it . This created a new pricing variable – 1 day pricing vs 30 day pricing. The genius of this model is it creates comparative decision points based on when you will use your minute and obfuscate the value of the actual minute i.e. the cost per call. It creates multiple points of value for the same minute (which in itself is a pricing point and in no way linked to how mobile technology cost structures really work).

Inducing Purchase

A recent study by Ali-Baba showed a 114% increase in conversion once special offers were provided after an abandoned cart. When we look at pricing purely as a retail price point versus a sequence of pricing including discounting as part of our strategy, we miss a key component of the matrix. How do we overcome fear or plug into greed in such a way that the consumer is convinced the price is too good to miss right now.

In the MIT paper “ markdowns versus everyday low prices”, the authors show the impact of behavioral economics on price perception, specifically fear and that consumer behavior is orientated towards” buying a deal” versus everyday low prices. In other words, emotional inducements are a powerful contributor in the pricing strategy – making pricing intrinsically illogical from a consumer perspective. Humans, prefer to “hunt” a deal than always pay a lower price.

Maximizing Value

You can test value/price before launching a product .Often, we see prices test well that don’t make sense. A specific pricing peak where we find higher conversion rates, these prices are usually not the cheapest nor are they based on specific rationality/logic other than a consumers value judgement on the right price for a product (i.e. too cheap/too expensive). Sometimes, the same product has two pricing peaks i.e. there is distinct interest for the same product in two different price segments and you need to choose how you will differentiate for the different pricing opportunities.

In a number of research studies we have seen that consumers have a weak link between what something costs them and what the price is -i.e. consumers latch on to a single number as “the price” but don’t understand the total cost of the transaction. This is prevalent in a number of industries like forex/low cost airlines/insurance/banking/investments/car rental/telecoms .

The industries that maximize value well are often finding ways of linking the value of your product to an external element that pushes up the value of your offer when it is used e.g. % of revenue (credit cards) or exchange rates (forex).

By Nevo Hadas – Nevo is the Founding Partner of &Innovation, now DYDX

Man on a horse

Don’t compete with the Price Point  … Compete with the Pricing Models

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In a world of competitive products and services, competing directly or as substitutes to solve a customers problem, the ones which become clear winners have differentiated how they price and not their price point. These clear winners gain rapid commercial success especially in saturated markets with limited product differentiation e.g. basecamp, slack, iTunes, Dropbox, Amazon Web Services, Netflix, Discovery, Outsurance are all examples of success stories that leveraged a different pricing model to stand out in the market and deal with a key pricing factor — FEAR.

“Slack’s genius was getting around the long buying cycles of enterprise software, which made it the fastest growing enterprise software business in history.”

We all make the same mistake. Your amazing product seems unique to you with blindingly obvious benefits in the marketplace over its competitors. Customers should be flocking, elated, and paying you a premium … or even a discount to competitors. However, to your customers, it is just another substitute to a problem they are currently solving or a scary new thing to try. Both have an emotional risk associated with making a bad decision that can feel much higher than the sales price.

The launching a new service/product it is often tempting to use the competitor price as an anchor and price around that i.e. higher or lower based on perceived quality. The truly disruptive businesses change the pricing paradigm to make comparison difficult. They obfuscate the price by either breaking it down into non-comparative components (e.g. AWS) by focusing not only on benefits but also on fears and purchase hurdles. This is more significant than providing a discount or low-cost trial as it sets up the company to earn larger profits over time.

Take slack for example. Is it cheap compared to other products? — not really. Slack’s genius was getting around the long buying cycles of enterprise software which made it the fastest growing enterprise software business in history.

Slack knew that their product would have traction with small dev teams. Once it caught on in a team the trick was to move from a free to use model to a paid for use model. The biggest hurdle is to combat complex purchasing processes within enterprises. So slack adopted a simple pay as you use model versus an upfront licensing model or tiered licensing model. Furthermore, because you pay based on the previous months users, if the users were inactive during the month you get a credit against your next bill. This level of transparency circumvents the complex negotiations with corporate. Furthermore, it encourages corporates to use the product more because it eliminates the complexity of licensing tiers.

Why is this disruptive? It took into consideration not only the physical cost of the product but also the emotional/political cost of the product, making it easy to buy (i.e. no business case or change management program or integration plan or political capital needed) and reducing the fear of unused licenses based on purchasing in tiers of licenses in advance.

Another method (now considered a norm) of dealing with user fear was to zero price limited functionality i.e. freemium and it was a breakthrough model when introduced by basecamp in the early 2000s and still highly successful today. This pricing model unlocked a massive amount of both latent demand that then current pricing models of software providers couldn’t accommodate (ie low monthly cost) AND shifted spend away from small custom built software solutions that companies had previously used. While it is cheap on a monthly basis, over the long term — you may spend more money on a cloud-based solution than the one you would have purchased and sweated for 3–5 years.

Dropbox gave you a free storage the more you shared their product and massively increased their user base which they converted into sales. Hotmail gave you a free email in return for advertising (vs the one you got with your ISP subscription or at work). Netflix, gives you a free month to try it out with no upfront cost or installation and no long-term contract (unlike cable or satellite TV). Amazon Web Services charged for computing power and features based on usage (which was a massive shift from building a server room). Discovery (medical aid company) reduces the cost of your insurance depending on your health level by keeping track of your exercise routines and promoting a healthy lifestyle. Outsurance rewards you for not claiming on your insurance by giving you back your premiums after 5 years.

All of these companies priced completely differently from their competitors and not only switched but retained their customer base and recreated the industries in which they compete.