Only Dead Fish

The Rise of Zero-Based Budgeting

Zero-based budgeting feels like one of those trends that is potentially pretty significant but which few people are talking about. I seem to be coming across it more and more. It's no doubt sprung from the increasing pressure that marketers are under to demonstrate the value of their investments, and the increasing accountability that comes from better data and analytics capability.

Rather than using more traditional budgeting methods in which previous performance, sales, revenues or costs are used as a base to extrapolate future budgets, ZBB starts from scratch with a zero base and no assumptions, and effectively involves re-evaluating and therefore re-justifying every line on a budget. Programmes or activity which have been justified then form the basis for the budget, rather than an incremental increase from last year’s numbers, and it assumes no expenses to be pre-committed or balances to be carried over.

ZBB is seemingly a response to pressure for growth and efficiency, and the need for organisations to examine every financial investment with scrutiny, but it carries with it some notable advantages and disadvantages.

On the plus side, ZBB might be regarded as a more accurate and efficient way to allocate resources, particularly in the context of rapidly shifting environments. Using last year’s budget as a base can often lead to hidden assumptions and inaccuracies, and a failure to properly take account of changed circumstances. Since ZBB effectively questions the need for everything, it forces marketers to re-evaluate all expenditure and assess the value of every piece of activity, ensuring that surplus, low value or unnecessary spend is identified and cut or re-allocated. It might also lead to the discovery of more efficient ways to achieve goals, prevent unnecessary budget inflation and it involves staff in the budget process.

One of the main disadvantages of ZBB however, is often cited as the amount of time and resource that can be dragged into the process. Since it ensures that every budget line is considered, ZBB can be a highly time and resource intensive process, and potentially lead to staff feeling as though they need to repeatedly justify every element of expenditure. This can be somewhat frustrating if not done in the right way.

This feels like a significant shift, and the fact that ZZB is a growing trend in many organisations and marketing teams means that the impact is also potentially widespread. It could mean that suppliers find it harder to secure longer-term relationships when the value that they bring is questioned so regularly. It may also mean that it's more difficult for marketers to protect long-term investments and in some circumstances, it could potentially lead to projects or innovations being killed off too early because they have yet to demonstrate sufficient value. But then the counterpoint to this is that when things are moving so quickly questioning everything that you do is not necessarily a bad thing.

Either way, I'm surprised that there's not more debate about this potentially significant shift.

N.B. I'll be talking about ZBB in my latest Digital Shift trends webinars for Econsultancy, scheduled for Thursday 19th at 9am and 4pm UK time.

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Agile Resourcing at ING

In the book I talk a lot about how agile thinking and principles (and not just Agile doing) can be applied in the service of supporting fundamental change in the organisation. To enable a far more responsive, customer-centric way of working. To enable a shift away from the entrenched processes and practices that are holding companies back in the digital-empowered age. Everyone gets how important change (do we call it 'digital transformation' anymore?) is. What most businesses that I talk to really need is pragmatic application.

One of the foundational elements of this application is resourcing. The principle here is that small teams, empowered by the right ways of working and new technologies, can drive big change. My approach with many of my clients is echoed by Eric Ries's phrase 'Think big, start small, scale fast'. You always need to begin transformation programmes with a compelling vision of the company that you want to become, with advocacy from the top of the business, with sufficient impetus to create a positive sense of urgency and kickstart the shift. But the process of transformation to becoming more agile should itself be agile. So you start small, with focused programmes tackling critical business challenges or customer problems, using small multidisciplinary teams to iterate and innovate and build new value but also new ways of working. And you of-course scale fast - using the learnings you get as you go to expand this approach, these ways of working, and to influence culture change, and support a shift in mindset. The number of small, multidisciplinary teams solving customer problems and working in agile ways increases as the programme for change gains momentum, maintaining a good balance between the need to deliver business as usual whilst still generating completely new models and value in new ways. 

A number of large organisations (including some that I work directly with) are utilising this approach to resourcing as a centrepiece of transformation (digital or otherwise). ING Bank is a particularly interesting example since they have been doing it longer than most (their programme has run for several years now), made a significant commitment to agile working from the outset, and so are probably one of the most scaled examples of how this works. Based on the famous Spotify model of Squads, Chapters and Tribes, they have organised in a way (at scale) that enables end-to-end ownership of customer propositions and journeys, focused delivery against customer objectives, heightened levels of employee autonomy and engagement, and organisational responsiveness. I've written up a more detailed case study of what ING are doing here. But they are not the only ones.

In all the talk about transformation there is precious little discussion and insight into the practical application of new ways of thinking (unless, that is, you hire McKinsey for a boat-load of cash). In all the focus on customer experience, and the horizontal challenges that that brings, there is precious little talk about how we need to rethink approaches to asset optimisation and resourcing to tackle these very real problems. I think there are critical opportunities that companies have to do this in the right way, and some very real difficulties that can arise if they don't. Not least is a sensible approach to where you apply these new agile ways of working and where you don't - characterised by the three domains that I talk about here.

But it's hard to under-play how important this. This is potentially one of the most significant shifts in organisation design in decades. I'd welcome a wider discussion and of-course, your own observations and ideas. 

Don't forget there is much more about agile transformation models, thinking and practical application in my book.

Blockchain and the Perez Technological Surge Cycle

In amongst all the Bitcoin hype there was a thought-provoking question posed in a well-shared post published just before Christmas by Kai Stinchcombe, founder of a Silicon Valley financial services startup, about whether there was actually any legitimate use at all for Blockchain technology: ‘Everyone says the blockchain, the technology underpinning cryptocurrencies such as bitcoin, is going to change EVERYTHING’ notes Kai, ‘And yet, after years of tireless effort and billions of dollars invested, nobody has actually come up with a use for the blockchain—besides currency speculation and illegal transactions.'

Kai notes how each purported use case, including payments, legal documents, so-called ‘smart-contracts’, distributed storage, and authenticity verification has flaws, and unforeseen challenges that have thus far prevented them from becoming more mainstream.  And how the advantages of existing human and software systems surrounding transactions outweigh the purported benefits, (and hidden costs) of irrevocable, automated execution. What if, asks Kai, the reason nobody has adopted a distributed ledger at scale is because nobody wants it?

As a counterpoint to that, renowned VC Fred WIlson (in his post about the big tech stories of 2017) describes why Blockchain may well be over-hyped in the short-term but under-hyped in the longterm (classic Innovator's Dilemma stuff). Using the Perez technology surge cycle chart, a favourite way of looking at new technologies, Fred notes that a fenzy develops when a new technology enters the material phase of the installation period - the frenzy in effect funds the installation of the technology.

2017, he believes, is the year when crypto/blockchain entered the frenzy phase, with over $3.7 billion raised by crypto projects/startups (about equal to the total seed investment in the US in 2017), effectively to build out what he describes as Internet 3.0 or the decentralized internet. Just as the Internet 1.0 frenzy in the late 90s provided the capital to build out the broadband infrastructure that was necessary for Internet 2.0 (the broadband / mobile Internet), this year’s frenzy will provide the capital to build out the infrastructure for the decentralized Internet. That infrastructure is needed badly since whilst you can get a taste now of what things will be like, you can’t really use the technology yet as it just doesn’t work at scale: 

‘But it will and the money that is getting invested via the frenzy we are in is going to make that happen.’

The transitions from Internet 1.0 to 2.0 to 3.0 cause huge disruption but also opportunity and whilst some of the big tech players will make a healthy transition, others may not (think of Amazon, Google but also Yahoo and AOL)

‘In the venture business, you wait for these moments to come because they are where the big opportunities are. And the next big one is coming. That is incredibly exciting and is why we have these ridiculous valuations on technologies that barely/don’t work.’

That question of who can successfully navigate the jump from one S-curve to the next is critical, and applies more broadly to all types of businesses and contexts. Every company is faced with a succession of S-curves to makes sense of (AI, AR, IoT, 5G, Blockchain perhaps) which defines the need for a different type of organisation that can successful respond to continuous change but also sets out some key challenges. Most notable amongst these is the challenge of managing existing business as usual whilst innovating around the unthinkable (the reality of where the rubber hits the road in many large organisations), the difficulty in a world of shareholder value of managing the short-term hit on performance that can result from this transition, and facing up to the 'dilemma zone', or the need to innovate and experiment before it is forced upon you by shifting consumer, competitive or market contexts. This is as much about mindset and orientation as it is about timing. You need to get all three of those things right, and aligned. 

N.B. if you're around I'll be talking about this (and other near to mid-term trends) in my quarterly Econsultancy trends webinar this afternoon at 4pm UK time (membership required though)

Democratising AI Capability

I don't claim to be an expert on AI but as someone who works in the 'digital industry' (whatever that means now) I think its important to keep track of notable shifts in an area that has become fast-moving and of huge potential significance. AI is surely one of the most important S-curves around, and despite AI being around for years we seem to now be on the much steeper upwards growth curve that charaterises classic technology adoption.

It’s been clear for a good while of-course just how important AI is to GAFA (Google, Apple, Facebook, Amazon) but a recent interview with Google’s Sundar Pichai showed just how big and fundamental Google think AI capability is. He declared AI to be:

“one of the most important things that humanity is working on. It’s more profound than, I don’t know, electricity or fire,”

Google's investment in particular, and their 'AI-first' strategy, seems to be generating rapid progress, but in some interesting ways. Last May they revealed their AutoML project which was a form of AI that was designed to help them to create other AIs. Late last year they announced that AutoML had beaten the Google AI engineers at their own game by building machine-software that is more powerful than their best human-designed systems.

In a couple of examples of both simpler and more complex tasks, an AutoML system beat the human-designed system in projects focused on categorising images for their content and a more complicated task of marking the location of multiple objects in an image (something that is important for autonomous robots and AR).

The implications of this are quite profound – the number of people on the planet that have sophisticated AI expertise is limited, meaning huge competition for talent but also representing a key challenge for any organisation looking to ramp AI capability (as surely many are). Google have of-course already created TensorFlow, the open-source software library for machine-intelligence (and Amazon recently announced the launch of Amazon ML Solutions, a new program that connects Amazon machine learning experts with AWS customers in order to help them identify new uses and capabilities for machine learning inside their businesses) but despite this, the development of your AI capability could until now pretty much only move as fast as the number and quality of expert brains that you could put on the problem. The potential to further democratise AI capability through using AI itself could take enterprise and consumer AI application to a whole new level.

Speaking about the automation of AI design and build, Sundar Pichai has said:

“Today these are handcrafted by machine learning scientists and literally only a few thousands of scientists around the world can do this…We want to enable hundreds of thousands of developers to be able to do it.”

Whilst it may currently be easier to adapt a current system to address a new task rather than build a new system from the ground up, the automation of this process could well make it far easier to design increasingly complex new systems. The role for humans in this process changes from designing and engineering to supervising and refining, for example to ensure that biases are not accidentally built into the system.

Whilst the times we live in are witness to some notable milestones in the development of a technology that will likely impact all of us, it is the potential to democratise the technology that perhaps will bring the most fundamental step change.

Google Firestarters - Change and Complexity - The Event

For our recent Google Firestarters (our 26th!), we revisited a successful format that we first did two years ago. In 2015, in one of our most successful Firestarters ever, seven of the best minds in the industry gave a ten minute perspective in answer to a single question: what's the best thing that you've learned in your career? This time we brought together another seven brilliant industry brains in the same quick-fire format to answer what is arguably the defining challenge of our time: what’s the best insight that you’ve learned for dealing with change and complexity?

Jim Carroll, erstwhile Chairman of BBH, kicked us off with a wonderfully insightful ten minutes drawing on some of the ideas he writes about over on his excellent blog. Jim talked a lot about how we often list out capabilities (both personal and agency) as a long tally of things we can do without really thinking about what our core competency truly is and how we can apply that in new or different ways. Using a lovely story of what happened when a famous taxidermist was asked to stuff a walrus when he'd never seen one in real life before, he took this into the dynamic that often exists between performance and transformation (to perform and/or to transform): 'If you want to stuff a walrus, you need people who know their walruses and people who know their taxidermy.' Transformational change requires cross-generational expertise. And finally he focused on how process can be a catalyst for change - if you want to change the product, change the process (the team, the brief, the meeting, the time, the context). Try new combinations and partnerships. Crash the procedure and crunch the schedule. Test and trial, experiment and explore. Be prepared for the unexpected. As John Bartle once said: ‘Be in the vanguard, not in the guard’s van.’

Mel Exon picked up on some of these themes in her talk, reflecting on a talk she'd given at SXSWi a few years back about Skynet vs Mad Max, and her own personal story of finding balance and establishing her own guard-rails within which to understand change. To quote Maya Angelou: 'The need for change bulldozed a road down my mind'. She pulled out some key thoughts on how important it is not to become overly-cynical ('cynicism is the enemy of creativity'), to question everything, to be brave in taking the leap. She quoted Paul Feldwick: 'We need to be respectful of the past and more critical of it'. I loved her point about how we need to embrace people who are different to us, but also how finding your gang (and the sense of belonging we get from likeminded people) is good. She emphasised the importance of being child-like in our learning and enthusiasm, how we should not lose our craft in the rush to management, but use pattern recognition, simplicity and adaptiveness as a way of navigating complexity.

For his talk Craig Mawdsley drew from Stoic philosophy (and The Daily Stoic), emphasising that the simplest approach to navigating complexity is to work out what's in your control and therefore what you can change, and then to let go of worrying about the other things:

“Some things are in our control and others not. Things in our control are opinion, pursuit, desire, aversion, and, in a word, whatever are our own actions. Things not in our control are body, property, reputation, command, and, in one word, whatever are not our own actions.”

Our main job is to be a human being, to just do the work, make the best of what is in your power and take the rest as it occurs: 'Look at what you've got and fall in love with that'. We have the potential to live a good and happy life if we can learn to be indifferent to what makes no difference.

Jerry Daykin, Head of Global Digital Media Partnerships at Diageo, followed with a high-paced but insightful ten minutes. Agencies, he said, need to understand that clients take big risks with their budgets and sometimes we just make things more complex than they need to be.

The number one thing that stop things from happening is time - comms is often a small part of what CMOs do, sometimes the benefits of digital can be oversold, sometimes we indulge in lazy-endism ('TV is dead'). The best way to create simplicity is to create guide rails for marketers, particularly around complex areas like programmatic, ad fraud. The opportunity is to generate more trust through making marketer's lives easier. Frameworks are useful, but execution is everything.

Lucy Jameson, Founder of Uncommon London, has had quite a couple of years. She told a personal and inspiring story of her transition from CEO of Grey, through a year in which she interned at Facebook, to her current choice to start her new agency. As humans, she said, we totally under-estimate the chance element of change and we love stories. So stories can be a powerful way to navigate change. Her own story about the choices she's made more recently in her career, and the work that she has chosen to do really brought this to life in a very heartwarming way.

Nicole Yershon describes herself as a maverick, inspiration and a troublemaker (in a good way). She's just released her new book 'Rough Diamond' which describes her journey of driving change, creating things from nothing, and turning disruption into advantage. Nicole also told a couple of vivid personal stories of how she'd made change happen when everyone around her was against it: 'ask not why we can do this, ask why we can't'. Disruption is so often seen as a negative word but it also leads to huge opportunity - but we have to get uncomfortable and persist through the pain barrier that change often brings with it. Innovate at the core.

Our final talk was a wonderfully witty presentation from Dan Cullen-Shute who rounded things off with a funny but insightful take on the theme which is difficult to do justice to here. He talked about working hard to solve the right problems, how we always think that we're living in the greatest period of change that the world has ever seen, and how if we look for complexity we'll always find it. But his final though was a brilliant way to finish our provocations: Never forget to be excited.

It was a truly fascinating event. My thanks go to all our speakers for their brilliant talks, to Google for hosting, and to all those that came along on the night. As we go into 2018 Google Firestarters is entering it's seventh year and (although I'm biased) it feels as though these events are more vibrant and challenging than they have ever been so my thanks to our community and speakers for making them so fulfilling to curate.

Thanks to @melex for the pic at the top