With the global pandemic of 2020 and the depression that followed, came the realisation that our economic system was hugely vulnerable in the face of disruptive events. Companies inevitably rushed to automation more than ever before, and the emerging AI & Robotics business sector played a pivotal role in this transition.

Why the past tense?

Because, regardless of whether it’s right or wrong, this is what will happen. This blog post does not look at whether Robotics is the future, but who is best placed to succeed. As a new economy emerges from the other side of this pandemic, businesses will be forced to question the previously unquestioned: are global supply chains optimal? Is ‘Just in Time’ manufacturing robust enough to survive future shocks? Do we need offices any more? 

As we adapt to lockdown, industry is struggling to cope with the sudden absence of people from essential processes, and automation is forefront in their minds. Previously, many saw automation as a way to remove human fallibility from well defined, repetitive processes in order to improve quality and productivity. Now it will focus much more on removing people completely from the process in order to remove a point of failure.

Automation of production lines has long been a thing, and although people play an important part in these lines, they are treated more as a cost/benefit equation than as the actual human beings they are. If (and it is a big if) we see a new economy emerging over the coming months – one that incorporates elements such as a more than minimum living wage or a universal basic income – then that cost/benefit equation will swing even more towards automation, adding to the sense of vulnerability businesses are now feeling. 

Given the extent of the damage caused to businesses by the lockdown, companies will now look for solutions throughout the supply chain, not just in the factories. They will accelerate the development and introduction of self-driving vehicles; they will roll-out Amazon Go – style self-service retail stores; they will copy Ocado and Amazon and replace people with robots in their warehouses.

This is a dangerous strategy, as it represents a swing of the pendulum to another extreme, and as discussed in Part 3, specialisation leads to fragility in the face of disruption. Imagine, if you will, what happens to this automated world in the face of a virus of the electronic variety.

Back to the Map

Rightly, or wrongly, it will happen, and so the more important question relates to which industries are best placed to capitalise on this trend. And so we return to the Map, and another “sea” waiting to become a landmass (business sector) in its own right. We’ve labelled it AI & Robotics. 

As you can see, the Map shows that the neighbouring territories are Computer Consultants, Software Development, Electronics, Electrical & Mechanical Manufacturing, and Motor Vehicle Manufacturing. Companies in each of these sectors are well placed to enter the field of robotics, and some are already doing so. In each case, the entry point is different and so it’s worth looking at a couple of them in more detail by way of explanation.

Step forward Dr. Susan Calvin

In Isaac Asimov’s body of work, there are a significant number of stories that centre around intelligent machines. Many of these stories feature Dr. Susan Calvin, who Asimov refers to as a robopsychologist working at US Robots and Mechanical Men, Inc. He postulates that this profession would be a combination of advanced mathematics and traditional psychology, but in reality the need is more likely to revolve around the training, utilisation and integration of Robots into the business world.

This is a reasonable role for companies operating in the Computer Consultants business sector to take on and thus start the migration into the AI & Robotics business sector. Following the disruption caused by the COVID-19 outbreak, and the resulting demand for greater automation, there is a clear opportunity for these businesses to promote their skills in this area and start the journey.

The first areas of greatest demand are likely to be in the production line, and in the warehouse element of the supply chain, where “dumb” robots already play a major role. There will now be a push to further automate the more complex activities currently undertaken by people, and this will lead to a demand for consultants with experience in introducing technology to organisations. Computer Consultants are ideally placed to benefit from this demand, especially if they include software development capability in their offering or partner with companies that do.

Management consultants are less well equipped to help as the level of technical expertise required to understand the art of the possible, and design solutions is far outside their skill set. They will, of course, have a go, but the Map confirms that they are not well placed to enter this sector.

Here in my car

The other area of the supply chain that will, no doubt see renewed demand for automation is that of transportation. This will accelerate development of self-driving technologies coupled with increased pressure from business to make changes to the road transport system to make introduction of such technologies less challenging. We can expect to see proposals for “freight only” lanes, and dedicated telemetry systems to lower some of the barriers to entry.

The companies best placed to occupy this part of the robotics landscape are the Motor Vehicle Manufacturers. Much work has already been done into self-driving vehicles, but most of the focus has been on cars. It is likely that attention will now move onto the larger freight vehicles. Despite their size, these vehicles actually present an easier route into this sector as they generally follow more predictable routes, and travel between a smaller set of end points. 

Transportation companies such as Uber have also tried to make inroads into this area, but the Map predicts a less successful outcome for them, as they are a significant distance from the new area of AI & Robotics. Remember, on the Map proximity indicates similarity of skills and mindsets – companies located in other areas take much longer to develop the required attributes than organisations on the immediate borders. Uber are making the classic mistake of assuming that being a consumer or seller of a product somehow positions you to become a producer in your own right.

Stuck in the middle

So, that covers the types of business that will benefit from the inevitable demand for automation, but what about the demand itself? At the start of this post, (and in previous posts) we’ve discussed the dangers of specialisation and the increased resilience that comes with diversification. It is for this reason that a headlong rush to “automate all the things” could create as many problems as it might solve. It would also lead to an unmanageable portfolio of change that could cripple an organisation during what will inevitably be an extended recession.

One of the more difficult decisions for most companies is where technologies such as AI and machine learning can and should be effectively deployed. There is much talk of AI as the answer to everything, but there are places where it is most appropriate and places where it is less useful. There is also the confusing matter of machine learning algorithms versus “true” AI in the form of neural networks. The same question arises – which to use and where.

The problem is complex, but as a starting point here is a simple 2×2 grid (because we all love a 2×2 grid): 

The horizontal axis represents the sophistication of the problem being solved ranging from highly complex (multiple variables and multiple outcomes), and the vertical axis represents the nature of the decision to be made ranging from fully objective (where there is little or no doubt) to highly subjective (where the outcome is open to interpretation and opinion).

For highly complex problems involving a significant amount of subjective judgement, people are by far the best suited to this type of activity. At the other extreme, simple problems with highly objective outcomes can easily be automated using traditional and well understood hard coded solutions. 

As we remove subjectivity from a problem best suited to people, or add complexity to a problem currently solved using traditional code, machine learning algorithms come into their own. These are complex, knowledge based solutions that take broad sets of inputs to make a decision in a predictable and traceable way. The automation of the NHS 111 service is a good example of a problem well suited to machine learning.

Heading in the other direction, if we can take some complexity out of the decisions currently made by people, or there are simple problems that were previously not automatable using traditional coding techniques due to the desired level of subjectivity, we now have AI as a solution. Familiar examples involve identifying the subject matter of documents, interpreting medical scans or identifying people or behaviours in CCTV footage.

The same grid can be applied to physical robotics. In the bottom left square we have the type of machines we’re all familiar with on car assembly lines. In the bottom right, (Complex/Objective) space we have the potential for automating surgical procedures. In the top left AI opens the door for semi-autonomous machines such as exploration vehicles. Self-driving cars sit on the boundary between the top left and right squares, and this is why the problem has proved so difficult to crack. Deliberate simplification of the problem by altering the highway environment (or reducing the scope as described for freight vehicles) could accelerate the introduction of such vehicles faster than advancements in the current level of AI might achieve.

And let’s not forget that automation does not have to mean less people; far from it. History has shown that as machines take over in one area of human endeavour, this opens up areas previously ignored. If social distancing has taught us anything, it has told us that personal contact is essential to our wellbeing and to the success of our businesses. Instead of replacing people with robots, think instead of using technology to do the mechanical things, and free up people to be more human.

And so that brings to a close our quick visit to the new landmass that is the AI and Robotics business sector. In part 5, we’ll look more broadly at the Map and how things might unfold as we move out of lockdown and into a time of financial uncertainty. We’ll look at the challenges, but more importantly we’ll seek out potential green shoots and identify where they could emerge.

Part 1 – Dealing with disruption
Part 2 – A fascinating journey, explained 
Part 3 – The Rise of the Avatar
Part 4 – Domo Arigato Mr Roboto – (you’re here)

The real answer to unpredictable change, if you have the scale to achieve it, is to maintain diversity of offering, and build flexibility into your processes. Diversity means that when change comes, if you lose in one area, you gain in another. Flexibility allows you to adapt quickly to change to capitalise on the gains and minimise the losses.

Survival of the fittest

In part 1 of this series we introduced the Business Evolution Map and explained its origins, and in part 2 we used the map to chart the Nintendo journey, showing how the Map can be used to explain (and therefore predict) success and failure. But that is the past, and it’s the future we’re really interested in when shaping business strategy. 

Specialisation can be powerful during times of stability. The hummingbird, for example, has evolved to feed on nectar from plants that only a few species can access. In return, certain plants have evolved to rely specifically on hummingbirds for pollination. This codependency works brilliantly, as long as the environment remains stable, but if you remove one partner from this equation, the other will struggle to survive.

The future is difficult to predict, and the only reliable way to survive the unknown is to remain diverse and flexible. Nature achieves this through evolution for slow change (the hummingbird) and variety for rapid change. The hummingbird may not survive the loss of one food source, but the diverse population of birds as a whole will barely be affected.

Before the COVID-19 outbreak, Primark was dominating on the high street, but without an online offering they are like the hummingbird without the flower. Overnight, specialisation has turned from a strength to a weakness. Similarly, companies with a predominantly online presence and high degree of automation will have suffered less, and may even have benefitted from the impacts of lockdown. Common Thread Collective provide some interesting raw data on their COVID-19 eCommerce update page. 

No doubt, we will see companies rushing even more to be “digital first” and “fully automated”. (In part 4 we will discuss how firms able to exploit the emerging Robotics business sector will benefit from this change). COVID-19 has taught many companies a lesson here, but the lesson is NOT digitalise and automate everything. The lesson is not about specialisation.

There but for the grace of God

Those who embraced digital as an integral part of their offering were certainly right to do so. In fact, if supermarkets had invested  more in online and home delivery capability the impacts of lockdown on our daily lives might have been significantly reduced. Instead, we are seeing the system failing to meet the new and unexpected level of demand. 

However, if fate’s dice had rolled the other way, things would have been very different. We can expect to see a lot of survivor bias exhibited in articles over the next few months, coupled with a renewed effort to get rid of “bricks and mortar” channels. Those who didn’t go “digital first” will be referred to as dinosaurs.

However, the next change is unlikely to be another once-in-a-century pandemic. The clue is, after all, in the name. Imagine if, instead of a physical virus, the next disruptive change came in the form of a virus of the electronic kind. This time the heavily automated, all-online businesses that would be the ones most affected. High street companies with large human workforces and manual processes would be the survivors in this scenario. Primark might have become even more dominant, and the survivor bias would look very different. The narrative would be less about dinosaurs and more about “look before you leap”.

The real answer to unpredictable change, if you have the scale to achieve it, is to maintain diversity of offering, and build flexibility into your processes. Diversity means that when change comes, if you lose in one area, you gain in another. Flexibility allows you to adapt quickly to change to capitalise on the gains and minimise the losses.

We’ve already covered flexibility in a previous series of blog posts that describe our Continuous Evolution framework. Diversification is what we’re going to cover next.

Serendipity

Luckily, identifying successful diversification is the core purpose of the Map. In Part 2, we used Nintendo as an example, and described a successful early partnership with Disney. If we compare their performances in the face of the current disruption, we see an interesting trend.

 

Looking first at Disney, we see a not surprising drop in share value as COVID-19 (commonly referred to as coronavirus) impacts economies across the globe. When we look at Nintendo, we see the same drop, but this is followed swiftly by a recovery back to its original position. Disney’s predicament is understandable; even when we take its broad range of assets into account, its business model has a strong (one could say pivotal) dependency on physical presence. Nintendo is not similarly encumbered, but more importantly the rise coincides with the release of the game “Animal Crossing, New Horizons”.

If you haven’t seen it, suffice to say the game allows multiple players to interact and socialise  as cute animals on an idyllic island. It is immersive, social, and stress free – the antithesis of present circumstances. In his review in The Telegraph, Jack Rear described New Horizons as “the perfect DIY recipe for the most chilled out, relaxing, and engaging life simulator ever.” The Atlantic also has a good piece about the game by Ian Bogost, entitled The Quiet Revolution of Animal Crossing.

What Nintendo has managed to do, in a very timely manner, is tap into an emerging business sector. A sector predicted by the Map in the form of an “inland sea”. 

New horizons

On spotting this feature of the Map, we tweeted about it, first in October of last year, and then in November:

It was clear from the Map that there was untapped revenue sandwiched between well established business sectors. A clear opportunity awaiting forward thinking companies currently resident in any of those neighbouring sectors. 

Entry into this sector has also been eased, rather than hampered, by current events. A far greater number of people have been forced to become “digitally capable”, and opportunities to interact virtually are being sought as a replacement for face-to-face interaction. People may have to be physically distant, but they are looking for ways to remain socially close. As indicated by the map, offerings in this space are limited. This is what an inland sea represents.

Nintendo has managed to take a step into this territory by capitalizing on its games development capability (Software Development). With sufficient foresight (i.e. access to the Map), DIsney could have protected themselves, in part, via a similar move. Exploring ways to offer immersive but virtual experiences, in addition to the very physical experiences that they specialise in. 

It’s reasonable to assume that these might have had low adoption rates, and been of low benefit initially in terms of revenue, but having this capability would have made their offering more adaptable to unexpected circumstances. It’s also possible that such an offering, far from detracting from their core business, could have created an adoption path into the physical disney experience. A “try before you buy” option for people who otherwise might not be willing to commit the time and money to fly their family across the Atlantic to visit Disneyland in Orlando.

Interestingly, Disney consider themselves to be early adopters of virtual experiences; ahead of the game. In some ways this is true, but only within their existing sector. Rather than creating virtual experiences, they have incorporated VR into their physical experiences. Although it might at first appear to be diversification, it actually represents even greater specialisation.

Distant rumblings

And so, we return to Nintendo and the successful launch of Animal Crossing New Horizons. Where one company finds success, others will inevitably follow. Some will just see it as another game, and miss the significance. Others will recognise the situation and attempt to open up in this sector from elsewhere on the map – we predict slow progress and probably failure. 

Those moving in from the neighbouring sectors will have a high chance of success. There are already signs. Amongst recent acquisitions, Apple has bought Voysis (a digital voice assistant) and NextVR (a combination of virtual reality and live events), both useful capabilities when entering the world of immersive experiences. What is more, they have the Interaction and Immersive Media sector firmly surrounded and should find it easy and profitable to make this move.

Another neighbour is Facebook who is in the process of launching “Facebook Horizon” on its VR platforms. Facebook Horizon is a virtual reality universe that allows you to build your own environments and games. You can then play and socialize with friends or explore landscapes created by other users. This has, of course, been attempted before, but as with all new ventures, the time has to be right. 

Getting social

To assume Interactive and Immersive Media is all about virtual reality headsets would be a huge failure of imagination. VR is only a small corner of this business sector. We’ve considered how organisations like the BBC might revive the concept of “event TV”. People are already attempting to recreate the group viewing experience online, but it takes real effort. An organisation in the Media Broadcasting space would be well placed to enter the interactive arena by creating a truly joined up virtual experience.

Companies have dabbled with the influencer market, but again, no one has really capitalised on this opportunity. Companies in the Hosting & Search or Advertising & Marketing Sectors could partner with a software development company in a platform play around this space.

Finally, social media platforms are certainly where people interact virtually, but the key purpose for those interactions are to share opinions, garner likes or enter into divisive arguments. They may be called “social” but they often are far from it. There is a clear place in the Immersive and Interactive Media sector for a platform that allows people to gather in a more positive way. To share in a social experience as we might at a club or event.

The list goes on; far too many to mention here. It is, after all, a whole new business sector potentially worth many billions of pounds in the UK alone (the Map indicates a potential initial value of £13bn).

And so, in summary, as you consider what to do next, remember these three points:

1. Specialisation leaves you exposed during times of change (the hummingbird)
2. Diversity coupled with flexibility are the best traits for survival (Nintendo vs Disney)
3. Knowing where and how to diversify is paramount for success (the Map)

Interactive and Immersive Media is an interesting route for diversification but if that’s not your area of the Map, then it’s not the right option for you. That’s why we intend to cover the other “continents” in this series. In part 4, we’ll explore another emerging business sector predicted by the Map – Robotics. We will show where it is positioned relative to other business sectors and who is best placed to exploit it.

Part 1 – Dealing with disruption
Part 2 – A fascinating journey, explained
Part 3 – The Rise of the Avatar – (you’re here)
Part 4 – Domo Arigato Mr Roboto

I’m sure, at some point in our careers, we’ve all embarked on a project with a clear outcome in mind, but found that somewhere along the way we’ve either lost sight of the goal, or worse still, delivered that goal only to find out things didn’t work out the way we’d planned. Reshaping activities as Bets keeps the mind focused on that uncertainty and breaks things down into meaningful wins.

You won’t know until you try

“Luck is what happens when preparation meets opportunity.” – Seneca

In part 1 of this series, we introduced our Continuous Evolution approach, in part 2 we explained how we use a purified form of OKRs to turn your vision into concrete objectives, and in part 3 we described how to condense all of this into a Roadmap Radar. You may already have read these preceding parts, and you may even have experimented with using what you’ve learned so far to shape a portfolio of work around your organisation’s strategic goals. 

However, before you proceed any further, there’s one more step and it’s probably the most important of all if you want to bring true agility to your ways of working. We call it the Bet Canvas, and it’s an easy-to-use tool that helps structure your delivery activities in a way that encourages experimentation, innovation and pragmatism. Placing bets allows your organisation to test which interventions will improve business outcomes, at minimum risk.

The word “bet” is intentional language that confronts how much we are willing to stake on the stated outcome, in terms of people, time and investment.  It relies on the effective design of a structured experiment, that creates feedback loops, validates the business value of an idea, and reports on progress towards specific, leading metrics.

What makes a good bet?

“If you must play, decide upon three things at the start: the rules of the game, the stakes, and the quitting time.” – Chinese Proverb

To work well, each bet must be:

• Aligned to a single objective of the organisation (as depicted by the Roadmap Radar)
• Specific enough to be (dis)proven within 90 days
• Based around experiments with carefully controlled variables

A bet is used to test one hypothesis for how an objective might be achieved, and so it is pursued by a small, autonomous, cross-functional team that contains all the skills required to prove out any assumptions. Each experiment builds the organisation’s capability, enabling the pursuit of future bets with a higher degree of confidence.

To explain the construction of a bet in more detail, let’s consider the following example:

1: The Bet Statement

The first section is a simple headline, capturing the essence of the bet.  Keep it short and ensure the statement feels familiar, by using the language of your organisation. Avoid specific solutions at this stage – this is supposed to be both general and memorable

2: The Hypothesis

The hypothesis should follow this simple formulation:

“We believe that [doing x]  will result in [y happening] and we will know we’ve been successful when [we measure z]”

In this example:

X = making our takeaway pizza boxes recyclable

Y = improved brand image

Z = brand sentiment improves without diluting the current profit margin

Each part of the hypothesis statement is a choice,and should be carefully considered and debated by the team. Be specific – each hypothesis refers to a single potential solution to a problem. Never include “and” statements as this indicates you’re attempting to pursue two bets at the same time.

3: The Problem

At this point, the team should outline, as briefly as possible, the problem they’re trying to solve.  Details, such as existing metrics, should be included, to indicate the size of the problem. If the problem cannot be concisely and precisely described, it means that you should either spend time developing a shared understanding, or place an alternative bet.

Any problem that is too large to claim, and/or is beyond your organisation’s influence should be considered a ‘fact of life’, and removed from the bet. For example, in this case, the pizza company cannot control the limitations of global recycling protocols.

Be ruthless – each problem must be substantial enough to justify committing time and resources otherwise it should be de-prioritised, and do not proceed beyond this point until everyone agrees on the problem being solved and the potential value therein.

4: Measures of Success

Using the measures articulated in your hypothesis, this list itemises how you will measure progress towards the goal & objective to which your Bet is aligned. Use measures that are easy to capture, and be creative – the right measure may not exist now, but can be created. Don’t try and boil the ocean – measuring the number of boxes sent to landfill would be a potential measure, but it is impossible to accurately capture.

In this example, the organisation is measuring success in two main ways: (1) improvements to brand image, and (2) maintenance of margin.  Whilst margin is easy to measure, the brand image is more challenging, but might be measured using mechanisms such as Net Promoter Score, sentiment on social media, headlines in the Press, and customer feedback. Recycled pizza boxes would be an “announceable”, and result in such events as the CEO being invited onto Radio 4’s Today programme, whilst customer feedback might come in the form of answers to the question: “Why did you choose us today?”

5: Challenges & Risks

This is an opportunity for the team to identify any difficulties they might face when pursuing the Bet, therefore prompting the right conversations, at the right time, about how to mitigate risk and/or drive out assumptions.

In this example, the organisation needs to confirm the cost and supply implications of inserting biodegradable greaseproof paper into their pizza boxes.  Thinking creatively about challenges and risks allows the team to anticipate problems that can be mitigated now – in this case, training requirements that could, depending on results, be rolled out nationally.

If risks cannot be removed or substantially mitigated by the core team, it may mean you need to invite more/different people. If the risks are too large and/or numerous, this means you need to pivot or abandon the bet. Don’t panic – all bets worth pursuing have challenges & risks.

6: Desired outcome

This stage involves a brief description of the optimal future state. It is the “why of the Bet Canvas, and its purpose is to help concentrate the mind. If the desired outcome can’t be easily expressed, or seems underwhelming, that is a signal that the team should pursue an alternative bet.

In this example, the bet is that the desired outcome (improved brand status) is made possible through making an intervention (in this case, including biodegradable greaseproof inserts) that changes behaviour (allowing customers to recycle their pizza boxes) with no adverse financial effects (such as reduced profit margins).

Outcomes should be ambitious, such that every bet feels like a stretch goal. Always think in terms of ‘interventions’ and ‘changed behaviours’, and avoid vagueness. Measuring progress towards the desired outcome should be easy, or at least, uncomplicated to capture.

7: Alignment

Each bet must align to an objective which in turn aligns to a goal, as confirmed through the OKR process.  That is to say, the successful pursuit of a bet delivers progress towards the realisation of prioritised business value. A bet should never align to more than one objective and should be checked regularly for relevance, as objectives can change. If the Bet doesn’t clearly align to an objective, it should be rejected and reformulated (or dropped).

8: Experiment

The last section is the most demanding, and the most valuable.  Time should be spent designing a robust, repeatable experiment that sensibly controls variables, and produces leading measures of progress that can be captured and reported weekly.

In this example, there are three cohorts – a control group, a group for whom the additional cost is optional, and a last group, who have the price of the insert included in their order by default.  Certain variables are controlled – firstly, the experiment only applies to one city, each group is defined by the boundaries of certain postcodes, and will only run for 90 days. This limits the organisation’s exposure to risk, whilst maximising the number of lessons learned from placing the bet. 

When devising an experiment, limit as many variables as possible as this reduces exposure to risk. Ensure that you have rapid feedback loops to help guide progress, and remember that this is not a ‘to do’ list, but a rigorous test of the assumptions that underpin the bet.

Survival of the fittest

“I told her once I wasn’t good at anything. She told me survival is a talent.” – Susanna Kaysen

This concludes our series of posts on our Continuous Evolution framework, and now is a good time to re-emphasise that the approach is iterative. It is not enough to create a roadmap, pursue some bets and then use that to create a long term delivery plan. This framework provides an alternative way of working, rather than a temporary fix to a short term problem. In part 1 we explained the overall cycle as three phases, Shape, Plan and Execute, and to get the most benefit from it, we would recommend that you repeat this cycle quarterly. This may seem challenging – it may even seem overwhelming, but that is the nature of change. It is relentless and inevitable, but it is not, as some would claim, highly variable.

There are not long periods of stability punctuated by sudden periods of change. It only seems like that to organisations that fail to notice the change around them until it becomes so great that it cannot be ignored – and then it is often too late. 

We have introduced, what might be, to many of you, a very different approach to managing change and planning for the future, and it is fair to say it only touches on what is a fundamentally wide reaching transformation for most traditionally structured organisations. However, We would encourage you to give it a try; it has worked well for those we’ve introduced it to, and it is based on experience gained in those same large traditional organisations.

Start small, explore, test and learn, and remember the world is not predictable. Success lies in the ability to adapt quickly – we’re here to help if you need us. If nature teaches us anything, it teaches us that to survive and thrive demands Continuous Evolution.

For more information, or to engage our services, you can contact the Equal Experts Strategic Advisory Practice at StrategicAdvisory@equalexperts.com. We’re also on twitter @EqualAdvisory if you want to follow us.

Part 1 – An agile strategy for an unpredictable world
Part 2 – Shaping the vision
Part 3 – The Roadmap Radar – When is a plan not a plan?
Part 4 – The Bet Canvas – Nothing ventured, nothing gained – (you’re here!)

Traditional roadmaps can become so granular that they turn into long to-do lists, or drift so far into vagueness that they mean different things to different people. Teams can’t see how their work relates to business priorities, and become demoralised and demotivated.  The Roadmap Radar addresses these anti-patterns by ensuring that all efforts are clearly aligned to your strategic goals and objectives. 

What is the Roadmap Radar?

“Sometimes I feel a lot of things but I keep it in. I’m sure we all have this built-in radar of what we predict and when it happens, we feel ‘I knew it’”. – Muhammad Ali

The Roadmap Radar is a tool unique to Equal Experts. We are not averse to reusing the tools already available, but in this instance we found the market lacking. Planning tools rarely cater well for agility and change, and do a poor job of connecting delivery teams with the organisational goals – the essential “why” of their work. It is for this reason that we developed the Radar to align the goals and objectives captured during an OKR session (as described previously in Part 2), and bridge the gap between the objectives and the tactical ‘Bets’ placed by the organisation in pursuit of business value (in Part 4).  

In essence, the model provides an intuitive visualisation of the organisation’s priorities.  By plotting initiatives against specific objectives within agreed time horizons, the Radar also confirms clusters and/or gaps in effort. In this way, activities are directly aligned to the organisation’s strategic goals, thereby providing teams with a greater sense of purpose and meaning.  Any misaligned activities are placed into the backlog, ensuring resources are effectively allocated. 

A common symptom of granular roadmaps is a tendency towards a ‘Project’ culture, with a count of outputs (items ticked off a list of tasks) distracting from the realisation of real business value.  And you know when the Roadmap has become too vague when you notice people – with all the right intentions – doing their best to interpret an obscure and ever-changing plan. The most obvious example of this is when teams build things “just in case”, that either overlap with other efforts, or are in themselves pointless.  

The Roadmap Radar ensures that everyone purposefully works on proving the business value of ideas that align to the strategy of the organisation. It removes dependencies, simplifies decision making, and empowers teams.

Why a Radar?

“I train myself mentally with visualization.” – Camille Duvall

We chose the visual metaphor of a Radar for a few reasons.  One is that a Radar is by nature dynamic; by using it, we challenge the idea that Roadmaps, once drawn up, are static and unchanging.  Another is that the ‘Bets’ appear on the Radar as blips, which can move towards the centre (therefore indicating that they are more urgent and important), or move out to later quarters, according to an organisation’s evolving understanding of the challenges and opportunities.  

The “single big picture” nature of the model allows anyone to see imbalances in the plan. Too many Bets against a single objective in a single quarter will most likely overextend the teams, and lead to diminished outcomes; too few plotted against a Goal typically indicates that the portfolio isn’t quite as balanced as the organisation may claim. It is always clear where further work is required.

The radar format also limits space in the current quarter, whilst providing more space in the outer rings. This naturally guides teams to commit to fewer things this quarter, but encourages conjecture in future quarters. As time progresses, and items move inward, discoveries and new information remove that conjecture and the reduced space encourages pruning and prioritisation.

A final advantage is that beyond four quarters, the Radar format becomes unwieldy. This is deliberate and should not be worked around. It is okay to use that space around the edge of the Radar for possible futures, but anything more than that ignores the original point of the Continuous Evolution – the future is unstable and unpredictable.

What outcomes should I expect?

“Tell people there’s an invisible man in the sky who created the universe, and the vast majority will believe you. Tell them the paint is wet, and they have to touch it to be sure.” – George Carlin

Across a variety of engagements in different sectors, the Radar has been instrumental in creating  a balanced portfolio of Bets, that helps organisations decide where to go next, with confidence. It has allowed companies to rapidly reorganise, shedding siloed approaches in favour of multidisciplinary teams, and it has worked within organisations to improve transparency and collaboration.

In a major mobile provider, we created a Radar that helped make a complex portfolio of innovative ideas manageable and focused effort on the first few bets prioritised by business value, speed to market, and level of experience gained.

Working alongside a major professional service provider, we tackled a traditional and static three year transformation programme with multiple critical paths and interdependencies. Using OKRs and the Roadmap Radar we turned it into an agile driver of change designed to deliver real value at least every quarter. 

We helped an eCommerce function within a large retail company get to grips with an overwhelming internal demand pipeline. Here, the Roadmap Radar helped not only with alignment of activities, but also with prioritisation, removal of duplicated effort, and stakeholder engagement.

In all these cases, use of the Radar significantly reduced risk, improved agility and improved team morale and motivation.

How is a Roadmap Radar structured?

“Order is the shape upon which beauty depends.” – Pearl S. Buck

Drawing on the language of OKRs, the Goals create the main coloured regions of the Radar, and reflect the long-lived ‘North Stars’ of the organisation, capturing its purpose and values. Radars tend to comprise 4-5 Goals, and this part of the model changes infrequently, unless the organisation decides to radically diversify.  

Objectives are the “pizza slices” of the Roadmap Radar, and are divided into concentric rings covering quarterly time horizons; they represent strategic priorities, and are always aligned to the Goals. Objectives  are aspirational, and outcome-based, e.g. “Acquire new customers” or “Be number one for customer satisfaction”and each objective is aligned to one, and only one goal. In working to achieve an objective, a team must prioritise the aligned goal in all its decisions, but is not allowed to undermine any of the other goals. This is another advantage of the radar format – it allows everyone to see the whole picture at once, and thus avoid any such conflict.

Whilst the number of Objectives per Goal varies, our advice is that one is too few and five is too many. If you only have one, and you fail against that Objective, you automatically fail against the Goal, which is a big risk, and this entire process is about maximising business value whilst minimising risk. Conversely, having five or more will dilute efforts across the 90 day cycle.

‘Bets’ are shown on the Radar as triangles, with each one representing a time-bound experiment, designed to explore the impacts of an intervention. Each Bet includes carefully controlled variables, and progress is measured by the Key Results captured during the OKR process.  The optimal approach is one bet per squad per 90 day cycle.

Using the Roadmap Radar

The most important thing to remember when using the Roadmap Radar is that it isn’t a plan; in other words, it is not laid out in stone to be followed blindly. Everything about the Radar is volatile, within its own cadence. Goals are relatively stable, but even these may change after a year or two. Objectives should at least evolve every quarter as Bets are won or lost, even if they are not completely replaced by new ones. And the Bets that populate the Radar should be the most volatile – we’ll cover Bets in Part 4.

It is not enough to simply use the Radar without adapting your organisation structure to it; this would defeat the original object of the exercise – to become a flexible company able to continuously evolve. But the Radar does make it easier to reorganise, as you already have the structure around which to do that. 

Transformation requires you to create self-contained multi-disciplinary teams dedicated to the delivery of specific Objectives. One team per Objective is ideal, but it is okay to have a team pursuing two or three neighbouring objectives at once, provided these objectives all align to the same goal. Each team should contain all of the individuals and skills necessary to achieve the objective, and so as the Bets evolve, it might be necessary to tweak the team make-up as you go.

The other thing that needs to change, if you are to get the full benefit of Continuous Evolution, is your performance and reward approach. If collaboration, empowerment and motivation are to be maximised, performance should be measured at the Objective (and therefore the team) level, and reward should be at least at this level and no lower. Individual performance management and reward, ubiquitous though it is, is not the only way to run a business, and it is not part of the Continuous Evolution approach.

In the fourth and final part of this series, we explain in more detail the concept of “Bets” and introduce the Bet Canvas – a tool for shaping activities in a way that gets you to doing fast, whilst reducing risk and resolving assumptions.

Part 1 – An agile strategy for an unpredictable world
Part 2 – Shaping the vision
Part 3 – The Roadmap Radar – When is a plan not a plan? – (you’re here!)
Part 4 – The Bet Canvas – Nothing ventured, nothing gained

 

Traditional businesses use KPIs that compare year-on-year performance, and “SMART” objectives that commit people to an inflexible 12 month journey. Reaction times are slow, and feedback loops bring insight far too late. It may seem counter-intuitive, but success with long term goals can only be achieved using short term objectives.

An alternative to KPIs

“Tradition becomes our security, and when the mind is secure it is in decay.” – Jiddu Krishnamurti

Organisations emerging from the industrial revolution were traditionally organised into hierarchies, made efficient through the separation of concerns, and measured using well recognised KPIs (key performance indicators – such as cost and time). This approach proved very effective for stable business sectors that had reached a high level of maturity and was recognised as the standard way of running a business.

The internet, however, has created significant market disruption, and the rate of change across many businesses is still rapid and promises to remain so for the foreseeable future. To respond to this ever-changing environment, a new way of setting targets and prioritising work has emerged that removes the need to micromanage every task and function. Made popular by Google, this technique is generally referred to as OKRs (Objectives and Key Results) and, unlike the more static KPI approach, it adopts a rapid review cycle and a focus on group responsibility. 

This is why we chose OKRs as our method of choice for linking strategic goals to delivery activities. At Equal Experts, we are experienced at bringing about change and OKRs are about delivering that change, not about maintaining the status quo.

Essentially, the OKR approach aims to achieve three outcomes:

1. Align task execution directly to company strategy
   When the tasks being performed by a team or individual are far removed from the strategy that gave rise to those tasks, the reason is lost. All too often, teams successfully complete these tasks but somehow manage to completely miss the strategic point. By linking tasks directly to core company goals, OKRs help to ensure that the “doers” understand the purpose and value of their efforts.
2. Create transparency
   Where teams and departments operate in isolation from one another, and when their work is hidden from the rest of the organisation, duplication of effort proliferates and waste is high. The OKR approach endeavours to create transparency so that unintended duplication can be avoided.
3. Encourage collaboration
   There is little incentive to collaborate when overall goals are divided and cascaded down to teams, and then divided further to individuals. By creating objectives at the team level, rather than measuring the success of each individual, collaboration can be encouraged rather than discouraged.

Goals: Setting the strategic direction

“The best way to predict your future is to create it.” – Abraham Lincoln

The starting point for our stripped down version of the OKR approach is to establish the core goals for the organisation. These goals typically manifest as a handful of statements that embody the overall purpose and intent of the organisation; they are high level, direction setting, and likely to create an element of conflict when taken as a set.

For example, a company might have as two of its goals, ‘be profitable’ and ‘be ethical’. There are many ways to be unprofitably ethical and many ways to be unethically profitable. Taken together, however, the number of options available to the company is reduced. Thus, through a small number of well-defined goals, a company can create a clear strategic direction.

Constraints may, at first glance, seem to limit innovation and progress; in practice, they help to focus attention on the changes that best align with the strategic direction of the company, thus facilitating faster and more effective decision making.

Goals are long-lasting (at least a year, and generally longer), and they form the first layer in the OKR hierarchy; there is only one more layer.

Objectives: A call to action

“Nothing will work unless you do.” -Maya Angelou

The real driving force behind the OKR approach are the objectives themselves. Objectives are the things you are going to achieve; they are time-based (typically to be concluded within one or two quarters), qualitative in nature and aspirational. 

An objective should clearly state an outcome, rather than an action or deliverable. “Build an application” is not an objective, but “Ensure our customers are engaging more regularly with our service” might be. This may seem like a small distinction, but it has a big effect; by focusing on outcomes you empower teams to use their skill and judgement to deliver success, rather than just complete tasks.

Each objective must link back to one of your goals, whilst conflicting with none of the others. If an objective seems to link to more than one goal, it is likely that you have combined more than one outcome into a single objective. This is not advisable as there will be a conflict of focus when attempting to deliver the objective.

Objectives form the second and final layer in the OKR hierarchy. Objectives should not have sub-objectives, nor should they be cascaded to sub-teams to create further related objectives. It should, therefore, be clear that objectives need to be assigned to multidisciplinary, empowered teams and not distributed to individuals. Anyone who is needed to make the objective successful should consider themselves part of that team.

Key Results: Measuring success

“In many spheres of human endeavor, from science to business to education to economic policy, good decisions depend on good measurement.” – Ben Bernanke

If the intent is to deliver successful outcomes, then there needs to be a way of measuring that success. All too often, progress is measured in terms of tasks completed or widgets delivered; this is not the purpose of key results. Each objective should have at least one key result by which its success is measured.

A well defined key result is numerical in nature, defines a specific target (either relative to a current baseline or absolute), and measures an outcome rather than the tasks undertaken to achieve that outcome. Additionally, care should be taken to select key results for which you can “move the needle” within the timescale of the objective. If you’re not going to see any movement in the measurement over the next quarter or two, then it is not going to be an effective way of guiding your actions and refining your approach.

Examples of key results might include “50% of new users return within 2 weeks” or “Churn rate < 2% this quarter”. An example of a poorly defined key result might be “20% more prospects contacted” as it measures the level of activity and not its success.

Establishing a cadence

“Nothing is ever so good that it can’t stand a little revision, and nothing is ever so impossible and broken down that a try at fixing it is out of the question.” – Rebecca Solnit

Establishing, monitoring and renewing OKRs is an iterative process, and once you have defined and assigned your objectives you need to establish a cadence for reviewing them. A typical cadence is as follows:

1. Plan quarterly
   Review all your current objectives, remove those that are no longer relevant or that have been completed, and create new ones for the next quarter. Some of these new objectives are likely to evolve out of previous objectives allowing you to take your success to the next level, or change tack in response to unexpected results.
2. Amend monthly
   The whole point of OKRs is to continuously improve based on your findings. It is therefore worth revisiting your objectives on a monthly basis to see if any are flawed and need to be adjusted to improve your chances of success. 
3. Report weekly
   Measuring your key results on a weekly basis and reporting on progress improves transparency across teams, and also allows you to test-and-learn as you progress. It is easier to know which actions produced which results if you measure at a granular level, rather than only on completion of the objective.

It is then up to the assigned teams how they deliver, and the tasks they perform to achieve that delivery, but as objectives are short lived, explorative and iterative in nature, agile techniques are usually well suited to their delivery. This is because OKRs are about change and improvement – for existing processes where change is not needed or prioritised, existing techniques should still be used to measure their success and efficiency.

The art of introspection

“You will only fail to learn if you do not learn from failing.” – Stella Adler

OKRs are simple in nature, but any change, no matter how small, is always hard to embed in a lasting way. This is because old habits are hard to break, and so it is essential that during the early stages of introduction, you revisit the rules for objectives and key results in this document and make sure you are applying them consistently. Otherwise, it is highly likely that you will drift back towards an existing KPI based approach. Three of the common mistakes made are:

1. Cascading objectives so that teams can create “subordinate” objectives of their own.
2. Measuring tasks completed rather than outcomes achieved.
3. Giving every objective to everyone, rather than assigning them to responsible and empowered teams.

Don’t expect to get this right the first time; no-one does. But don’t forget to learn and improve either; that’s the point of iteration. We have a tried and tested approach to putting OKRs into practice, so if you’re interested in doing this either experimentally, or at scale, drop us a line at strategicadvisory@equalexperts.com  and we’ll see what we can do to help

In Part 3, we will introduce our Roadmap Radar tool, which allows you to visualise your entire portfolio of work in a way that creates clarity, agility and collaboration.

 

Part 1 – An agile strategy for an unpredictable world 
Part 2 – Shaping the vision – (you’re here!)
Part 3 – The Roadmap Radar – When is a plan not a plan?
Part 4 – The Bet Canvas – Nothing ventured, nothing gained

To evolve is to survive, and to plan is to succeed, but all too often, plans are static whilst the world is ever changing. In this four part series, we propose a tried and tested approach that introduces quarterly agility into your organisation without losing sight of your long term goals.

Iceberg! Right ahead!

“No plan survives contact with the enemy.” – Helmuth von Moltke the Elder

Here at the Equal Experts Strategic Advisory Practice, we recognise that stability is an illusion, and steady state is a temporary luxury. Any attempts to create and stick to long term plans are inevitably doomed as they fail to adapt to the world around them, or take account of the discoveries made once the journey has begun. 

This doesn’t mean you can’t have long term goals; quite the opposite, but to assume you can decide today all the actions necessary to get there is folly. It is no more realistic than standing in Liverpool, pointing a ship at New York, setting its course, and hoping it will arrive at its destination unharmed with no intervention from the captain. Decisions have to be made, events adapted to, and courses changed.

Instead, you might think of strategy as being a sailing boat in high winds, crewed by a group of people with different but complementary skills, who have the autonomy to make adjustments quickly, in coordination with others, according to the conditions.

After all, sometimes there are icebergs.

Seasons come, seasons go

“In the depth of winter, I finally learned that within me there lay an invincible summer.” – Albert Camus

Of course, we acknowledge that businesses need a plan, but the duration of such plans is shorter than you might think. Consider those 2020 vision documents produced by most organisations, some as long ago as 2015. We have seen very few of those plans that made it past the first year without becoming irrelevant, and not surprisingly, none included the impacts of a global pandemic followed by a recession.

In our experience, the most effective cadence for planning is quarterly. It fits well with company funding cycles, and is short enough to allow course corrections within the financial year. It also fits well with a more fundamental cycle that affects human motivation in a way that few people recognise. There are, of course, the recognised impacts of season – the January blues, flu season, holiday seasons and so on – but there is something more fundamental. 

We humans work in seasons, measuring the end of one and the start of another. Traditionally, we had to align tasks to these seasons to ensure our crops were properly planted, tended and harvested, and our hunting behaviours adapted to the migratory patterns of animals.  Even now, in our sanitised world, we see the seasons as natural start and end points, and yet at work our projects often continue on unbroken throughout the year. As the weeks turn into months, and the end seems far away, it can be hard for us to remain motivated, and productivity starts to fall. People lose focus.

We have found that moving to a quarterly cadence, where outcomes are achieved and teams move on to the next challenge every three months, can avoid this slump. A clear break every three months give teams a fresh boost and renewed focus. This doesn’t mean you have to abandon what you’re doing; just create a clear “cake and candles” moment to celebrate success. Then you can reset direction and go again based on what you’ve learned and what has changed in your business landscape.

Switching to a quarterly cadence means you are discovering all the time and are giving yourself the space to continuously adapt your plans. That’s why we follow an approach we call Continuous Evolution.

Ninety days to done

“Learning is not attained by chance, it must be sought for with ardor and attended to with diligence.” – Abigail Adams

Breaking out of a tightly planned and predictable way of working can be very challenging. Our Continuous Evolution framework helps guide an organisation through the unknown, no matter what factors are driving the need to change, or the kind of transformation required. The aim is to build an agile and iterative strategy, in pursuit of the surest and quickest path to business value. Making well-planned interventions and measuring their impact is the key to creating the right mindset and high performance culture capable of rapidly delivering sustainable change.

Working in 90 day cycles, this three stage framework exists to: 

1. Shape – Establish the goals & objectives of the organisation, as well as the best ways to measure progress towards them (Objectives & Key Results)
2. Plan – Visualise how time-bound activities are aligned to the strategic priorities of the organisation, indicating clusters and gaps (Roadmap Radar)
3. Execute – Gather, prioritise and place ‘bets’ that are designed to realise business value through experimentation, maximising returns whilst minimising the exposure to risk (Bet Canvas)

At the end of each 90 day cycle, leadership should reflect on the progress achieved, and lessons learned.  That allows the organisation to revise to their OKRs and Roadmap Radar as required, before deciding (a) which bets to evolve or stop; and (b) which new bets should be placed during the next cycle.

Stage 1: Shaping the vision

“The only limit to our realization of tomorrow will be our doubts of today.” – Franklin D. Roosevelt

There’s a lot more to strategy than simply feeling your way through experimentation, and we have discussed this in previous blog posts. However, there’s also a lot more to strategy than thinking and talking – effective strategy arises from situational awareness and insight, and these can best be discovered through hands-on experience.

Not great fans of reinventing the wheel, we use OKRs (objective and key results) as the first step in the Continuous Delivery framework. However, we did strip that particular wheel back to its basics so that it could be easier for organisations to adopt and adapt it to their own needs. We find that OKRs provide a flexible, collaborative method that ensures activities are aligned to the strategy, across the organisation, whilst optimising the time spent on this activity.

The advantages of the OKR method are:

• Strategic priorities are discussed and agreed by leadership, including the establishment of long-term goals 
• It provides assurance that the various aims of the organisation do not conflict with or contradict one another
• It ensures the goals and objectives of the organisation are clearly understood at all levels, through regular communication 

This transparent and non-hierarchical approach to strategy helps deliver change, by creating a shared understanding of the organisation’s long-term goals, before aligning a set of measurable objectives. Progress towards each objective (and therefore goal) is measured by Key Results, with outcomes reported to the whole business in a regular cadence. 

Stage 2: The Roadmap Radar

“Mann Tracht, Un Gott Lacht” – Anonymous

Literally translated, “Man plans, and God laughs”. It’s an old Yiddish adage and it carries a lot of hard learnt wisdom in its brevity. It sums up the fragility of detailed plans in the face of uncertainty, unpredictability and the unknown. But any venture involving more than a handful of people needs some form of plan if it is to avoid descending into chaos and conflict, and that’s why we’ve created a unique tool that carefully balances the need for direction with the importance of agility and empowerment. 

The Equal Experts Roadmap Radar provides an intuitive view of the goals and objectives of the organisation, with initiatives plotted on the radar to indicate clusters and gaps in effort. It’s simplicity allows everything to be shown on a single picture, and the ease with which it can be changed encourages flexibility to changing circumstances.

The advantages of the Roadmap Radar are:

• It creates a portfolio of prioritised bets, to help the organisation decide where to go next, with confidence
• It aligns effort directly to the organisation’s strategic goals, providing teams with a greater sense of purpose and meaning
• Once misaligned activities are placed into the backlog, multi-disciplinary teams can be more effectively formed by bringing together the right, motivated people.

Once the goals and objectives of the organisation have been affirmed through the OKR process, efforts can be plotted as ‘bets’ against each objective, laid out to indicate a timeline for delivery (in this quarter, in the next quarter, etc).  By visualising the balance of effort, any prioritisation decisions are radically simplified. 

Although the Roadmap Radar shows four quarters, the only certainty is in the first of these. Everything beyond that is conjecture; sound conjecture based hopefully on best available knowledge, but conjecture nonetheless. Each sector represents an objective that can be pursued by a team, independently of the others. This reduces cross-team dependencies, allowing greater empowerment and increasing motivation.

Stage 3: The Bet Canvas

“You will have to experiment and try things out for yourself and you will not be sure of what you are doing. That’s all right, you are feeling your way into the thing.” – Emily Carr

The way we approach the “doing” part of the Continuous Evolution cycle is through the use of highly structured “bets”. These outline how experiments will be designed, how success will be measured, and the challenges and risks that will be faced. Bets are delivery focused, and are guided by continuous feedback loops.

The benefit of the “bet” approach:

• A bet is a specific idea whose value is tested methodically through experimentation, optimising the return of business value whilst minimising exposure to risk
• Each Bet Canvas includes a time-bound experiment, with a plan for how evidence of the impact will be gathered and analysed 
• The progress of each bet can be reported regularly (at least weekly) and allows the riskiest assumptions or least well understood things to be tested quickly

The purpose of each bet is to (dis)prove a hypothesis through experimentation, which in turn links to an objective, which aligns to a strategic goal.  The language of ‘bets’ is intentional – how much time, effort and resource – that could be spent elsewhere – are you willing to commit to the exploration of this idea?  Some ideas require more investment to prove than others, and some are better understood and therefore require less validation. As a result, not all bets are equal.

The Bet Canvas ensures that each bet has a clear and rigorous structure, and can be displayed for all teams to see and add suggestions, comments, and questions.  It also guarantees a consistency of approach, whilst also highlighting unknowns, which allows for easy and regular reporting of progress.

Rinse and Repeat

“Yesterday I was clever, so I wanted to change the world. Today I am wise, so I am changing myself.” – Rumi

As bets conclude value is generated and lessons are learnt. With that increased knowledge and released value, the organisation can enter the next discovery cycle better informed and focused. How many times should an organisation repeat this process until it reaches steady state, and when does business as usual resume? The answer is, when the world stops changing, you can stop discovering, and until then, discovery IS the steady state.

In Part 2 we will discuss the OKR approach in more detail and give you a taste of how we facilitate OKR sessions to get the most out of them.

 

Part 1 – An agile strategy for an unpredictable world – (you’re here!)
Part 2 – Shaping the vision
Part 3 – The Roadmap Radar – When is a plan not a plan?
Part 4 – The Bet Canvas – Nothing ventured, nothing gained