Leadership in an age of abundance

Automation transforms the priorities - and therefore the skills required of - the leaders in a new age of abundance.

By offering limitless low-cost labour it provides:

1. Immediate abundance of capacity.

2. Learned abundance of capability.

Before the opportunity to automate - particularly the opportunity to engage ML/AI-infused automation - successful management was all about control and direction of constrained and relatively fixed capacities and capabilities. These primarily existed in the employee cohort.

Over time this extended to out-sourced cohorts which offered a little more flexibility - but essentially capability and capacity resided in the people you directly or indirectly employed.

The scarcity of labour made the wise and timely allocation of it an essential business skill. That created an entire industry of strategic planning, roadmaps, business case development. HR and logistics to identify the need for new capacities and capabilities and scale up (and down) accordingly.

Pre-digital it was ok to have five-year plans. Digital typically thrust an annual cycle on leaders; the combined effect of the cloud and of globalization has already been to rapidly close any gap a 'strategy' may initially provide by way of competitive advantage.

With automation, there is no cycle. Leaders can summon up or switch off entire new swathes of digital workforces in seconds. Enabling this friction-free recruitment and redundancy through the cloud and appropriate pricing models is the near-term competitive battlefield for automation vendors.

And it closes the enablement gap between strategy and execution in ways 20th century leaders could only dream of.

But it also threatens some fundamental relationships between the organization and work. How many times have we heard leaders proclaim 'people are our greatest asset'. Now our leaders command a digital workforce - to both do the grunt work and augment the decision-making and creative delivery of their human teams.

Today's leader must become skilled in directing an automated workforce to deliver on decisions made by a human workforce, augmented and amplified by their digital peers.

Their choices are less about how many people they direct to to do what, and more about carving out the differentiation that informs what data they seek, where from and how it is interpreted for insight.

With so much data available to understand needs and wants, so many systems available to listen-learn-respond to those needs and understand customer contexts, and such limitless low-cost labour to deliver vs those needs in more and more customised configurations, business process operations will be honed  in ever-improving, self-learning and natively automated iterative cycles.

Recognising and assembling the technologies to do this (as described by the OneOffice Emerging TechPlatform) at least places the enterprise on a level playing field with all the others that are smart enough and fast enough to recognise how digital transformation gets out of a strategists head and into the systems of the organisation.

Make no mistake, first-mover does offer an advantage here. The first to set their systems of learning rolling will accelerate their self-improving processes, and get faster and better at doing so - opening a gap that laggards will find hard to close.

But it is in the will to break down silos, in the quality and systemization of change, the emphasis on scaling their organisational digital fluency, and in the selection of a domain to extend expertise in, that competitive differentiation will emerge.

These then are the areas in which tomorrow's leaders must accelerate their skills. Not all come naturally. Selecting the domain comes down to legacy purpose or establishing one. This is where vision and belief come together to encompass both goals and ways of working to attract employees, partners, and customers and to inform and be reflected by the algorithms of the business - as much part of your brand as anything.

This will require a step-change in the embrace of data and insight for decision making, driving process and supporting the employee and customer experience.

Tomorrow's C-suite must be skilled and able to coach their intelligent automation processes to assist and complement their expertise - just as much as they coach their human reports to better support them in the future.

They must learn to trust in, and act on, the new opportunities their systems of anticipatory insight present them. They must accept that much of judgment now resides in backing the real-time data - ready to press the go-button on instant new divisions of digital labour to take advantage.

For some, the trust will only come when they understand and believe in the decisions embedded in the processes that deliver that data. They have to go on their journeys of discovery right now. Because before long we will stop talking about lucky generals and ballsy decisions.

The complete leader will be an insight-led pragmatic decision-maker, combining a scientific approach to data with the emotional intelligence, imagination and empathy to guide both people and bots towards an intended future in which the shared values and concerns of the humans engaged are brightly and clearly reflected.

Photo by Raphael Rychetsky on Unsplash

The Great Backlog clearance. Building stuff people used to need.

We are in the midst of the Great Backlog Clearance. Innovating backwards.

Granted - there is some smart, future-creating innovation being driven in pockets, but the majority of commercial activity right now has defaulted to a realisation that all that stuff we had been happy adding to backlogs, feeling in the rush of pre-Covid BAU that it could wait, we now realise is an urgent must have.

We've been generating quite a long-list for several years. Now a lot of organisations are hurtling head-long through their to-dos in a game of digital catch-up.

Hence the market demand for people who can make the stuff on that to-do list. Coders, engineers. Nuts and bolts folk. Of course, as the backlog becomes the product to ship, you then need folk to sell it. Hence the current demand for people to sell stuff you've made.

So - people who make the stuff you are in a dash to catch up with. People to sell stuff when you make it.

When you are clearing the backlog, what you don't need is people to tell you what needs to be made. There's so much to do, already, right?

Hence the lack of demand in the insight-to-innovate space.

While this may feel like the appropriate response to difficult economic circumstances, it is, instead, a short-cut to mid-term decline. Dealing with the backlog is dealing with past demand, generated in the context of a different (pre-Covid) world. One which is changed for a minimum of three years and perhaps forever.

You are building responses based on invalid insight. You are innovating backwards. You are building things people used to want. That may feel like you are getting stuff done, but it is not serving the new needs of the new contexts. It is supply to an out-moded demand.

The Responsive Organisation is seeking to build better from change. It is not looking at what it should have done in the old context. It is seeking to understand the new contexts, imagining the experience of its customers in the new, next and possible contexts of the now and next system we are feeling are way through. And it is moving fast to serve those new needs.

It is asking itself, what needs to be made now?

It is enabling the mindset, ways of working, collaborations and commercial approaches, and access to technology, to deliver best-fit solutions for the new and next nows.

So if you are busying yourself building out your pre-Covid backlog - stop. 

Reassess your backlog; revalidate the insight; start from live understanding of need in new contexts, to press the go button on your insight-to-innovate investment. Start responding to now and next.

Lift you head up, look around. You're not in Kansas anymore.

Photo by Brett Jordan on Unsplash

It never was all about the economy -stupid

Context Shocks - as Covid19 demonstrates time and again - reveal trends that the system was already aligned to generate.
We have seen it in distributed working, reimagining of the city, targeted education etc.
Another very significant one reveals itself in the level of state intervention required when markets fail in their primary task - to allocate resources vs human need.
This is an interesting challenge to the western political hegemony - in which the tendency is toward 'In The Market We Trust'. It has seemed there is no problem the market couldn't handle.
But rather like a Prime Minister 'taking personal control' of any and everything that appears to be going off the rails, it turns out - somewhat ironically, that the market only has a limited amount of political capital to spend. And it is all spent out.
The massive scale of state intervention around the world (another £100bn of quantitative easing announced in the UK yesterday) reveals a trend to truth - that the role of The economy is subservient to the Government, not the other way around.
The capacity and necessity of massive state involvement illustrates this truth.
And this trend to truth reveals another, just as important. The state intervention is to meet the needs of people. Given our perilously constrained resources - it is also to meet the needs of the planet. There's no people, government or economy without the planet.

So, the content shock of Covid19 gives us a new context in which to experience, and in this new experience we can imagine, and are starting to observe:
The role of Government is to gather insight about the needs of people and planet.
The role of the economy is to gather insight about the needs of Government and the needs of people.
The role of the economy is then to respond to the needs of Government (and people and planet)
The role of Government is then to respond to the needs of People & Planet.

With this we do at least have a simple way of describing the systems goals. Feedback loops flowing between people and planet, between Government and Economy and all combinations thereof will need to be understood and managed in order to steward the right outcomes.
But at least we can establish some clarity about who and what the outcomes are intended to benefit.
It never was about all about the economy - stupid.

Why we should embrace GDPR

The General Data Protection Regulation due to come into force next May should be regarded as the biggest hint yet for companies to reshape themselves for the digital world - aligning with The 10 Principles of Open Business.

Rather than fear at the number of sticking-plasters that need to be applied to support business as usual, forward-thinking companies will be taking the hint; data ownership is no substitute for genuine relationships.

That's the real message of GDPR - stop hoarding data to exploit customers.
In fact it's very difficult to see in a post GDPR-world why any customer would choose to allow a company to retain their data unless (and they have to be transparent about this) their is a genuine and positive partnership defined in their data notices.

Of course companies can (and many should) spend time, trouble and money ensuring compliance by (for example);

• Appointing a Data Protection Officer
• Reviewing each and every business process to ensure data protection is designed in
• Ensuring default privacy settings are set to high at each and every touch point
• Making it crystal clear exactly what data is being stored about whom, for how long and for what purpose - at every relevant interface
• Providing complete data portability - enabling users to withdraw access to all of their data and take it with them, at any point they choose,
• Devising Data Protection Impact Assessments
• Developing new processes to respond to requests for data and complaints about use
• Preparing to defend your use of logarithms for the decisions they deliver and offers they make or do not make

With up to 4% of last year's global revenue at stake as a sanction, there's much sense in taking this very seriously indeed. However, much of the data storage, privacy and permissions issues become much less onerous if you shift  the nature of your relationship with customers - and in doing so your relationship with their data.

Start to think of data as less a substitute for a relationship - and more an enabler for building one through genuine engagement. 

The start point requires three simple steps:

1. Understand the role of the customer in your business: (Hint - the passive consumer no longer exists, if they ever did).

• Where are the benefits in partnering; how far into the centre of the organisation can customers be brought
• How do you score for trust?
• Set a new goal state, roadmap for organisational change and supporting technology architecture

2. Why do you want to know more about your customers - what is driving you to build engagement?

• Is it to build trust?
• Get direct insight?
• Get help in decision making?
• Find savvy co-creators?
• Deliver a better experience, better serving need?

3. Now you should devise a customer data strategy;

• What data could be available to you – what can you learn from customer interactions? 
• What value for third parties and customers could that generate 
• Consider role of Decisioning (NBA)

By now you have a handle on what you want to achieve with customer data and how you are going to 'sell' that to customers in a way they will see as a fair exchange.

And that's a far better place to start from when working towards compliance with GDPR.y 2017

*This is always the case with my writing - but given the legal complexities of the GDPR I want to make it even more clear than usual - these views are mine and mine only and should not be assumed to represent those of my employer.

Insight in a Columbo-stylee

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Big thanks to David Armano for pointing us to his colleague's work via twitter