Predictions for the new year are something of a fool’s errand, but stepping back and looking at some of the topics that have crossed my newsfeed in 2014, I think there are two current trends that will start to have an impact on how work is organised in 2015, and two others that will likely come into sharper focus, although they will take longer to play out in practice.

Practical solutions to management inertia

The first issue I think we will see come to the fore in 2015 is the need for practical workarounds to prevent dominant management culture holding back organisational improvement and agile working. Whilst there are already some visionary leaders creating protected spaces in which new ways of working and collaborative methods can thrive, the bigger question is how we can build the requisite skills into management education and practice as a matter of course. We have seen such a plethora of articles and studies in 2014 suggesting that current management culture is one of the biggest factors holding back efforts to create more agile and responsive organisations, but so far not much in terms of practical solutions. I think that will change in 2015.

The problem is not just cultural. There are key management processes baked into existing structures that will have to be tackled, or at least routed around, if new ways of working are to have a chance. Budget setting, planning cycles, employee appraisals and overall performance management may sound like simple and solvable issues, but they are so central to the way that large organisations work today – and so central to their politics – that reforming them is not for the faint hearted, despite the huge benefits that can accrue from doing so.

Giving everyone a role in organisational improvement

A second issue that has been bubbling up in 2014, and which I think will hit the management agenda this year for both startups and large firms alike, is how to involve change agents and local leaders across the organisation in helping to design and improve their own organisational structure, philosophy and practice, rather than just expecting them to work within the standard boxes-and-arrows org chat template that is handed down to them.

For startups that are serious about scaling, following the example of small high-value teams is a better way to go than seeing themselves as nascent mini-corporates, but even so it becomes challenging to coordinate fast-growing teams without reaching for the old tools of departmental management and reporting lines. The first step is to develop an awareness that choosing the right structure, and developing the right culture, needs to be on the management agenda from day one and is just as important as choosing a technology platform or a brand identity.

For large organisations, the key priority is to have a target operating model in mind to drive towards when planning technology, innovation or change initiatives, and to build a view of the organisation’s capabilities, readiness and progress towards this goal into regular reporting cycles. Just as we already monitor various lower-level health measures in technology, individual performance and plant machinery, I think we will see higher level organisational health measures become part of weekly and quarterly management oversight.

One factor that has prevented this in the past has been the fact that organisational change was seen as the concern of only the C-suite – and especially incoming CEOs wanting to make their mark – or external consultants who are brought in to shake things up. Top-down change-as-a-major-initiative has rarely worked, and I think the penny has finally dropped that unless we find a way to distribute ownership and accountability for the shape of the organisation, and how to change it, then little progress will happen. This challenge will be a major focus for our company in 2015 as we make our methodology and tools for managing progress towards new ways of working more widely available.

Looking beyond the immediate horizon to bigger changes in the way we think of organisations and how they work, two emerging topics look set to have an influence on the future.

What sort of org structures work for people, machines and real-time data?

The first is about data – not the ‘Big Data’ that is rapidly becoming a business jargon cliché, but increasingly distributed small, real-time data. The loosely defined field of ‘big data’ began with a rather centralised mainframe-type approach to data gathering and processing, but that is looking unsustainable for real-time use cases that are not about needle-in-a-haystack pattern identification. We are starting to see a distributed approach emerge, whereby certain aspects of collation, processing and insight generation happen closer to the edges of the organisation, where they are most needed, whilst the big picture pattern matching happens not in a single system, but rather in a shared data pool (or ‘lake’) that various apps can dip into.

As Ron Miller wrote in Techcrunch recently:

“What we don’t want to do in a day and age where we need answers quickly is to create a guru bottleneck where we go to an expert to get the answers, then wait for the results.”

“…predictive analytics are improving all the time, and sometimes the data points straight at an answer, but it still remains a complicated mix of human and machine and how this all comes together is very much a work in progress, even as the technology marches forward.”

“Until we find that balance or it tips sharply in the favor of machines, we face a big wisdom gap and that will take some time and technological advances to fill.”

A distributed approach to data processing, combined with a steady increase in the number of internet-connected ‘things’ and machines talking to each other and to people, poses all kinds of interesting questions for organisational design. How can we make the best use of human intelligence and machine-generated data in a distributed system with the widest possible scope for local action? Also, given that the velocity and volume of data informing decision-making would overwhelm conventional reporting lines and centralised processes, how can we enable people to operate more autonomously at the edges of the network in response to changes they sense in local data?

But there is also a bigger question: what sort of organisational structures will be appropriate for a mixed population of humans and data-sharing machines or connected ’things’? How will the rise of data-driven approaches to performance measurement, decision automation and applying intelligence at the edges impact on the very nature of the firm? 

Some of the changes we might expect to see in how large organisations use data are laid out in an O’Reilly ebook by Alistair Croll entitled Data: Emerging Trends and Technologies:

  • Fog computing – the cloud de-centralising to the edges, with data being processed and intelligence generated at a local level
  • IoT moving from dumb devices that share their data with centralised services, to smarter variants where more processing happens on-device
  • Simple local machine learning, at least for pre-processing and flagging of patterns and outliers
  • Cognitive augmentation – people are still the best sense makers, but better presentation of data can help them do this more effectively
  • More focus on real-time actionable data rather than ‘big’ data – this is where machines can do things that people cannot

All this has architecture implications for technology, but also for the organisation. In the future, we will need to understand what sort of organisational structure works for machines sharing vast amounts of real-time data with each other, as well as with their human colleagues.

Beyond Uber: towards the distributed autonomous organisation?

Finally, and perhaps even slightly further out, there is the question of whether large companies will continue to exist at all in the form we know today, regardless of whether they can reform and stay competitive.

In several talks last year, I began by asking what it means when Ronald Coase’s theorem – essentially that a firm exists to minimise transaction costs within its structure – is no longer true in an increasing number of cases, where the internal realm of large enterprises no longer provide a cheaper or more efficient means of coordinating resources than the external market, and when small startups are able to orchestrate their own supply chains on the open market to deliver products and services that beat those backed by the resources of large firms. If indeed, many companies are effectively resource allocation markets, then we already have the technology to organise and optimise them better than ever before, as all kinds of examples from Amazon to Uber are demonstrating, although we are still working out what that means for workers.

The current wave of companies like Uber are probably transitional. They are very assymetrical, accruing all the benefits of a corporate legal and financial structure (including an absurdly high valuation for a distributed taxi firm, however efficient it might be) but passing the risks on to their workers and suppliers. These firms are looking more like robber barons than a new class of corporation, and seem to be throwing up a number of ethical issues. In the UK we have seen similar dynamics in the collapse of City Link, where the private equity investors were not even investors, but just providers of secured loans with liquidation preference over unpaid workers (many of whom were actually non-independent, i.e. tied to City Link) contractors when they pulled the plug. Not a great advert for a model of workers as independent contractors.

The long-term direction of travel for the type of firm seems to be towards distributed organisations. Frederic Laloux wrote about one very human-scale distributed organisation in the form of the Dutch nursing organisation Buurtzorg, which has scaled successfully without the need for a centralised structure. This distributed model has worked well in a context where human-centred methods are key to providing a better service, and where participants have a high degree of mutual trust and common purpose. But it might not work so well in many areas of commercial business.

But what has been dubbed the second wave of blockchain innovation (the technology that underpins Bitcoin and other distributed currencies) could perhaps provide another way to achieve this, and indeed go further towards the concept of Decentralised Autonomous Organisations. The blockchain can not only form the basis of smart contracts, it could also provide a trusted mechanism for automating supply chains and resource allocation that goes beyond an individual organisation and, in theory at least, require no management beyond control of the algorithms. Companies like Eris Industries are already working on a distributed application stack that can create serverless decentralised apps on top of the blockchain, and others are already thinking about where these might take us in the future.

Looking ahead to 2015

Whilst these two long-term trends will not have a huge impact on the way business is done in 2015, I expect to see some more far-sighted companies begin to put in place some of the building blocks needed to exploit them. In the meantime, we will continue working away at finding solutions to the immediate management structure and culture issues that are holding companies back from utilising more lean, agile and responsive operating models, and hopefully developing better tools and methods to think about and manage the process of evolution towards new and better ways of working.