Moving from “Best Practice”
to “Next Practice”
How to drive effective transformation

August, 2018
(Originally published 2015)

ContentExecutive summary3

1. Complicated versus complex

4

2. Best practice versus next practice6

3. Conclusion

7Authors:
Carl Bate
Partner, Digital Problem Solving,
London & New Yorkbate.carl@adlittle.com>

Greg Smith
Partner, Digital Problem Solving,London
smith.greg@adlittle.com

This article originally appeared in Cutter Business Technology Journal, Vol. 28, No. 11/12, 2015 https://www.clutter.com/article/
moving-best-practice-next-practice-drive-effective-digital-transformation-489181. Republished with permission.

Executive summary
We are constantly bombarded with the message that we are living through a period ofunprecedented change; that technology is rewriting the rule book across all industries; that anyorganization that fails to fully master technology will become commoditized, obsolete, or extinct;
and that the only possible solution to these challenges is to implement the latest technologicalmiracle cure.
While we can discount the inevitable hyperbole — and, all too often, the self-interest — at theheart of these opinions, there is undoubtedly a foundational shift occurring in the information
technologies that underpin our businesses and organizations. We have not yet found a consistent
way to articulate this foundational shift; perhaps the closest we have come to a widely accepted
definition is the categorization of business technologies into “digital” and “enterprise IT.” Digital has
become synonymous with customer-facing technologies that embrace the world of social, mobile,cloud, big data, and emerging technologies such as AI, while enterprise IT remains the de facto
term for back-office and enabling technologies.
These two categorizations extend to different worldviews and ways of working, with theirrespective practitioners adopting a tribe-like mentality to self-identify. The internecine battle
between these technology tribes is a pointless distraction for most large-scale organizations. For
these businesses, the new digital technologies and approaches will need to leverage and exploit
the over 20 years of investment in enterprise IT if they are to fully realize their transformational
potential. New digital capabilities will need to build upon existing IT-enabled operational capabilities.
In this context, the scope of digital transformation needs to be widened to incorporate both theharnessing of emerging technologies and patterns and the genuine exploitation of legacy
technologies and services. However, we should be careful not to confuse exploitation of legacy
technologies with the application of so-called IT “best practices.” Simply replacing old enterprise IT
with new cloud enterprise IT by itself may not cut the mustard. We find this approach can often add
to enterprise IT complexity (as not everything gets switched off as expected), and even thesuccessful programs need to interact effectively with digital.
In this article, we will argue the past is a poor playbook for the future when it comes to delivering
real business value from technology. Whilst successful exploitation of legacy technologies is critical,
the best practices that the IT industry has promoted and applied for the last 20 years have littlevalue in this endeavor.
In a fundamentally changed world, technologists will need to embrace and adopt “next practices”1
if they are to be successful. Before moving on to this challenge, though, we first need to establishthat the situation we face as technologists has indeed changed fundamentally.
1The term “next practice” has probably arisen independently multiple times, but we were first introduced to the concept by C.K. Prahalad.

31. Complicated versus complex
Through the Cynefin framework, knowledge management
expert Dave Snowden has created a useful typology fordescribing the different contexts within which all organizations
and their associated technology functions operate. Snowden
defines and describes four primary domains:nn Obvious. The relationship between cause and effect isclearly identifiable and understood by all.
nn Complicated. There is an identifiable relationship between
cause and effect, but the relationship needs to be discovered
through analysis or investigation.
nn Complex. A relationship between cause and effect can be
identified in retrospect, but not in advance.
nn Chaotic. There is no identifiable relationship between cause

outcompete their rivals. But what happens when there is apossibility that it may start to rain during the race?
In this scenario, the F1 team needs to rely on a sophisticatedsense-and-respond mechanism, which does have an ability
to directly impact race outcomes. If you predict the weather
conditions better than your competitors, respond appropriately,
and carry out your pit stops perfectly, you will create a significant
opportunity to outperform your rivals. Unfortunately, though, theopportunity will be short-lived. Your competitors will very quickly
change their tires over to wet-weather tires and put themselves
back on a level footing. However, the same finely honed
capability will present another opportunity to outperform thecompetition if it stops raining, the track dries out, and you decideto revert from wet tires to dry ones.

and effect.
These definitions provide a useful framework for articulating
how the world has radically changed for most businesses overthe last 10 years and why the change is truly fundamental.
Over this period, the majority of businesses have moved fromprimarily operating in a complicated world to now having tocompete and excel in a complex one.
At the heart of this move from complicated to complex is
the increasing importance of human factors in all facets ofbusiness, and in particular the liberation of the customer, whois now increasingly able to operate as an independent actor,
with all the challenges and unpredictability this can lead to.
As a broad generalization, we are also moving from a worldof predominantly closed system interactions, which can becontrolled, measured, and codified, to a world of open systeminteractions, where we need to constantly sense, adapt, andrespond to emerging needs and challenges.
The interplay of complicated and complex can perhaps best beillustrated through a sporting analogy. In motor racing, a Formula
1 pit crew can change from dry tires to wet tires in less than
10 seconds — a complicated and highly orchestrated processthat is analyzed rigorously and practiced obsessively to ensure
reliable execution in race conditions. However, all teams havebroadly similar capabilities, and whilst a failure in the ability tochange tires faultlessly can certainly cost a driver his position on
the winning podium, mastering the complicated tire-changing
process does not allow the driver or his team to significantly

4

In this example, we are primarily operating in a complex, opensystem domain, where external factors (precisely when willit start to rain, how heavy will it rain, what race strategy thecompetitors will adopt) can have a major bearing on successor failure no matter how good the driver and team are at theaspects that they control (driving the car, changing the tires).
Choosing the right strategy is critical — but then the chosen
strategy needs to be executed perfectly. Mastering the complex
allows a team to create a race-winning opportunity; mastering
the complicated allows the team to seize the opportunity.
When we start to look at our businesses through a similar lens,
we see that the truly game-changing opportunities or challenges
we face are also a blend of the complicated and the complex.
Being able to understand the difference between the twodomains and manage accordingly is thus the key to success.
An inability to differentiate between complicated and complex
leads to one of the most fundamental causes of business andtechnology failure — the illusion of control.
Too often we believe we can precisely predict the outcomeof our projects and actions because we have created detailed
execution plans; we have a strong grip on delivery; we havelocked down performance of external suppliers through precise
contracts; we have applied a comprehensive governanceframework; and we are obsessively measuring our progress.
Then we “go live” and things don’t quite work out as planned.
As we are all painfully aware, the track record of major
business technology projects delivering anticipated outcomes
and benefits is spectacularly bad, and yet we continue toslavishly apply so-called best practices and are still surprised
when another major technology investment fails to live up toexpectations.

are wholly unsuited to delivering successful outcomeswhen challenged with complex, open systems. Under thesecircumstances, we need to understand best practices but fully
embrace and apply next practices.

The fundamental challenge is that technology best practices
have been designed for complicated, closed systems and52. Best practice versus next practice
The need to move from best practice to next practice manifests
itself across multiple dimensions within an organization andat multiple scales, from individual activities to overall industry
ecosystems. Consequently, successful guiding principles, whichare required to help with the transition from best to next, need
to be able to inform and assist decision making within this“fractal” context.
At a summary level, next practice guiding principles can becategorized into four main dimensions:

1. Business leadership
2. Organizational and behavioral
3. Operational
4. Technology
The principles shown in Tables 1-4 below are drawn from alibrary of over 50 examples and are intended to illustrate how
principles can assist an organization in challenging conventional
wisdom and avoid reversion to “tried and tested,” which all toooften now is “tried and failed.”

The business leadership dimension
Best practiceManaging the complicated
Assumption that system is closed – Strategic plans assume
certainties with management focus and resources prioritized on‘delivering the plan’, which will often be multi-year in duration.
Failure to deliver the pre-determined plan is not an option◼ Internal focus dominant – Majority of management attention is on
internal factors (e.g. overseeing internal resources)◼ Metaphors and inspiration from engineering and physical sciences –Terms like ‘engine of growth’, ‘software factory’ and ‘themachinery of the business’ dominate, reinforcing a mechanistic,reductionist mindset and diminishing the attention and focus onhuman factors in the business◼ Strategy defines challenges (a priori) – Strategy, that is where weplay and how we win, is deterministic and the business isfocussed on analysing and then answering the question it sets
itself◼

Source: Arthur D. Little

Next practice
Embracing the complex
Assumption that system is open - Strategic plans assume
uncertainties and emergence, with management focus ondelivering the next part of the plan, deliberately assessing
feedback and constantly tuning resource allocation to deliver thepart. ‘Pivots’ are allowed, as new evidence is discovered thatchallenges the initial hypothesis◼ External focus dominant – Majority of management attention is on
external factors (e.g. customer and market feedback)◼ Metaphors and inspiration from biology and natural sciences – The
notions of emergence, memes (ideas and concepts that canself-replicate across the organisation) and discovery overinvention◼ Challenges define strategy (a posteriori) – Strategy is emergent
based on real world feedback, even if that doesn’t fit with theprevailing mental model the business has of its world. The
primary strategic questions to be answered emerge from a wide
ranging survey of data and insight and are unknown or partiallyknown before the analysis◼

The organizational and behavioral dimension
Best practiceManaging the complicatedCommand and control – Management always knows best andtells staff what to do, often in highly prescriptive ways withclose scrutiny◼ Hierarchies and chain of command – Decision making by who’s themost senior. Activities are directed and delivered throughresources that are perceived to be wholly under the control ofthe organisation◼ People are totally rational, calculating machines – Ways of working
and KPIs assume people are totally rational (based on
management’s view on what rational looks like)◼ Seek permission – Permission is required to undertake an activity
that is not preordained or tightly defined – responsibility is heldby the few◼

Source: Arthur D. Little

6

Next practice
Embracing the complex
Influence, enable and empower - Management creates overall
direction and principles and then empowers people to use theirtalents to deliver the best outcome in an emergent and often
unpredictable set of specific circumstances◼ Networks and shared incentives – Decision making by who’s themost qualified. Activities are delivered by a network ofresources with widely differing levels of direct control from theorganisation but with aligned incentives to ensure co-ordinated,
win:win outcomes◼ People are predictably unpredictable – Ways of working and KPIs
assume the business is more like an economy than a factory,
and that human factors (such as those defined by behaviouraleconomics) dominate. Individual actions may not be precisely
predictable but the sum of activities is stochastically reliable◼ Ask for forgiveness – Staff are encouraged to use initiative toachieve goals; but also to take responsibility for actions –responsibility is held by the many◼

1

The operational dimension
Best practiceManaging the complicatedStability and predictability – Management culture, KPIs andincentive systems are all based on predicting the future andthen precisely delivering to that prediction. Change is seen as
disruptive◼ Procedures, rules and routines – All activities are broken down into
discrete elements with staff then expected to precisely follow
specific procedures (although they don’t always seem to). Often
viewed by staff as centrally imposed and ‘getting in the way ofgetting the job done’◼ What has worked in the past – Actions are based primarily on priorexperience and learned behaviour◼ Measure and manage – Management is based on what is known
and retrospective analysis and reviews (e.g. month end reviews)◼

Next practice
Embracing the complex
Agility, emergence and adaptability – Management culture is basedon delivering value early and often, accepting emergent
phenomena, with self-disruption seen as not only to beexpected, but a positive◼ Algorithms, checklists, proxies and heuristics – Rules of thumb andtried and tested shortcuts to guide decisions, plus checklists for
specific activities. Proxies used to allow early insight into
performance of a system. Staff view tools as helpful andpersonal ownership◼ What could work better in the future – Actions are based primarilyon expertise and continuous learning, even if this challenges
prior successful ways of working and habits◼ Sense and respond – Management is based on continuously
seeking out what should or could be known and reacting in nearreal time to emerging situations.
◼

Source: Arthur D. Little

The technology dimension
Best practiceManaging the complicatedEstablished enterprise solutions – Technology strategy is primarily
based on well-known enterprise solutions and technologies;
governance is applied via rules and regulations, directing which
technologies can be used and how they are implemented◼ Change management – People are told what the new ways ofworking are and the assumption is that staff will adopt rationallyonce they have gone through required training andfamiliarisation◼ Up-front grand design and big bang delivery – Large scale programs
following significant periods of design without usage; team size
can be 100+
◼ Legacy as millstone to be replaced – Assumption is that legacy is
the problem and needs to be replaced wholescale to allow
major changes◼

Next practice
Embracing the complex
What would the web do? – Technology strategy is primarily basedon emerging technologies and consumer style solutions;
governance is via principles and patterns◼ Adoption engineering – Focus is on influencing changes in habit
and being in the shoes of the recipient, not mandating change
centrally; techniques like MINDSPACE and SCARF can be used
to allow users to self-adopt. Adoption of change is driven by“path of least resistance” and mimics users experience withconsumer technologies◼ Emergent requirements and incremental delivery – Smaller
programs with delivery early and often; team size tends to be 15
or less◼ Legacy as lodestone to be exploited – Focus is ‘what problem are
we solving for whom?’ and assumption is that legacy may bepart of the answer. Typically asks the question ‘what is theminimum we can change and still deliver the benefit?’◼

1

Source: Arthur D. Little

1

7

3. Conclusion
Feedback from early adopters of next practice has found that
this way of thinking helps make explicit the underlying trends
and disruptions we all experience in our daily lives but struggle
to articulate within the corporate environment — beyondlabeling them with the overused “digital” tag. However, wealso find that merely creating another tribe — this time a nextpractice one — only adds to the issues.

8We propose next practice as an “and,” not a wholesale
replacement for good and established practices. Most
fundamentally, it should be a way to help creativity, continuous
learning, and common sense prevail. We hope this article
has triggered a reaction — one way or the other! — and wewelcome the ensuing debate and challenge as part of theevolution of the next practice mindset.

Contacts
If you would like more information or to arrange an informal discussion on the issues raised here andhow they affect your business, please contact:

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lee.kevin@adlittle.com

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bamberger.vincent@adlittle.com

Middle East
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kuruvilla.thomas@adlittle.com

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baban.coskun@adlittle.com

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Fabian Doemer
doemer.fabian@adlittle.com

Netherlands
Michael Kolk
kolk.michael@adlittle.com

UKGreg Smith
smith.greg@adlittle.com

India
Srini Srinivasansrinivasan.srini@adlittle.com

NorwayLars Thurmann-Moe
thurmann-moe.lars@adlittle.com

USACarl Batebate.carl@adlittle.com

Moving from “Best Practice” to “Next Practice” –How to drive effective transformation

Arthur D. Little
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