Content uploaded by Allan H. Church
Author content
All content in this area was uploaded by Allan H. Church on Jul 10, 2017
Content may be subject to copyright.
You better start swimmin’ or you’ll sink
like a stone
For the times they are a-changin’
—Bob Dylan
If we have learned anything during our
collective years researching, practicing in,
and writing about the field of organization
development (OD) it is that change is a
constant phenomenon. In the 1980s we
had the Greek salad of change with alpha,
beta, gamma, and even omega in the mix
(Porras & Singh, 1986). In the 1990s it was
likened to whitewater rapids (Vaill, 1989),
in the early 2000s it had something to do
with the diminishing supply and move-
ment of one’s cheese (Johnson, 1998), and
over the past decade it has been all about
managing the clash of boomers, gen xers
and gen yers in the workplace (Zemke,
Raines, & Filipczak, 2000; 2013). It is a
cliché these days to start an OD article
with a statement that organizations are
in a constant and/or increasing state of
rapid change.
But that is because it is true. Organiza-
tions are experiencing change at rates we
have never seen before. The best analogy
today might be Moore’s Law from the
world of semiconductors. It is the asser-
tion that advancements in technology
double every 18–24 months. This law
has proven accurate for the past several
decades, despite several proclamations of
its death (something this concept shares
with the field OD) and has been applied
to other domains as well such as business
processes (Rawlings & Bencini, 2014) and
digital marketing (Dragojlovic, 2016). In
the context of organizations, we would sug-
gest that the rate and complexity of change
and the implications of those changes
are accelerating at a similarly exponential
pace. What matters to companies today can
quickly shift tomorrow.
Moreover, much of this change is
being driven either directly or indirectly
by advancements in technology. It is the
socio-technical (Trist, 1978) revolution all
over again. For example, in 2013 there was
debate over allowing employees access to
social media at work (Beasley, 2013). Today
many functions have hired social media
experts (they are in very high demand
in executive search) directed at advertis-
ing their products, watching for external
media impressions, and actively staffing
talent. The online traffic and opportuni-
ties for impact are certainly there. Dream-
grow reports that Facebook tops the social
media sites as of 2017 with 1.9 billion
visitors each month (Kallas, 2017). While
more targeted professional workplace
social media sites such as LinkedIn (peer to
peer business connections) and Glassdoor
(which features anonymous ratings and
comments regarding company reputation)
see fewer visitors, they are still at about 106
and 23 million respectively each month.
The potential for a poor senior leadership
decision or a botched change effort leaking
out to the public is beyond anything ever
imagined in the past.
If we think about the implications of
managing complex multi-year organiza-
tional culture change vis-à-vis social media,
“Our backgrounds as social scientists puts us at an advantage at understanding the true dynamics of
social systems yet our potential impact on the actions taken is diminishing. It is time to enhance our
skill set in these areas and direct our academic and professional programs to focus on this as well.”
Four Trends Shaping the
Future of Organizations and
Organization Development
By Allan H. Church
and W. Warner Burke
14 OD PRACTITIONER Vol. 49 No. 3 2017
one could argue it might be a completely
different process than in the past. The
extent to which OD practitioners are lead-
ing edge regarding the impact new technol-
ogies have on the nature of organizational
change is an open question. Moreover, in
the context of the HR and talent manage-
ment (TM) vernacular, the term organiza-
tional culture is often used interchangeably
with “employer brand” and “employee
value proposition” (EVP). Although not
particularly new (e.g., see Michaels,
Handfield-Jones, & Axelrod, 2001), these
are terms and related concepts nonetheless
that are far less familiar to OD practitioners
and probably worth some additional focus
as well on our part as a profession.
In the past, we have written about
change in the context of helping individu-
als (e.g., Burke & Noumair, 2002; Church,
2014), aligning large-scale organizational
change interventions (e.g., Burke, 2011a;
Burke & Litwin, 1992), and assess-
ing the capabilities of OD practitioners
(Burke & Church, 1992; Burke, Church &
Waclawski, 1993; Church & Burke, 1993).
We have also focused on describing major
shifts in the field of OD overall (Bradford
& Burke, 2004; Burke, 1976; 1997; 2011b;
Burke & Goodstein, 1980; Church, 2001;
Church, Shull, & Burke, 2016). Some
of those changes tend to reflect perennial
swings back and forth on a pendulum
(e.g., centralization vs. decentralization,
specialist vs. generalist capability models,
industry consolidation vs. entrepreneur-
ial and niche marketplaces), but other
types of change are more significant and
long-lasting.
The focus of this paper is on the latter
type. The reality is we have never seen
anything like the forces facing society
today. New technology in the form of social
media, tablets and other portable devices,
new digital capabilities, and Big Data
applications, coupled with the shrinking
scope of the world thanks to globalization,
and the subsequent shifts in how and what
types of work employees desire are result-
ing in a sea-change. It is hard to believe
these trends will not result in profound
shifts in the way companies organize them-
selves and run their businesses.
Thus, based on the academic and
practitioner literatures and our collective
experience in consulting and in large cor-
porate settings, we thought we would take
a shot at describing where we are headed.
Overall, and in the context of the Burke-
Litwin model (1992) of organization perfor-
mance and change we see three major
drivers present in the external environment
that are shaping the future of organizations
and OD along with them. These drivers
are resulting in four major trends that we
see already occurring today in the business
world. Our primary concern here are the
implications of these four trends for both
organizations, the role we as OD practitio-
ners need to play in helping organizations
manage through them, and the capabilities
we need to do so going forward.
The Three Drivers of Change
Although topics such as employee engage-
ment, organizational design, mission and
strategy, human capital management,
total rewards, diversity and inclusion,
and workforce planning are all critically
important for organizations today and will
continue to be going forward depending
on the strategy of the firm, we see three key
universal drivers of change that generally
sit above these. These drivers are shaping
how organizations are organized and the
skills required for success in the future.
These should be familiar to most readers
so we will not belabor them here but they
are worth mentioning:
1. The Changing Nature of Work—i.e.
the ways in which organizations are
literally organizing themselves (e.g.,
setting boundaries around companies,
functions, teams, and jobs), and defin-
ing how people do their day-to-day
activities and connect in various social
systems (Allen & Eby, 2016; Boudreau,
Jesuthasan, & Creelman, 2015; Gulati,
2009; Worley, Zardet, Bonnet, &
Savall, 2015).
2. The Changing Nature of Data—i.e. the
velocity, variety, veracity, and volume
(Big Data) of information both pub-
lic and private coming in and out of
processes, tools and systems including
“the internet of things” (Bersin, 2012:
Church & Dutta, 2013; Guzzo, Fink,
King, Tonidanel, & Landis, 2015).
3. The Changing Dynamics of the Work-
force Itself—i.e. the shifting ethnic
and generational demographics, values
structures, expectations, and social
responsibility requirements of the new
workforce (Deal & Levinson, 2016;
Ferdman, 1999; Meister & Willyerd,
2010; Twenge, 2010; Zemke, Raines, &
Filipczak, 2000; 2013).
While these drivers are significant, and we
have been talking about them for many
years in some cases (e.g., generational
differences), by themselves they are not
Figure
1
. Global Monthly Visitors to Popular Social Media Websites (Billions)
Source: https://www.dreamgrow.com/top-15-most-popular-social-networking-sites/
and authors’ research.
15Four Trends Shaping the Future of Organizations and Organization Development
actionable. Rather, these drivers have
produced four trends that do have conse-
quences on the way organizations function
and the requirements of doing OD work
within them.
Four Trends for the Future
Trend #
1
:
A Shift to Platforms over Products
The first major shift we see that has hap-
pened already in certain sectors is one
of structure—i.e., the move to platforms
over products in form. New types of
organizational designs have emerged in
the last 5-10 years, many as a result of the
e-commerce boom, to looser, virtual, fluid,
and dynamic structures (e.g., platforms)
where the boundaries of what is and is not
part of the “firm” are less clear (Boudreau,
et al., 2015). This enables them to be more
flexible and resilient in business environ-
ments. Existing brick and mortar firms
are attempting to evolve as well, but some
are having more difficulty doing so than
others given the nature of their business
models, the sophistication of their technol-
ogy, and certain elements of their cultures
rooted in the need for old school face-time
relationships.
Those companies that are moving
to platform models, however, are becom-
ing less and less focused on a total qual-
ity management (TQM) style production
mindset and directing energies instead
toward an adaptive service approach. Gulati
(2009) talks about this shift in terms of the
need for “customer centricity” while oth-
ers have focused on the concept of design
thinking (Brown, 2008). Whatever the
term, it represents a fundamental shift in
how people conceptualize work, how they
operate and involve the customer (or con-
sumer), and the face they present externally
to the marketplace (remember the EVP and
employer brand ideas mentioned earlier).
However, one of the cornerstones of design
thinking and creating resilient organiza-
tions is embracing a systems point of
view—something with which OD practitio-
ners should be quite familiar.
Our thinking here regarding the
shift to platforms over products emerged
from a recent analysis of the application
of traditional OD applications to other
types of organizations (i.e., those in the
government sector). In a special issue of
the OD Practitioner, Burke (2017) wrote
about “those other organizations.” The
question he explored was whether OD,
having emerged in the 1950s and 1960s
largely from business-industrial organiza-
tions such as the Harwood Manufacturing
Corporation, General Mills, and Humble
Oil, and therefore had (and still does) a
social technology based on tightly coupled
systems with top-down management, was
applicable to federal and state government
organizations and healthcare organiza-
tions. After a review of the relevant change
literature he concluded that the process
of OD, e.g., involving people in decision
making that directly affects their work and
degree of commitment, worked effectively
regardless of organizational type. The
difference was in the content. For business-
industry, the content primarily for OD work
is strategy—figuring out customer needs,
how to beat the competitor, and supplying
those needs. In government organizations,
the primary content concerns time, that is,
long-term vs short-term. In healthcare, the
primary issue is the conflict for a physician
in charge of a clinic; hospital department,
etc., that is, following the professional code,
e.g., Hippocratic Oath, vs. following the
needs of the organization itself—achieving
financial goals and matters of budget.
These organizations-business- indus-
trial, government, and healthcare—with
their variations of hierarchy and inter-
dependence, primary characteristics of
a tightly coupled system (Burke, 2014),
have been around for a long time and are
familiar to us. But what about the newer
organizations of today, especially those in
the “platform” category? Is “normal” OD
appropriate for change efforts in these
organizations? Let us briefly explore this
question. The Internet has changed our
work significantly, destroying things, e.g.,
the telegram, and creating others—the so-
called platform organization we mentioned
earlier. Even though in cyberspace, certain
organizations today provide a platform,
a place on the internet for transactions
to occur. Of this ilk, perhaps the easiest
to understand is eBay. This organization
provides a site (platform) on the internet
for people, i.e. eBay customers who want to
sell something they no longer need or want
anymore, say, a baby crib, to anyone who
needs a crib (think garage sale) and will
not have to pay a fortune for it. The price is
Figure
2
. Four Trends for the Future
OD PRACTITIONER Vol. 49 No. 3 201716
agreed to by the two parties and the seller
ships the crib to the buyer. eBay makes its
money from a percentage of the deal. Other
platform organizations include Facebook,
LinkedIn, Twitter, and Uber.
What makes these organizations
unique and reflective of the future is the
combination of the central headquarters,
if you will, and a huge network composed
of transactions on the platform provided
by the company. But these transactions are
independent of the company. Headquarters
does not control them. A platform organi-
zation is therefore at least two organiza-
tions—a central command that attempts to
operate like most any other business, that
is, having a CEO at the top of a hierarchy
and having interdependent functions such
as finance, marketing, operations, human
resources, etc., and a network of dispersed
customers and constituents that has no
hierarchy nor little or no interdependence.
In other words, these two organizations
are somewhat antithetical, one, headquar-
ters, being a tightly coupled system, and
the other, a network of customers, being a
loosely coupled system. From an OD stand-
point one works with these two systems
very differently (see Burke, 2014).
At some level, the CEO of Uber,
Travis Kalanick understands that drivers
are independent. He and his colleagues
at headquarters have hired hundreds of
social and data scientists (see Trend #4)
to entice drivers to work longer hours and
have monetary targets for their work day.
These enticements are, of course, based
on corporate goals not those of the driv-
ers, thus, commitment is problematical.
The extensive article in the New York Times
demonstrated quite dramatically this two-
system conflict (Scheiber, 2017). Uber driv-
ers, after all, are contractors not employees.
However, they are not selected to join as
contractors in any systematic way either,
which has resulted in all sorts of problems
(Church & Silzer, 2016). Instead, they are
bound by stipulations within a contract,
but otherwise they are independent, free
to decide their own working hours and to
some extent their geographical domain.
They pay a price, literally, for this freedom,
e.g., paying for their vehicle, maintenance
and insurance costs, and the cost of fuel.
And the long-range future is not rosy.
Kalanick and his executive colleagues are
moving slowly but ever so deliberately
toward driverless vehicles. In the mean-
time, intergroup conflict will remain for
the two systems.
The practice of OD for these platform
organizations will need to be done with
a true systems mindset. It will need to
be accommodative in approach with an
emphasis on common goals across the two
systems. It will also need to adapt as well
to different types of work contexts and con-
structs. For example, imagine conducting
a cultural or engagement audit of such a
firm. Would you include the drivers as part
of the survey effort? And if so, would you
expect them to be able to answer the same
types of questions as the primary organi-
zation? Should they consider themselves
as part of the organization or not? What
if their engagement levels are lower—is
that expected, is that acceptable? Similarly,
how would performance management play
out there? If you were focused on apply-
ing a dialogic model of OD (e.g., Bushe &
Marshak, 2009) how would you account
for the lack of interaction between drivers
in 1000s of disparate locations and the
formal organization? Communications are
executed in short bursts through hand-
held devices. Clearly, for OD practitioners
we must be more agile in our approach to
working with organizations and change
than ever before.
Trend #
2
:
A Shift to Digital Over Mechanical
The second major shift occurring in orga-
nizations today is a focus on the digital
over the mechanical (or the mechanistic)
ways of doing business. As technology
becomes increasingly integrated into our
lives, the need for agility and speed in the
way businesses respond to information
demands that they adopt a digital mindset
and set of processes. While the first step in
this direction is often to create formal dedi-
cated roles (e.g., a chief digital officer, an
eCommerce group, a digital marketeering
function, etc.), the bigger challenges lie in
the need to transform the entire business
end-to-end to reflect a truly digital focus.
This means everything from integrating
digital technology across all of one’s exist-
ing processes (e.g., people, culture, and
structure) as well as building new capabili-
ties and infrastructure which have never
existed before in their business models.
Unfortunately, this is far from easy and
many traditional organizations are simply
not ready to make the transition. Research
conducted by MIT Sloan Management
Review and Deloitte (Kane, et. al., 2016),
for example, has indicated that while 90%
of executives anticipate their industries will
be disrupted by digital trends to a great or
moderate extent, only 44% say their organi-
zations are appropriately prepared for these
challenges today.
One of the most intriguing aspects for
us in watching this digital transformation
occur (beyond the need for greater clarity
in the construct definition itself) is that
it is again forcing organizations to think
and operate at the systems level. While
most of the authors currently writing
about the challenges of going digital are
not grounded in the OD space, they are
in fact promoting the concept of systems
thinking whether intentionally or not. In
its most basic form we are simply talking
about inputs, throughputs, and outputs as
described in classic social psychological
theory (Katz & Kahn, 1978). This is encour-
aging to say the least. The biggest differ-
ences that we see with the current focus,
however, is in (1) the nature of those inputs
(i.e. data of a completely different nature
along with products and/or services), and
(2) the speed and direction of that flow
throughout the system.
In traditional mechanistic models of
organizations, the process flow follows a
more simplistic supply chain model. Raw
materials enter the system, are transformed
along the way into goods or services, and a
product (material or knowledge) is deliv-
ered. In the digital world data is generated
about the data collected along with the
process itself, and the feedback loops that
occur at every stage along the way are at
least as important if not more so than the
output itself. They represent end-to-end
systems and at higher velocities, depth,
and reciprocity between organizational
sub-systems than ever before. In other
words, fully digital organizations are in the
17Four Trends Shaping the Future of Organizations and Organization Development
unique position of being able to generate,
collect, synthesize, and process informa-
tion real time that allows them to pivot and
adjust their delivery models. This results
in ultimate flexibility (or at least that is the
goal most hope to achieve with a digital
transformation). While feedback loops have
always been a key component of process
systems and double-loop learning has its
roots in OD (Argyris, 1977), the digital
focus has taken this thinking to the next
level in organizations.
While the implications for organi-
zations with more traditional business
process models might be clear (e.g., they
are facing an uphill battle and will need
to retrofit their approaches and/or fun-
damentally rethink their designs), what
are the parallel implications for our OD
efforts? First, we need to help leaders better
understand the transition to the digital
environment in the first place, and what
that means for their organizations. In some
cases this may simply be a process of edu-
cation and training. In others, we may need
to find ways to help our clients learn new
knowledge, skills, and behaviors (e.g., how
to accelerate the speed of decision mak-
ing, how to capitalize on information –see
Trend #3). Still in others it might require
assessing for fit and changing out the
leaders themselves to make way for more
enlightened talent (see Trend #4).
Second, it is critical that the different
components of the organization are aligned
to support the digital transformation. As
with any large-scale OD intervention (and
the shift from traditional/mechanistic
to digital is arguably just another type of
cultural change), the degree of alignment
and congruence between the different
elements of the organizational system
need to be managed. The mission-vision,
structure, systems and process, leadership
and managerial behaviors, cultural messag-
ing, climate, and employee value proposi-
tions must all appropriately align (Burke &
Litwin, 1992). If an organization is moving
toward a digital mindset and yet the lead-
ers do not embrace technology or the use
of data for decision-making, for example,
there will be little belief on the part of
employees that the transformation is real
or supported. This is simply OD 101.
Third, we believe that OD practitio-
ners must understand and embrace the
concept of “mass customization” (Golay &
Church, 2013) as it relates to our interven-
tion sets. Mass customization in OD is all
about giving employees choices within a
given set of boundaries. Given the fluid-
ity of the processes needed to support and
sustain a digital organization, the OD tools
and offerings that are put in place must be
able to flex to the needs of individuals and
their contexts. For example, and build-
ing on earlier implications from Trend
#1, employees are expecting there to be
choices in how their performance is man-
aged, the ways in which they can receive
developmental feedback and learning,
where and how they work with others, the
mechanisms for giving feedback to their
managers or offering their opinions and
suggestions regarding the organization as a
whole, how jobs are defined, identified, and
filled, etc. We as OD practitioners need to
move away from being too systematic and
standardized in our approach to some of
these elements of organizational function-
ing. In information systems terms, we
need to understand the difference between
customization and configuration. Not every
OD intervention or process needs to follow
its own unique path, nor do we want all of
them to follow the same exact path. The
answer is somewhere in-between but we
need to determine where that is. In small
companies this has never been an issue,
but in larger ones we have our work cut out
for us as organizations constantly seek to
standardize in the spirit of efficiency and
effectiveness.
Finally, as with the first trend noted
above, we as OD practitioners need to
continue to embrace systems thinking.
We also need to embrace technology. This
means building new capabilities and skills
in the digital marketplace by translating
our traditional interventions where pos-
sible into this new medium. While neither
of these should be hard, our most recent
survey of OD practitioners (Shull, Church
& Burke, 2014) suggests just the opposite.
That is, survey responses from 388 active
practitioners indicated that the value of
systems thinking was ranked 13th overall
(out of a possible list of 36) which was
much lower than we would have expected.
Clearly there has been a shift in OD away
from having a systems perspective, which
is concerning. More troubling, however, are
the findings around our ability to embrace
technology. Specifically, the item “helping
organizations integrate technology into
the workplace” was ranked 40th and “the
development of socio-technical systems”
was ranked almost at the bottom of the
list at 56 out of 63 possible interventions
in use today. It would seem that OD is not
particularly progressive in this area.
Some might review these data and
argue this is not an issue, suggesting
instead that OD is all about human process
and social interaction. And they would be
right. However, we would contend that OD
is in some ways old school and living in the
past from a “technology” and data point
of view. As a field we need to think bigger.
We need to build our skills and develop
more agile processes and interventions
that can influence a new generation of data
and systems like never before. That is not
to say we should lose sight of the human
element. If anything, we may be the last
bastion of people focused on it! Imagine
the day when the digital transformation
reaches the next stage of its evolution and
robotics become the norm even in the
professional workforce. OD needs to stand
at the ready to support organizations, their
leaders, and their people in this trans-
formation. Yet, if we are not part of the
solution we are part of the problem. It is
on us to define and embrace “doing digital
OD”—whatever that might mean.
Trend #
3
:
A Shift to Insights over Data
The third major shift concerns the use of
data. As might be expected from the dis-
cussion above these new types of organi-
zational forms (e.g., digital platforms) are
producing volumes of data. While the use
of data is nothing new in organizations,
the expectations for how data is harnessed
and used is changing dramatically. More
specifically, and as alluded to earlier, the
collection and processing of this informa-
tion alone is not enough. In today’s busi-
ness landscape organizations are focusing
increasingly on generating insights from
OD PRACTITIONER Vol. 49 No. 3 201718
that data. Insights that will inform business
decisions, drive specific actions, and help
set future business directions. In fact, the
combination of the digital transformation
and the need to generate insights from the
massive amounts of data being generated
comes together in the Big Data phenomena
(Church & Dutta, 2013; Guzzo, et al., 2015).
This is where the science of analytics meets
business strategy, statistical modeling, and
workforce planning. It is no wonder then
that organizations are also hiring chief data
scientists (along with chief digital officers).
The reasons for why businesses might
want to link various sources of informa-
tion and identify potential relationships
is clear (and again is not entirely new).
What is new is the sheer volume, variety,
veracity, and velocity of the data available
to mine, and the resulting technology
infrastructure and capabilities required to
appropriately model and leverage it into
meaningful insights.
As for OD practitioners and their data
analytic capabilities, we have raised the red
flag on this gap in skills before (Church
& Dutta, 2013; Church, Shull, & Burke,
2016). There is a critical need on the part
of current practitioners to be able to ana-
lyze large sets of data, find the relevant and
actionable insights, and weave them into
a compelling story for the organization.
Today this is simply not likely to be the case
with your average ODer. While OD has his-
torically been grounded in action-research
and data-driven methods (e.g., Burke,
1994; Nadler, 1977; Waclawski & Church,
2002), and one could argue that qualitative
or quantitative data is at the core of 50% or
more of the classic OD consulting model
(Church, 2017), the fundamental signifi-
cance of the role of data has changed.
There is pressure from clients not only
on demonstrating the ROI of our existing
efforts in OD, but also to integrate and
synthesize disparate data sources to find
new solutions based on connections we
never even thought would exist. Is much
of the “values-free analytics” work done
a-theoretically? The answer is yes. Just
because a relationship is identified statisti-
cally does not always mean it makes sense
or is the right thing to do philosophically
for an organization’s culture or its employ-
ees (Church, 2017). Is the lack of attention
to theoretical models, frameworks, and cul-
tural contexts stopping organizations from
turning to people with deep analytical skills
to determine the solutions to their prob-
lems vs. relying on others (e.g., OD) who
might have a more informed point of view?
The answer is no, it is not stopping them
one bit. After all they are data scientists and
we are OD people. We have got to fix this.
If you have not already experienced
this issue, you probably soon will. We are
hearing about OD (and other) profession-
als finding themselves competing with
practitioners from other disciplines such as
economics, finance, information technol-
ogy, and statistics where their skills at deep
analytics and modeling are significantly
better. Even Industrial-Organizational
psychologists, who generally have a more
reliably consistent level of analytic capabil-
ity are having their qualifications come
under-fire when it comes to Big Data appli-
cations (Church & Rotolo, 2015; Guzzo, et
al., 2015).
We believe many practitioners today
are woefully ill-equipped to remain cur-
rent in the Big Data digital world. This
is an area we believe OD professionals
need to step-up their game now, as well as
ensure professional doctoral and masters
programs in the field lay the appropriate
groundwork for future entrants before
it is too late. If we do not act soon, other
professional groups will soon eclipse us
as the key providers of insights regarding
how organizations operate and what levers
to pull to drive change. We are losing our
seat at the table in this regard when in fact
we have more context and knowledge about
what should make organizations work than
most others. Remember, in our study of
current OD practitioners only 29% cited
using statistics and research methods in
their toolkits. As we have stated elsewhere,
while this can still be done in the context
of new OD philosophical approaches to
collaborative and adaptive consulting
efforts (e.g., Bushe & Marshak, 2009),
the analysis and insights skills them-
selves today are lacking.
Trend #
4
:
A Shift to Talent over Employees
The fourth and final shift we see in orga-
nizations today is one that is perhaps even
more controversial than the last, i.e. the
emphasis on talent over employees. This
trend sits front and center of the HR and
OD agenda so the implications for organi-
zations and the practice of OD are imme-
diately relevant. Here we are talking about
the philosophical distinction first made by
Church (2013; 2014) between the area of
talent management (i.e. a disproportion-
ate focus on the few) and OD (a concerted
focus on the many). We all would agree
that OD has deep roots in the develop-
ment and growth of individuals, groups,
and organizations. Following the “original”
war for talent (Michaels, et al., 2001) pre-
cipitated by the dot.com boom, and more
recently the emphasis placed on changing
demographic trends in the workforce as
well as multi-generational workplaces and
how to navigate those, (e.g., Deal & Levin-
son, 2016; Zemke, et al., 2000; 2013) we
are now firmly in what we might whimsi-
cally call a “war for talent management.”
The emphasis has indeed shifted in
many companies (and particularly those
with large established TM functions—see
Church, Rotolo, Ginther & Levine, 2015)
from creating a development culture in
general to focusing on methods for facili-
tating talent differentiation and segmenta-
tion. In short, this means directing funds
and resources to the identification and
We believe many practitioners today are woefully ill-equipped
to remain current in the Big Data digital world. This is an area
we believe OD professionals need to step-up their game now,
as well as ensure professional doctoral and masters programs
in the field lay the appropriate groundwork for future entrants
before it is too late.
19Four Trends Shaping the Future of Organizations and Organization Development
classification of people into high-potential
and non-high-potential categories for deci-
sion-making. This is done to ensure that
limited resources are applied to the right
groups in the leadership pipeline (Silzer &
Church, 2010). As a result, the data-driven
OD interventions and processes we used
to use for developmental interventions
(e.g., 360 feedback, surveys, interviews,
personality measures—Waclawski &
Church, 2002) are now being deployed
more consistently for assessment and
decision-making.
Not only does this emphasis put more
pressure on OD people to be technically
adept at using these types of tools given
there is now more weight associated with
their application, but it also challenges
the core assumptions of many practitio-
ners. Some may simply refuse to engage
in efforts of any nature that will result in
the segmenting of talent into the haves
and the have nots. On top of this many
organizations are shifting away from OD
altogether. Recent survey data (Church &
Levine, 2017) from 71 large well-known
companies on their functional reporting
structures noted that 71% of their formal
OD groups, and 68% of their culture and
engagement survey teams now officially
report into the Talent Management
function. By comparison only 49% of
the diversity teams and 12% of the total
rewards (compensation and benefits)
report into TM. This suggests a poten-
tial challenge when it comes to aligning
resources over time and where tradeoffs
need to be made. From our perspective,
OD practitioners need to fully understand
the ways in which our core tools can and
cannot be used and what conditions are
needed to build effective legally defensible
decision-making (TM) vs development only
(OD) processes.
Sure, OD people can choose not to
work in such environments. They can
boycott organizations that are emphasizing
TM. But that seems like throwing out the
baby with the bathwater to us. If not us,
the work will get done by someone in HR,
and by engaging in the efforts we remain
key players in ensuring it is done well and
people are treated with dignity. It is up to
OD professionals to ensure that our values
are manifested in how data-driven tools
and processes are used for development or
decision-making outcomes. That means
that we are on point to ensure people are
treated fairly, the process is clearly com-
municated, and when differentiation does
occur there is transparency and account-
ability for the how and the why. And we can
ensure that leaders are held accountable for
their actions as well.
Back in the 1990s, had we been asked
to design a 360-feedback system to be
used to segment talent and make decisions
about who would and who would not be
promoted we might have said no. In fact,
we did say no at least once to something
quite similar. Today, however, times have
changed. The process of 360 is no lon-
ger a fad but has proven to be stable as a
measurement tool when done well and
quite ubiquitous. Organizations are using
360 now for decision-making in a variety
of ways whether that is for performance
management (Bracken & Church, 2013) or
talent management and the identification
of high-potentials (Church & Rotolo, 2013).
If the right procedures are followed in the
design and execution of the process it can
be done well for the benefit of the organiza-
tion and the employees. After all, millenni-
als love feedback and want to know if they
are likely to have a successful career or not
in their current company—transparency
works for them (Church & Rotolo, 2016).
From our vantage point, the keys to ensur-
ing this type of work always aligns with OD
principles are making sure: (a) feedback
is always delivered to participants in some
meaningful and supportive form, (b) what
is measured is psychometrically valid and
appropriate if used for decision-making,
(c) people use the data in the right ways
and at the right times, and (d) the process
is clearly communicated and transparent to
those involved.
Conclusion
In summary, when we look to the future
of organizations and the role that OD
practitioners can and should play in them
we see the potential for real progress. As
organizational forms continue to morph
into platforms and other virtual structures,
and the business processes themselves
become entirely digital in their end-to-
end designs, the opportunity for OD to
make an impact is very tangible. Given
our grounding in the social sciences and
systems thinking we should be one of the
best groups of professionals to help lead-
ers think through the implications of these
changes on the culture, people, processes,
structure, behaviors required and other ele-
ments of the entire organizational system.
While there is room to grow when it comes
to OD professionals embracing technology
in the digital age, as long as we do not lose
sight of our higher-level systems thinking
skills, there is real value to be offered from
the OD perspective. This discussion does
make us wonder though if it is time for a
return to the socio-technical model.
Our concerns for the future of OD,
and perhaps organizations as well by impli-
cation, is what happens when the data anal-
ysis and insights requirements outstrip our
ability to even be part of the discussion. As
leaders look to data-scientists for insights,
actions, and interventions we need to be at
the table and questioning the way the sta-
tistics were run, whether certain contextual
variables were considered, what research
methods and controls were examined, etc.
Our backgrounds as social scientists puts
us at an advantage for understanding the
true dynamics of social systems yet our
potential impact on the actions taken is
diminishing. It is time to enhance our skill
set in these areas and direct our academic
and professional programs to focus on this
as well. If we do not ensure our students
have these capabilities they will be rel-
egated to focusing only on the areas where
data does not have an impact. If we follow
the breadcrumbs above between platform
organizations where people are loosely con-
nected and digital networks and robotics
become the norm, these changes will mean
our opportunities to influence will only
continue to decrease.
Finally, although the core of OD is
all about development, the field is being
subsumed under the TM function in many
big organizations, and our processes and
tools are being used in other ways. Rather
than look the other way or run from these
issues we should learn the skills needed
OD PRACTITIONER Vol. 49 No. 3 201720
to embrace them. Specifically, who better
to design a new leadership competency
assessment and help the organization
identify and select the best future leader to
develop than an OD person? Who better to
coach other talented leaders that were not
selected for a given role because of their
strengths, opportunities, and skill gaps, if
not an OD professional? We should be the
people managing both sides of the TM and
OD equation. That way we know for sure
it is being done with the right perspective
in mind.
References
Allen, T. D., & Eby, L. T. (Eds.) (2016). The
Oxford handbook of work and family
(pp. 455–464). New York, NY: Oxford
University Press.
Argyris, C. (1977). Double loop learning in
organizations. Harvard Business Review,
55(5), 115–125.
Beasley, K. (2013). Should employees
access social media at work?
Business2Community.com.
Retrieved from http://www.
business2community.com/social-media/
employees-access-social-media-work-
0639919#Egu8D1FjdUW2SEBf.97
Bersin, J. (2012). Big Data in HR: Building
a competitive talent analytics function—
The four stages of maturity. Bersin &
Associates Research Report.
Boudreau, J. W., Jesuthasan, R., &
Creelman, D. (2015). Lead the work:
Navigating a world beyond employment.
Hoboken, NJ: John Wiley & Sons.
Bracken, D. W., & Church, A. H. (2013).
The “New” performance management
paradigm: Capitalizing on the unreal-
ized potential of 360-degree feedback.
People & Strategy Journal, 36, 34–40
Bradford, D. L., & Burke, W. W. (2004).
Introduction: Is OD in crisis? Journal
of Applied Behavioral Science, 40(4),
369–373.
Brown, T. (2008). Design thinking. Har-
vard Business Review, 86(6), 84–92.
Burke, W. W. (1976). Organization develop-
ment in transition. Journal of Applied
Behavior Science, 12(1), 22–43.
Burke, W. W. (1982). Organization develop-
ment: Principles and practices. Boston,
MA: Little Brown.
Burke W. W. (1997). The new agenda for
organization development. Organiza-
tional Dynamics, 26(1), 6–20.
Burke, W. W. (2011a). Organization change:
Theory and practice (3rd Ed.). Thousand
Oaks, CA: Sage.
Burke, W. W. (2011b). A perspective on
the field of organization development:
The Zeigarnik effect. Journal of Applied
Behavioral Science, 47(2), 143–167.
Burke, W.W. (2014a). Changing loosely
coupled systems. Journal of Applied
Behavioral Science, 50(4), 423–444.
Burke, W. W. (2014b). On the state of the
field: OD in 2014. OD Practitioner,
46(4), 8–11.
Burke, W. W. (2017). Those other organiza-
tions. OD Practitioner, 49(2), 10–16.
Burke, W. W., & Church, A. H. (1992).
Managing change, leadership style, and
intolerance to ambiguity: A survey of
organization development practitioners.
Human Resource Management, 31(4),
301–318.
Burke, W. W., Church, A. H., & Waclawski,
J. (1993). What do OD practitioners
know about managing change? Leader-
ship and Organization Development
Journal, 14(6), 3–11.
Burke, W. W., & Goodstein, L. D. (1980).
Organization development today: A
retrospective applied to the present
and the future. In W. W. Burke & L. D.
Goodstein (Eds.), Trends and issues in
Organization Development (pp. 3–15).
San Diego: University Associates.
Burke, W. W., & Noumair, D. A. (2002),
The role of personality assessment
in organization development. In J.
Waclawski & A.H. Church (Eds.),
Organization development: A data-driven
approach to organizational change (pp.
55–77). San Francisco, CA: Jossey-Bass
Burnes, B., & Cooke, B. (2012). The past,
present and future of organization
development: Taking the long view.
Human Relations, 65(11), 1–35.
Burke, W. W., & Litwin, G. H. (1992), A
causal model of organizational perfor-
mance and change. Journal of Manage-
ment, 18(3), 523–545.
Bushe, G. R., & Marshak, R. J. (2009).
Revisioning organization development:
Diagnostic and dialogic premises and
patterns of practice. Journal of Applied
Behavioral Science, 45(3), 348–368.
Church, A. H. (2001). The professionaliza-
tion of organization development: The
next step in an evolving field. In R. W.
Woodman & W. A. Pasmore (Eds.),
Research in organizational change and
development (V. 13, pp. 1–42). Green-
wich, CT: JAI Press.
Church A. H. (2013). Engagement is in the
eye of the beholder: Understanding dif-
ferences in the OD vs. Talent Manage-
ment mindset. OD Practitioner, 45(2),
42–48.
Church, A. H., (2014). What do we know
about developing leadership potential?
The role of OD in strategic talent man-
agement. OD Practitioner, 46(3), 52–61
Church, A. H., & Burke, W. W. (1993).
Exploring practitioner differences in
consulting style and knowledge of
change management by professional
association membership. Consult-
ing Psychology Journal: Practice and
Research, 45(3), 7–24.
Church, A. H., & Dutta, S. (2013). The
promise of big data for OD: Old wine
in new bottles or the next generation of
data-driven methods for change? OD
Practitioner, 45(4), 23–31.
Church, A. H., & Rotolo, C. T. (2013). How
are top companies assessing their high-
potentials and senior executives? A
talent management benchmark study.
Consulting Psychology Journal: Practice &
Research, 65(3), 199–223.
Church, A. H., & Rotolo, C. T. (2016). Lift-
ing the veil: What happens when you
are transparent with people about their
future potential? People & Strategy, 39(4),
36–40.
Church, A. H., Shull, A. C., & Burke, W.
W. (2016). The future of organiza-
tion development, transformation,
and change. In W. J. Rothwell, J. M.
Stavros, R. L. Sullivan, & A. Sullivan
(Eds.), Practicing organization develop-
ment: A guide for leading change (4th ed.,
pp. 419–428). Hoboken, New Jersey:
Wiley & Sons, Inc.
21Four Trends Shaping the Future of Organizations and Organization Development
Church, A. H., & Silzer, R. (2016). Are
we on the same wavelength? Four
steps for moving from talent signals to
valid talent management applications.
Industrial and Organizational Psychology:
Perspectives on Science and Practice, 9(3),
645–654.
Deal, J. J., & Levenson, A. (2016). What
millennials want from work. New York,
NY: McGraw Hill.
Dragojlovic, K. (2016). Moore’s law and
digital marketing. Retrieved from https://
www.linkedin.com/pulse/moores-law-
digital-marketing-katja-dragojlovic
Ferdman, B. M. (1999). The color and
culture of gender in organizations:
Attending to race and ethnicity. In G.
N. Powell (Ed.), Handbook of gender and
work (pp. 17–34). Thousand Oaks, CA:
Sage.
Golay, L. M., & Church, A. H. (2013). Mass
customization: The bane of OD or the
cure to what ails it? Leadership and
Organization Development Journal, 34(7),
661–679.
Gulati, R. (2009). Re-organize for resilience:
Putting customers at the center of your
business. Boston, MA: Harvard.
Guzzo, R. A., Fink, A. A., King, E., Toni-
dandel, S., & Landis, R. S. (2015). Big
data recommendations for industrial–
organizational psychology. Industrial
and Organizational Psychology: Per-
spectives on Science and Practice, 8(4),
491–508.
Kallas, P. (2017), Top 15 most popular
social networking sites (and 10 Apps!).
May 8, Retrieved from https://www.
dreamgrow.com/top-15-most-popular-
social-networking-sites/
Kane, G. C., Palmer, D., Phillips, A.
N., Kiron, D., & Buckley, N. (2016).
Digitally savvy executives are already
aligning their people, processes, and
culture to achieve their organizations’
long-term digital success. Retrieved
from http://sloanreview.mit.edu/projects/
aligning-for-digital-future/
Katz, D., & Kahn, R. L. (1978). The social
psychology of organizations (2nd ed.).
New York, NY: John Wiley.
Meister, J. C., & Willyerd, K. (2010).
The 2020 workplace: How innovative
companies attract, develop, and keep
tomorrow’s employees today. New York:
HarperCollins.
Michaels, E., Handfield-Jones, H., &
Axelrod, B. (2001). The war for talent.
Boston, MA: Harvard Business School,
McKinsey & Co
Porras, J. I., & Singh, J. (1983). Alpha, beta,
and gamma change in modelling-based
organization development. Journal of
Organizational Behavior, 7(1), 9–24.
Rawlings, C., & Bencini, R. (2014). What
Does Moore’s Law mean for the rest of
society? Futurist, 48(4), 40–42.
Scheiber, N. (2017) How Uber pushes driv-
ers’ buttons. New York Times, (April 3)
pp.1, 14–16.
Shull, A. C., Church, A. H., & Burke, W. W.
(2013). Attitudes about the field of Orga-
nization Development 20 years later:
The more things change, the more
they stay the same. In A. B. Shani, W.
A. Pasmore, R. W. Woodman, & D. A.
Noumair (Eds.), Research in Organiza-
tional Change and Development, (Vol. 21,
pp. 1–28). Bingley, UK: Emerald Group
Publishing Limited.
Shull, A. C., Church, A. H., & Burke, W. W.
(2014). Something old, something new:
Research findings on the practice and
values of OD. OD Practitioner, 46(4),
23–30.
Silzer, R., & Church, A. H. (2010). Identify-
ing and assessing high potential talent:
Current organizational practices. In R.
Silzer & B. E. Dowell (Eds.), Strategy-
Driven talent management: A leadership
imperative (pp. 213–279). San Francisco,
CA: Jossey-Bass.
Twenge, J.M. (2010), A review of the
empirical evidence on generational
differences in work attitudes. Journal of
Business and Psychology, 25(2), 201–10.
Waclawski, J., & Church, A. H. (2002).
(Eds.). Organization development: A
data-driven approach to organizational
change. San Francisco, CA: Jossey-Bass.
Worley, C. G., Zardet, V., Bonnet, M., &
Savall A., (2015). Becoming agile: How
the SEAM approach to management
builds adaptability. Hoboken, NJ: John
Wiley & Sons.
Zemke, R., Raines, C. , & Filipczak, B.
(2000). Generations at work: Managing
the clash of boomers, gen xers, and gen
yers in the workplace. New York, NY:
American Management Association.
Zemke, R., Raines, C., & Filipczak, B.
(2013). Generations at work: Managing
the clash of veterans, boomers, xers, and
nexters in your workplace. New York, NY:
American Management Association.
Allan H. Church, PhD, is Senior
Vice President of Global Talent
Assessment & Development at
PepsiCo. Over the past 17 years he
has held a variety of roles in orga-
nization development and talent
management in the company. Pre-
viously he was with Warner Burke
Associates for almost a decade,
and before that at IBM. He is cur-
rently on the Board of Directors
of HRPS, the Conference Board’s
Council of Talent Management,
an Adjunct Professor at Columbia
University, and Associate Editor of
JABS. He has been a former Chair
of the Mayflower Group. Church
received his PhD in Organizational
Psychology from Columbia Univer-
sity, and is a Fellow of SIOP, APA
and APS. He can be reached at
Allan.Church@pepsico.com.
W. Warner Burke, PhD, is the
Edward Lee Thorndike Professor
of Psychology and Education at
Teachers College, Columbia Uni-
versity where he has been since
1979. He has written or edited 20
books and authored well over 150
articles and book chapters. He has
received many awards includ-
ing the OD Network’s Lifetime
Achievement Award and NASA’s
Public Service Medal. He was the
administrator of the ODN from
1966–1967 and executive direc-
tor from 1968–1974. He helped to
launch the OD Practitioner in 1968.
He can be reached at wwb3@
columbia.edu.
OD PRACTITIONER Vol. 49 No. 3 201722
