Target in Transition: A Case for Organizational Agility

Network Analysis @ Target

Target 2006 – 2010 by classification (super-cluster view)

via “Network Explorer”

target 2006 - 2010 v2

(1)  “Target to cut Minnesota jobs while expanding in New York / California” (3/3/2015)

As Target sharply downsizes in Minnesota, it is expanding its corporate footprint in Silicon Valley and New York.

The restructuring will be concentrated at Target’s corporate locations and focus on driving leaner, more efficient capabilities — removing complexity and allowing the organization to move with greater speed and agility.

New Target CEO Brian Cornell has found the corporate culture in Minneapolis too plodding and cautious. Cutting complexity at the corporate level will make Target more competitive. Retail specialist Dave Brennan at the University of St. Thomas sees a real cultural change underway. Cornell’s background includes experience at Sam’s Club and he is operating with the same kind of dispatch as the Walmart organization.

(The Walmart culture is typically more action-oriented — they analyze opportunities comprehensively, but faster than Target.)

Target intends to make large investments in mobile and digital technologies. It has already made some large strides in those areas, but it needs to do more. Because omni-channel customers are so profitable, Target needs to be ready as U.S. consumers become more tech-savvy. Digitally-connected shoppers who interact on more than one channel generate three times the sales and two-and-a-half times the margin as customers who shop only in the store.

Target is one of many retailers and manufacturers, including Best Buy, that have recently opened innovation centers on the tech-heavy West Coast.

(2)  “Target starts tearing down corporate walls” (3/12/2015)

An organizational concept called “centers of excellence” will encourage cross-functional collaboration and decrease redundancy.

Target is one of few retailers that can combine data about what individual customers buy in stores with what they buy online to develop product recommendations for those customers.

(3)  “Target layoffs will hit 1,700” (3/12/2015)

Chief executive Brian Cornell said that the cuts were necessary to speed up decisions and projects at the nation’s fourth-largest retailer.

Though cutting staff will save money, Cornell and other Target executives focused more on speeding up an organization in which decision-making had become bogged down.

In order to compete today, speed and simplicity are critically important – they are looking at every opportunity to eliminate complexity.

(4)  “Firms reach out to ex-Target workers” (3/12/15)

(5)  “Highly skilled / highly paid target jobs probably gone forever” (3/11/2015)

Having smart young people come here — and stay — is how the Twin Cities became a metro area that’s among the leaders in median income, educational attainment, and other economic measures.

Target executives said last week that the company will continue to hire people with unique skills, such as data science.

Some will stay put and bring their skills to other top companies or kick-start their own businesses.

A layoff of this magnitude is something that our vibrant and diverse economy will mostly shrug off.

Cutting jobs at headquarters makes the work simpler; some tasks get done faster, some don’t get done at all.

(6)  “Hundreds of Target workers cut all at once” (3/11/2015)

Neuro-nomic Experience Design / “Open Space”

like “ergo-nomic”

– David Rock (author of “Your Brain at Work”) on neuroleadership / brain-friendly conference design — via Erika Garms (neuroscience colleague @ MNCMN):

“New business relationships are far more valuable than new ideas.”

– “open space” / Harrison Owen (think socratic method for groups)

Liberating Structures

The Surprising Power of Liberating Structures

via Keith McCandless

health care organizations –> organism / biological model

manufacturing, retail / distribution, financial services organizations –> machine / mechanical model

How could health care organizations further leverage the biological model as an agility template?

How could manufacturing, retail / distribution, financial services organizations adopt the biological model from health care organizations?

Theory U / Leading from the Emerging Future

a community conversation

via Otto Scharmer

The premise around “field structures of attention”: We can’t solve level 4 problems with level 1-3 mechanisms. Consistent with general theory of complex adaptive systems.

(Also consistent with Gödel’s incompleteness theorems of mathematical logic translated to complex systems / computer architecture: A computer of a given size can model only a smaller computer — it cannot model itself. If it modeled a computer of its own size and complexity, the model would fill it entirely and it wouldn’t have any resources available to exercise the model. A corollary — we may never fully understand the human brain by using the human brain to understand it.)

The Evolution of the 21st-Century Organization

via John Kotter

Concept of hybrid network / hierarchy in the intra-organizational context seems analogous to the concept of hybrid network / hierarchy for “innovation ecosystems” in the inter-organizational context.

We form machines in the image of our brain; we form organizations in the image of our brain.

hierarchy / linear / monolithic structure –> operational / repetitive functions –> primitive brain
network / nonlinear / granular structure –> creative / non-repetitive functions –> advanced brain

Optimizing for agility vs. efficiency… in the context of an “organizational operating system“.


Athletic Machines / Athletic Organizations

via aerial robotics / the “Internet of Things” / pervasive computing / “big data”…

If we can draw analogies between software engineering and organizational design (both of which are formed in the image of the human brain)…

Can we draw analogies between athletic machines and athletic organizations / agile organizations?

The Astounding Athletic Power of Quadcopters

Raffaello D’Andrea via “flying machine arena” / TED

What does it mean for a machine to be athletic?

Quadcopters are extremely agile, but such agility comes at a cost — they’re inherently unstable.

They need some form of automatic feedback control in order to fly.

Estimation and control algorithms are the magic that bring these machines to life.

How does one design the algorithms that create a machine athlete?

These scientists use model-based design.

They capture the physics with a mathematical model of machine behavior.

Using a branch of mathematics called control theory, they analyze the models and synthesize algorithms for controlling them.

They capture the dynamics with a set of differential equations — they manipulate the equations using control theory to create algorithms that produce the desired behavior.

Knowledge of the mathematical models enables the researchers to design novel machine architectures and clever algorithms that that gracefully support exotic configurations.

The researchers are using machine athleticism to develop new algorithms for machines that push them to their limits.

Free-Agent Nation / The Rise of the Network Organization

“Free Agent” is New Face of Workforce

– More than 40% of American workers classified themselves as a “free agent” in 2012

– The trend is driven by both necessity and possibility

– The shift is clear in industries like software development and construction

– The baseline level of skills required in traditional organizations is increasing — in some ways, those skills that are needed as an entrepreneur: Self-motivation, problem-solving, critical thinking, teamwork


Three stages of development / evolution:

1) Monolithic / traditional structure (largely historical)

2) The rise of a more granular (agile / flexible) structure as a significant component of economic activity (free-agent, contract / temporary work — the current trend — trending even further toward hyper-granularity)

3) Integration / optimization of the more granular component with the more monolithic component (the next generation of industrial organization)

From the perspective of neuroscience in the workplace (see “Your Brain at Work” by David Rock): The two components of industrial organization (monolithic / granular) map roughly to functional specialization (operational activities / creative activities); that functional specialization in industrial organization also maps roughly to brain function (pre-frontal cortex = non-repetitive, creative activities; basal ganglia = repetitive, operational activities). Interesting how we humans tend to create industrial organization in our image / the image of the human brain.

monolithic structure –> operational activities –> primitive brain                             – granular structure –> creative activities –> advanced brain

(For more background on organizations as brains / organizations as organisms, see the classic works “Images of Organization” by Gareth Morgan and “The Well-Being of Organizations” by West Churchman.)

Although granularity is on the rise, monolithic-type organizations will persist (largely for more operational / scale-based / repetitive activities). Insofar as monolithic-type organizations persist, they will nevertheless migrate toward internal structures that emulate granular-type organizations — by ‘decomposing’ their breadth of scope into smaller / more agile components and effectively integrating those components into larger super-structures (including super-structures that form beyond the organization’s natural boundaries).

While the network organization is only in its practical infancy, the discipline of software engineering has shown significant maturity in applying the principles of decomposition / integration. The immense demands on software systems that are vast in scope / complexity and robust in the face of incessant change has forced software engineering to produce radically new architectural and developmental paradigms — just as the emerging workplace realities will stimulate radically new organizational paradigms.

Although software systems are not human / organizational systems, the two contexts share some common characteristics, and advances in software engineering (object orientation, client-server architecture, agile development) can provide some symbols, models, and templates for the organizational challenges that lie ahead.