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Global Complexity Challenges Innovative Enterprises

By Navneet Bhushan

As globalization increases there is a corresponding explosion of global complexity. It is not about one location, one market, limited competition, specific life-long products – it is a dynamic world of collaboration. The dynamic world is increasing its value exponentially while at the same time complexity increases. Survival and success in today’s world depends solely on continuous learning and innovation. Some managers, leaders, employees and customers are losing confidence in their own abilities to make decisions in this atmosphere. How does an individual frame the right problem before solving the problem?

Complexity is reflected in the increasing numbers of alternatives that are available. The ones winning are more agile, faster and quicker. At each decision point, increasing time pressure to make decisions results in how fast one innovates; it sometimes is viewed as more important than how accurately one innovates.

This increase in decision-making time causes the need for more analysis. Networks of all types are increasing at an unprecedented rate. The connections among those networks – hidden as well as visible – are increasing as well. Yet individuals are constrained by the limits of their minds.1

Is there a blueprint for globally distributed enterprises in this seemingly chaotic world?

Empowering Group Ideas Together – The Mantra for Enterprises
Power can be seen as the ability to change. When a group’s ideas are empowered, organizations succeed and grow. This is the only blueprint for success in a future characterized by increasing globalization and complexity.

Modern businesses are not designed for continuous innovation. How does an individual influence continuous innovation in large organizations? By empowering ideas. There is a need to understand and leverage each and every human mind working for an organization (including employees, customers, suppliers, partners and competitors). Engage their minds to develop a thriving idea pipeline; ideas die first and then, the enterprise.

Future Proofing Globally Distributed Enterprises
Research and experiments indicate that globally distributed enterprises need to focus on four key areas:

  1. Customer value framework
  2. Knowledge / information worker productivity
  3. Decision engineering
  4. Innovation crafting framework

These four areas need to be explored with a focused approach in order to adapt, adopt and thrive in the globalizing world. The following includes in-depth information on these four areas.

Customer Value Framework – The Customer of Products / Services
Most individuals know the value they are delivering to customers. But what is customer value?

It is important to understand and empathize with the customer while evaluating value – this will add value for the customer. There will, however, always be a tradeoff between total benefit versus total cost that the customer will continue to evaluate during its relationship with any business.

For example, the smart salesman sells enough benefits at the highest cost and creates the impression that the benefits perceived by the customer are the best that the cost incurred can buy. The salesman may not keep the relationship going if the value remains at the perception level only. This calls for an end-to-end customer value model shown in Figure 1.


There are two key dimensions of any customer-supplier scenario:

  1. The first dimension shows how much the customer knows what they need.
  2. The second dimension shows how much the supplier knows and what the customer needs.

These two dimensions create four clear quadrants:

  1. Known-known (box 1): the deterministic world; the focus is on delivery and efficiency.
  2. Known-unknown (box 2): the supplier has to discover what clients need. It has to follow the path of customer intimacy.
  3. Unknown-known (box 3): the supplier has to let the customer learn through a process of orchestrated customer learning.
  4. Maximum synergy and value (box 4): where maximum synergy and value can be co-created. No player knows the needs in this scenario. The value-net deep dive is used as the model for creating value.2

Knowledge / Information Worker Productivity
Productivity as the ratio of output and input is the metric of efficiency that was inherited from the industrial age. This metric in the new world of knowledge / information work is failing miserably.

Consider, for example, software development activity. What is the output of software development activity? Is it the amount of software (i.e., size as reflected in lines of code) or the functionality delivered? Does this output need to be measured only in terms of size or should the quality of output be included? What about the input?

The software is developed through the intellectual effort of people (software developers) and also the time that they take to develop the software. Since studies have shown that the number of software developers and the amount of time are not replaceable with each other in a linear manner, it makes sense to incorporate both as the input. The established, standard metric that is used (a legacy of industrial era production based metrics) known as the kilo lines of code per person week (KLOC / PW) does not reflect the true nature of software productivity.

In the age of wikis, blogs, social networks, micro-blogging, un-conferences and open environments, how does an individual understand what is work and how is it measured? Is there a need to have a metric at all? Globally distributed enterprises understand the value of the knowledge work and they come up with assessments on how to value it.

Decision Engineering
Decision engineering is an emerging discipline for developing tools and techniques for informed operational and business decision making within the industry by collating and exploiting distributed organizational knowledge. In Figure 2 it indicates the stages in decision making and the key requirements in each stage. An enterprise-wide decision engineering framework should incorporate these tools and techniques during all stages.


The extent of the work involved in designing such a framework – for the number of techniques for forecasting alone include:

a. Systematic expert judgment
b. Decision matrix
c. Analytic hierarchy process
d. Bayesian inference
e. Cross-impact analysis
f. Early warning indicators
g. Extrapolation with moving averages
h. Trend analysis
i. Time series analysis
j. Spectral analysis
k. Combined trend
l. Trend impact analysis

It is important to be able to use different techniques in specific business scenarios so that decisions can be engineered at various levels including:

Strategic / Policy

  • Evaluating options / alternatives
  • Evaluating factors affecting a particular decision
  • Evaluating return on investment / cost benefit analysis
  • Evaluating uncertainty
  • Market analysis / technology forecasting


  • Process evaluation
  • Process optimization
  • Performance evaluation
  • Evaluation of quality attributes – reliability / availability / survivability

Project / Program Execution

  • Technology evaluation
  • Choosing a product
  • Benchmarking products
  • Evaluating architectures

No single approach, tool or technique will work in an enterprise. Frameworks need to be evolved to help globally distributed enterprises make robust decisions in constrained time lines.

Innovation Crafting Framework
Innovation cannot be left to happen on its own. Globally distributed enterprises need to make it happen. It is about shifting from what is currently working and looking at what is needed and what should be needed by customers.

This can be accomplished by experimenting with several techniques of idea generation.


The techniques help teams, groups and companies in new product development, process improvement, organizational change initiatives, the creation and alignment of vision, strategy deployment and a variety of scenarios that come up as situations to be explored for implementing change.

The framework for creating innovation defines specific phases of the innovation process and aids the process through established techniques and methods with robust results. Instead of using regular brainstorming methods, the Theory of Inventive Problem Solving (TRIZ), design structure matrix (DSM) and analytic hierarchy process (AHP) are three main techniques that are introduced in the framework.

In the increasing globalizing complexity world, continuous innovation is the only savior. The methods, metrics and structures of the past are failing in the open world of globalizing work. The new methods of models, metrics and structures and dynamic collaboration are needed to make the globally distributed enterprises successful. The four key frameworks proposed to help with the deployment of the globally distributed enterprises to ensure robustness included:

  1. Customer value framework
  2. Knowledge / information worker productivity
  3. Decision engineering
  4. Innovation crafting framework

The key is to future proof the enterprises by making them innovative. In a world of exploding global complexity, innovative enterprises are the only option.


  1. George A. Miller, Magical Number Seven, 1956.
  2. Navneet Bhushan, Define and Quantify Customer Value – Reveal the Needs, Real Innovation, 2008.

About the Author:
Navneet Bhushan is the founder / director of an innovation co-creating firm, Crafitti Consulting Pvt Ltd. He has worked close to two decades in managing and developing IT, innovation and productivity solutions and has worked in large commercial and government organizations. He is the principal author of Strategic Decision Making – Applying the Analytic Hierarchy Process published by Springer, UK, 2004. His current research interests include complexity, open innovation and globalization. He is a visiting faculty member at Welingkar School of Business Management. Contact Navneet Bhushan at navneet.bhushan (at) or visit