Business agility means how a company adapts to a changing competitive landscape. To be agile in 2016, it is not enough to clearly predict the future, move fast, and execute plans well. What will contribute to success is including the emotional elements.

How to be efficient in practice?

The post-millennial technology boom gave agility management a series of new spins and colors. When making a corporate change program more efficient, aligning all employees may not be necessary. Just winning the critical few opinion leaders could achieve the same communication impact. It could also speed up organizational response times. What about anticipating the emotional elements, the ones that business data analytics do not necessarily turn up? Could it be useful to keep an eye on the key opinion leaders, rather than sampling large populations per se.

Recent scientific concepts from neuroscience to biometrics and network research could teach personal and corporate agility: how to stay fit and adaptable with more speed, anticipation and efficient delivery.

This is how pioneers do it

Is this pure speculation? Certain pioneering organizations have implemented the above principles:

A leading energy group used network research-based methods to speed up decision making, but not by cutting consultative elements. In fact, more consultation with the right opinion leaders might decrease the time needed to reach a quality decision, factoring in most of the relevant views.

A pharmaceutical company used advanced diagnostics to simplify communications, killing up to 30% of the mail traffic and filtering out messages likely to cause more “noise” than progress.

A major telecommunication firm used networks mapping to enhance communication efficiency in a post-merger situation, driving down integration time and costs.

Speed as the factor for effective business agility

Agility has been on the agenda since Charles Darwin identified adaptability as a key to survival. Re-emerging in the corporate vocabulary after the notable failures of iconic firms such as PanAm and Kodak. When technology enabled disruptions dominate this landscape, adaptation speed first needs redefinition. It used to be fine to ”strategically adapt”, over two, three or even five years. Agenda 2012, 2016 and even 2020-type corporate visions were typical before the global shock of 2008-9. Nowadays, few firms dare to think or plan ahead more than one or two years – in the best case, three. Some industries define innovation cycles in weeks, rather than months. To be agile in 2016, adaptation is not enough: rapid adaptation is the starting point. One might argue this focus brings the short-termism as by-product for individuals, firms and possibly nations – see Brexit.

The limits of predictions in the case of Brexit and the US presidential election

The second wave of change addresses the target models. It used to be wise to wait and see if a new business model, approach or technology panned out; many large, risk-averse corporations avoided ”early follower” strategies. This belongs in the vintage bin today. Agile firms need to excel in anticipation, not necessarily predicting one future state, but distributing the best resources in a combination of alternatives, including the winner(s). Think of professional sports: in a world where all opponents are fit, anticipate better and faster - where the ball is going, what the next move might be. A pure mental game.  [The quotation from hockey great Wayne Gretzky, “Skate to where the puck is going, not to where it has been” is possible here, but also already a cliché.]

The current increase in sensors and data, adding advanced modeling algorithms, enhances this anticipative or predictive capability. But wait a second. Most data predictive algorithms build on the assumption that the past – with smart trending – will predict the future. Would it? Take Brexit or the election of Trump. Few of the advanced statistical, mathematical models are capable of modeling emotions, relations, and power of networks. So the second new element of agility is predictive capability, in a broad sense.

How efficient are the responses?

The third new feature is about response efficiency. Some call it “strategy execution capability”. Even with good predictions and speed, the force, focus or precision needed to make a sufficient impact may still be lacking. With an environment awash in data and initiative, the emergence of  “stop-lists” instead of old school to-do-lists underscores this assertion. Look at corporate simplification programs. Look at simple product designs.

Part of the success is to refine the focuses, key initiatives, and related messages. But it is equally important to de-clutter, and get rid of possibly useful, but resource-intensive activities. But where are these trade-offs, what are the insufficiently useful processes, people or topics best left alone? We could call this leadership judgment, which sounds risky in a hectic global economy with political unpredictability caused by such judgments. There must be a better way to de-clutter and simplify.

Act the leaders!

There are several ways to skin a cat in making an organization more agile. Leadership, program management, technology are among the usual top suspects. Sometimes it does not take a big, brave new idea; simple, practical tools may contribute more than expected.