Hindustan Times (Delhi)

Why decision intelligen­ce is crucial for a career in digital entrerpris­es

While decision intelligen­ce is crucial everywhere, it is a critical capability required in a digital enterprise where all sorts of data, informatio­n or knowledge are the only resources that can create a competitiv­e advantage

- Dr. Roger Moser letters@hindustant­imes.com

nIn 2018, Google defined “Decision Intelligen­ce” as a key element of further competing in an increasing­ly digital economy and society. Cassie Kozyrkov, Chief Decision Scientist at Google wrote in the same year: “Decision intelligen­ce is a new academic discipline concerned with all aspects of selecting between options. It brings together the best of applied data science, social science, and managerial science into a unified field that helps people use data to improve their lives, their businesses, and the world around them.”

Why go Google and other tech companies like Alibaba, best known for their capabiliti­es to deal with big data and artificial intelligen­ce, put suddenly such a strong emphasis ‘old-fashioned’ social and managerial sciences?

An answer might be that the business environmen­ts of companies around the world are progressiv­ely becoming more volatile, uncertain, complex and ambiguous, often denoted by the acronym ‘VUCA’. In such a VUCA world, the business models of all sorts of companies are increasing­ly challenged by developmen­ts such as swift policy changes, fast macro-economic and social trends as well as disruptive technologi­cal innovation­s and advancemen­ts. One such major disruptive developmen­t is the shift to an increasing­ly knowledge-based and digitalize­d society and economy, also in India.

DECISION INTELLIGEN­CE AS THE FIT BETWEEN INFORMATIO­N REQUIREMEN­TS AND INFORMATIO­N PROCESSING CAPACITIES

In such dynamic environmen­ts, the informatio­n requiremen­ts of senior executives and other managers to formulate competitiv­e strategies are exacerbate­d. Senior executives and other decision makers increasing­ly rely on big data-driven approaches.

At the same time, the way individual­s, groups, organizati­ons, and industries work and collaborat­e are being transforme­d by the capacity to store, communicat­e, and compute informatio­n – resulting in new and different types of digital enterprise­s. However, with an almost unlimited access to an array of informatio­n sources, senior executives and their middle managers also face a host of challenges, such as potential informatio­n overloads leading to biases in judgements, costs associated with managing vast informatio­n, and the risk of being distracted from truly relevant informatio­n. From a career perspectiv­e, any future leader in a digital enterprise must therefore be proficient at filtering insights that really matter from the informatio­n (over)loads they are exposed to.

Almost 30 years ago, scholars had already identified that a misfit between the informatio­n requiremen­ts of a company and the way it gathers and processes informatio­n increases the likelihood of accidental­ly neglecting relevant factors, filtering out important informatio­n, or relying on misleading clues.

Recent research has further empiricall­y confirmed that a better fit between the various levels of informatio­n requiremen­ts of a company and its informatio­n processing capacities leads to superior levels of strategic insights, and subsequent­ly to firm performanc­e. The same research also confirmed that there exist different ideal informatio­n gathering and processing profiles depending on the VUCA environmen­t a company operates in. However, today’s reality for most executives is still well described by what Prof. James G. March wrote already 25 years ago: “Decision makers and organizati­ons (a) gather informatio­n but do not use it, (b) ask for more and ignore it, (c) make decisions first and look for relevant informatio­n afterwards, and (d) gather and process a great deal of informatio­n that has little or no relevance to decisions”.

DECISION INTELLIGEN­CE COMBINES MANAGERIAL & SOCIAL SCIENCES WITH DATA SCIENCES

Some years ago, we have therefore developed the Decision Intelligen­ce Navigatort­m to support companies in achieving and sustaining competitiv­e advantages in a VUCA world. It stands for a different perspectiv­e when thinking about strategic analyses and the creation of competitiv­e advantages – especially for digital enterprise­s which often face “the winnertake­s-it-all” markets and where any strategic mistake can ruin the company. Although Decision Intelligen­ce is pioneered by tech giants like Google or Alibaba it is less about data analytics or artificial intelligen­ce but about the capability to combine the right analysis frameworks from social & managerial sciences or engineerin­g with the most suitable informatio­n gathering and processing solutions.

According to our experience with multinatio­nals, SMES and start-ups the effective applicatio­n of Decision Intelligen­ce in a company builds on the four elements of the Decision Intelligen­ce Navigatort­m:

•DECISION CONTEXT: Do the executives in a company understand the decision challenges they face and sufficient­ly reflect on what kind of frameworks and intelligen­ce (data, informatio­n, knowledge) they need?

•FRAMEWORK PROFICIENC­Y: Do executives master enough social sciences and managerial frameworks to select the most appropriat­e analysis concepts for any decision challenge they face?

•INTELLIGEN­CE ACCESS: Does a company provide access to the necessary data analytics tools and databases to gather and process the necessary intelligen­ce?

•DECISION PROFICIENC­Y: Are executives able to turn strategic insights into effective decisions and implementa­tion plans?

While Decision Intelligen­ce is crucial to a career in any company, it is most likely to be the most important capability of any executive in a digital enterprise where all sorts of data, informatio­n or knowledge are basically the only resources that can create a competitiv­e advantage. Thus, if you aim at a career in a digital enterprise or tech giant, do not underestim­ate the value of social sciences to reach the top.

The author is Senior Lecturer, Macquarie Business School, Macquarie University, Sydney, Australia & Adjunct Professor of Business Policy & Strategy, Indian Institute of Management, Udaipur, India.

 ?? ISTOCKPHOT­O ?? Digital enterprise­s need those good at filtering insights n
ISTOCKPHOT­O Digital enterprise­s need those good at filtering insights n

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