Is there a business case for the Chief Analytics Officer?

The past decade has seen huge growth in the practical use of data mining and analytics. Increasingly, analytics is being used not just to inform decision makers; it is being embedded into operational systems and processes. As analytics becomes increasingly business critical, I share a few thoughts on the question: is it time for the Chief Analytics Officer (CAO)?

Contributions of a CAO

Executive officer (CxO) roles are responsible for setting strategic objectives, making strategic decisions, leading employees to achieve objectives, directing day-to-day operations, executing change, and monitoring performance against the business strategy. A good starting point for defining the role of the CAO is to describe how an analytics professional might fulfil these CxO functions. My thoughts are summarised in the table below. In my opinion, these contributions certainly can amount to a substantial and valuable CAO role. So, my next question is: When does the CAO role make sense?

CxO Function CAO contribution
Set strategic objectives
  • Ensure Executive understands how analytics can be exploited to achieve strategic objectives (e.g. gaining competitive advantage)
Make strategic decisions
  • Contribute to decisions about using analytics to achieve strategic objectives
  • Provide analytical insights into the enablers and constraints on achieving strategic objectives
Leadership
  • Provide clear direction to the analytics function and/or analytics teams embedded within business units
Operational Direction
  • Ensure business operations are effectively supported by analytics
  • Ensure operational analytics systems perform well for the business, achieving required service levels
Deliver Change
  • Act as the senior responsible owner for analytics projects
  • Ensure the use of analytics is embedded within projects delivered across the business where it can reduce costs or improve the quality of what is delivered
Measure and Monitor Performance
  • Ensure analytics is used to create the most effective business performance measures
  • Ensure the Executive is provided with the analytical insights to explain why the business is performing in the way it is and how performance can be improved

Conditions for a CAO

These CAO contributions can only be made when an organisation is committed to institutionalising data-driven decision making. By this, I mean that a CAO can only perform effectively if the rest of the Executive truly wants to use evidence-based insights from data themselves and want to see all employees doing the same.In a culture where evidence is either ignored or used only to support personal agendas, the true value of analytics cannot be realised. In such conditions, a CAO’s value is diverted by the battle to change decision-making culture.

I suggest the following conditions need to be present for a CAO to be a truly worthwhile addition to the Executive Board:

  • The Executive as a whole is committed to benefitting from analytics
  • Senior managers appreciate the business value that analytics can provide (they “get it”)
  • Analytical applications are already embedded within the organisation
  • Most or all decision makers are data hungry and base decisions on evidence
  • The CAO role is defined to be clearly distinct from other CxO roles (particularly Chief Finance, Chief Information and Chief Risk Officers)

What makes a good CAO?

Assuming that we’ve met all of the above criteria, and are confident that having a CAO is a good idea, what kind of person are we looking for? I propose no definitive qualities needed by a CAO but instead make some observations about the nature of business decisions.

As we progress through decision making processes, the emphasis shifts between different modes of behaviour. Business problems are social constructs, as they concern how the organisation responds to the actions of other groups, such as customers, competitors and suppliers. Ensuring business problems are well defined principally concerns ensuring effective group dynamics (for example, avoiding ‘groupthink’).

With a problem defined, we go on to identify feasible solutions and evaluate their pros and cons. This is the time when normative evidence-based analysis comes to the fore. Often, this stage of decision making is led by analytical professionals.

Following analysis of the options, a shift is made from “decision making” to “decision taking”. In other words, we shift from defining the problem to focus on the act of choice. At this stage, cognitive factors, such as the decision maker’s ability to interpret the evidence, the proportion of their time and attention they give to each piece of evidence, and similar factors are pivotal. It is at this stage that many so-called “judgemental errors and biases” come into play (see, for example, the works of Daniel Kahneman, Amos Tversky).

Finally, we conclude with the act of choice itself. For the individual, the choice is influenced greatly by psychological factors, such as personal values, needs and preferences. This is combined, though, with the social dynamics of collective and organisational decision making.

Analytics approaches decision making from a normative perspective. A CAO can add value by ensuring analysis is done to a high standard and working to ensure the normative (i.e. evidence considering) aspects of decision making are given due weight and are supported by high quality analysis. A truly effective CAO is also able to ensure that the social, cognitive and pyschological aspects of decision making are treated with equal care. In this respect, the role of the CAO is not merely to be a great analyst and/or advocate of analytics but a person committed to improving the quality and integrity of decisions and decision making processes of all kinds.

 

 

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