Many of you will be familiar with the Hollywood hit movie Moneyball, which told the story of how the use of data and algorithms in American baseball assembled a winning team. It feels as though we’re now at a tipping point in how algorithms (and also artificial intelligence) will be heavily immersed into society and business. Narrowing down to the discussion point at hand - both hold unbound and unthought of potential in transforming how humans come to optimal decisions.


Data, algorithms and sources of competitive advantage

The increased volume and velocity in the accumulation of data means it can be daunting for a business to effectively use algorithms and AI to help make decisions. Whether these are strategic decisions (for example, influencing a company acquisition decision) or smaller day-to-day decisions (what should my next action be on a sales opportunity). In addition to this, the majority of companies in the present day use information systems that cannot process all of this data, let alone use it to predict and better competitive positioning.

It doesn’t seem completely irrational to think that a world in the future could mirror a Minority Report level of artificial intelligence - one where algorithms evaluate multiple scenarios, data points, potential outcomes - and provide us with optimal actions to take. This next-level type of decision-making would undoubtedly offer competitive advantages to those willing to adapt:

  • Speed of decision-making - e.g. computing power would come to optimal decisions far quicker than humans alone.
  • Minimising human bias and error - e.g. algorithms are not influenced by emotion and impulses in decision making.
  • Increasing the breadth of data considered - e.g. cross-analysis of data from markets, geo-political, economic, currency headwinds, traditional and social media, amongst many others.
  • Evaluating multiple “what if” scenarios.
  • Capitalising on previously unthought of market opportunities - e.g. entering new markets through technological disruption not thought of within the initial human field of thought or vertical integration strategies.


Human Business Acumen versus AI and Algorithms in Decision Making

An interesting sub-plot to unravel is the dynamic between human derived business acumen and the increased use of AI and algorithms. Will the former be devalued with an increased faith put into AI and algorithms for decision making? Posing the above question is not how it will play out in real-life - one will not simply replace the other. But it is an interesting subplot nonetheless.

An important consideration of comparing the two is the context. For example, algorithms are able to outperform humans in active stock management, but the interpersonal communication skills required to negotiate and close a sales deal are secured through a human connection. Manufacturing process-level decisions are made by algorithms, but a human resource hiring decision is deeply influenced by a human connection.

For a human to acquire a high degree of business acumen requires years of education, nurturement, personal development, and on-the-job experience. This produces one human to various capability standards -- and are often regularly replaced at a high cost. An artificial intelligence decision-making engine learns and adapts at a rate, speed and scale like no human can. In the future a harmony between the two will become the apex for decision-making. An MBA educated individual required for the interpersonal, motivation, leadership and day-to-day management, that is equipped with a cutting edge artificial intelligence system.


Here are some simple examples where AI and Algorithms can be utilised in everyday decision-making:

  • Business forecasting - analysing sales, booked revenue, currency fluctuations, market volatility data to show future financial performance predictions and recommended actions to take now for a desired outcome.
  • Sales management - using sales data, contact information, historical sales data, like-for-like comparisons, and social media data for recommended next steps to progress a sales deal opportunity.
  • Service optimisation - using chat-bots and linguistic analytics to manage customer service at scale, field service routing and optimising field personnel management.
  • Marketing and image processing - using AI-powered image recognition for ad placement decisions on social media.


We’re at a critical moment in time in the adaptation of algorithms and artificial intelligence. If we want to bring this to the zenith of its potential, it will require a re-equipping with the latest technologies and addressing the culture of how people will use them -- and using this entire process as a catalyst for positive change.

To discover more about how AI can revolutionise your customer relationship management practices for the better, download our e-book on AI for CRM.