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1.3. Human and Machine: The Ideal Decision-Making Team

We are in luck because machines happen to be very good at exactly what we are not so good at. Gartner, the information technology consulting and research firm, produces a series of research notes that cover a wide range of topics related to information technology and associated topics and disciplines. The company occasionally issues what they refer to as “maverick” research, which is research that pushes the technological and social envelope on a topic. One such research note,“Judgment Day, or Why We Should Let Machines Automate Decision Making,”46 was written by Nigel Rayner. They believe that we are at a point at which more and more decisions will be automated and the decisions taken by machines will be better than ones made by humans.

In their recent book Race Against the Machine, Erik Brynjolfsson and Andrew McAfee of MIT provide some insight into the question of our relationship to technology. There has long been a question about whether technology will replace us or complement us. This is a question that has been around since the first machine was built. The position taken in Race Against the Machine is that our decisions can be far superior if we leverage those aspects of machines that complement our own facilities. Brynjolfsson and McAfee discuss the 1997 loss of Garry Kasparov to IBM’s Deep Blue supercomputer. The media seized on to the win by Deep Blue; discussed much less was the fact that the best chess champions were actually teams of humans using computers. According to Kasparov, a strong human player using a standard laptop was able to beat Hydra, a supercomputer designed for chess.47 CEOs find that data-driven decisions provide the greatest potential for long-term value creation.48 This really is the crux of the matter: developing and utilizing technologies that compensate for our weaknesses and accentuate our strengths.

Are some HCM decisions best addressed through advanced analytics? The fact is that these new and developing tools could aid with nearly all decisions. Table 1.2 describes some of the important HCM decisions and how advanced analytics can assist.

Table 1.2 HCM Decision Framework

HCM Decision

Challenges to Optimal Decision Making

Advanced Analytical Tool

Alignment with organizational objectives

Tremendous variation of situations and potential policies and practices

Machine learning/expert systems

Workforce planning

Broad scope of pertinent information

Simulation and predictive analytics

Machine learning/expert systems

Selection

Biases

Predictive analytics

Machine learning/expert systems

Performance management

Biases

Predictive analytics

Machine learning/expert systems

Compensation

Biases

Large data sources

Machine learning/expert systems

Collaborative decision making

Data overload

Predictive analytics/expert systems

1.3.1. A Word About AI Tools

A number of different AI software applications are available from various AI vendors. In addition, many different open source and commercially available tools can assist with decision making. I am going to be primarily using a sophisticated expert system called Expert Maker, which includes a broad range of AI tools. You can find these tools on this book’s website: DecisionAnalyticsInc.com.

Depending on your level of interest, you might want to consider a number of open source and commercially available tools, including Python, R, Octave, WEKA, MATLAB, Apache Hadoop, and vendors (including the usual suspects SAS, IBM, Oracle, and SAP) that are developing ever-more sophisticated AI tools in their business intelligence and other offerings. In addition, some smaller companies and start-ups are doing very interesting things. I profile a few in later chapters. There is much more to say about this, so I encourage you to visit the website (DecisionAnalyicsInc.com) to find more information. I also strongly recommend that if you do not know how to code, learn. There are great online resources available to help you with this (Codeacademy, Code/Racer, MIT OpenCourseWare, Coursera, among others).

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