New skills, new manager on the block
As a manager, you ask yourself – what will I be doing more over 12 months, over 5 years – and what will I do less.
One thing is for certain – still more computer oriented skills are expected from the managers of tomorrow. In the 80-ties, managers embraced spread sheets – beginning of the 90-ties word processors became standard on their PC.
Now in 2020, internet browsing has become a basic commodity – something that is available to so many people around the globe. ‘Commodity’ also means – nothing special. The next step is Big Data in the internet revolution. Big data is really something most managers should consider working with themselves, as supported by studies. “The managerial challenges, however, are very real. Senior decision makers have to embrace evidence-based decision making” [Harvard Business Review, Oct. 2012].
Eager managers do begin configuring rudimentary cloud services
Increased usage of big data by managers means that they will want to understand how the numbers, analytic results, algorithmic predictions and key performance indicators are calculated. You trust what you thoroughly understand. In fact, big data analysis was mentioned as a required management skill in 2019 [Journal of Business Research]. Three computer related skills were attributed to present-day managers: Emergent technologies, Decision making tools and Big data analysis.
Looking for large common denominators, emergent technologies being spent management time on include
• Cloud computing,
• Predictive analytics – Big data,
• Online management
Eager managers do begin configuring rudimentary cloud services – for example setting up a relational database with relevant data items. And – why not? It is less complicated to do using the web interfaces of contemporary cloud vendors. Setting up a responsive web-application in the cloud – that is delegated to computer engineers.
Predictive analytics is a natural extension of skills that are being taught for decades at MBA classes and economics studies. A definition, “Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events” [Wikipeadia]. What has always been part of the bachelor and master curricula at business schools, is statistics.
Statistics – linear/logistic regression, discriminant analysis – they are the basis for predictive analytics in the big data area. Big data arrive on the fly – in vast quantities. Still more cloud solutions are available to assemble, organize and filter these data streams. Managers should be able to oversee these data silos in their company.
So cloud technology and big data go together in contemporary business.
Predictions from machine learning models go far beyond what a basic statistical package could do 20 years ago. Ready-to-use software services like Amazon Rekognition can be trained to recognize objects, scenes and photos of for example landscapes that are relevant to your market. Deep learning neural networks is the key technology used in Rekognition.
As a manager, you will want to have insight into why a specific analytic prediction is most likely. This will make solid any resulting decision making that follows. Which factors contribute the most? Such insight is not provided by deep learning models. A good way to ensure insight and understanding of your big data streams, is to work with the data yourself also. A recent survey shows that the average manager in the US spends 1 hour and 45 minutes per day on own projects [Cmoe blog].
Business moves fast – so you need the market and customer information to be readily available, transparent, convincing and with a high level of credibility [Harvard Business Review, 2011].
Online management coins the process of managing employees working remotely. The numbers of people working primarily from home are growing. Besides emails and the often included attachments, managers employ more recent types of software technology to communicate with remote employees as well as stakeholders within – and even outside their own organization. Several web-based software tools facilitate combined video and audio connections between groups of people.
Getting ahead of emergent technologies
The essential way to get over the hill, is to begin working with big data and predictive analytics. Configure a relational database with 1-2 tables in an available cloud service. Upload some business data from your company into the database. And then – work the numbers. It can be an idea to fetch your 2nd year business statistics book and build a regression model, from your data stored in the cloud database.
A next step can be to build a predictive classifier. You will be surprised just how versatile classifiers are.
Get together your results into a presentation – and share it with a few colleagues. As the average manager spends more time working with teams than on their own [Cmoe blog], there is plenty of opportunity to discuss the predicted results.
Visit Insight Classifiers where you can build and use your own predictive analytic models on-the-fly. The prediction models are stored in our cloud, for your later use.
McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard
Business Review, 60, 60–66.
Sousa, M. J., & Rocha, Á. (2019). Skills for disruptive digital business. Journal of Business Research, 94, 257-263.
Oldroyd, J. B., McElheran, K. & Elkington, D. (2011). The Short Life of Online Sales Leads, Harvard Business Review, 89(3).
Cmoe blog: https://cmoe.com/blog/how-leaders-spend-their-time/
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© Insight Classification Technologies, 2020.
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