HBR frequently features articles that elaborate on how management approaches are changing as a response to the rise of analytics. Authors Thomas Davenport and Randy Bean notice that “there is a tendency with any new technology to believe that it requires new management approaches, new organizational structures, and entirely new personnel.” This is not true they claim, and they continue to provide “two good examples of combining well-established practices with cognitive technology to achieve business success“: Procter &Gamble and American Express. These two companies employ several (seemingly) best practices that prove successful in the transition to the digital age:
- Build on current strengths: Current analytical personnel can (easily) be trained to work with machine learning techniques. Cognitive technology and AI are not so much a new domain, as they are extensions of applied statistics.
- Focus on talent: Build your data science talent pool by combining internal development and mobility with external hiring.
- Do it yourself: It is often more effective and cost-efficient to develop analytical capabilities internally, than to partner up with consultants/vendors.
- A customer focus: Focus on win-win applications first, those which create value for the organization as well as the customers.
- Augmentation, not automation: Focus should not be on cutting labor costs (automating jobs), but on creating human-AI synergies (augmenting jobs).
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