Managing Machine Learning: How to Bridge the Man/Machine Divide
The idea of "learning computers" that become smarter with more time and information used to be confined to the realm of sci-fi or the most cutting-edge technology projects. But fact has caught up with fiction; machine learning is transforming both large and small businesses that want to take advantage of reams of data at their disposal.
Machine learning allows the computation of patterns and outcomes across massive data sets at a scale far greater than traditional analytics could ever achieve. And because the computation is completely independent of manual processing, companies gain the ability to effectively collect and analyze even more data, utilizing the inexpensive storage, computing power and distributed database technologies now available. Simply stated, machine learning begins to present itself as a retailer's best tool in a time where data doubles every two years.
Despite these clear benefits, machine learning still arouses the suspicion of those in organizations who stand to benefit from its adoption. Perhaps the idea of machine learning crunching complex algorithms on an enormous scale lends itself to the belief that the technology spells the end of human analysis in a zero-sum scenario. However, businesses can help employees to more receptively embrace machine learning when guided by the following principles:
1. Honestly assess your company's readiness. Before rushing headlong into machine learning nirvana, determine if your company comfortably accepts new technology in general. The adoption of machine learning necessitates changes in the processes and methods of a company, which may meet with resistance from teams that aren't typically early adopters or are more inclined to adopt technologies after the first movers in their industry have already done so. After analyzing your company's culture, ask yourself if you have a competitor making visible gains with machine learning. If industry rivals are already seeing return on investment from the technology, you're more likely to get a positive response to the idea of machine learning adoption.