How can Automation help your company?


Senior executives need to understand the tactical as well as strategic opportunities, redesign their organizations, and commit to helping shape the debate about the future of work. We are on the cusp of a new age of automation. Robots have long been familiar on the factory floor, and software routinely outperforms humans when used by delivery companies to optimize routes or by banks to process transactions. But rapid strides being made in artificial intelligence (AI) and robotics mean machines are now encroaching on activities previously assumed to require human judgment and experience.

For instance, researchers at Oxford University, collaborating with Google's DeepMind division, created a deep-learning system that can read lips more accurately than human lip readers—by training it, using BBC closed-captioned news video. Similarly, robot “skin” is able to “feel” textures and find objects by touch, and robots are becoming more adept at physical tasks (such as tying a shoelace) that require fine motor skills. There are still limitations. Machines lack common sense, can't always pick up on social and emotional cues, and still struggle to understand and generate natural language. Yet the pace of technological progress, propelled by massive increases in computing power and cloud storage, suggests the next frontier will soon be crossed.

Senior executives have two critical priorities in this world. First is to gain an appreciation for what automation can do in the workplace. While cost reduction, mainly through the elimination of labor, attracts most of the headlines and generates considerable angst, our research shows that automation can deliver significant value that is unassociated with labor substitution. In this article, we describe a wide range of business opportunities that automation is creating: for example, helping companies get closer to customers, improve their industrial operations, optimize knowledge work, better understand Mother Nature, and increase the scale and speed of discovery in areas such as R&D.

As leaders consider this wide range of possibilities, they have a second priority, which is to develop an action plan. That plan should include a view of both tactical and strategic opportunities for their companies, a blueprint for building an organization in which people work much more closely with machines, and a commitment to helping shape the important, ongoing debate about automation and the future of work.

How can automation help?

To gauge the business-performance benefits that automation could deliver beyond labor-cost savings, we asked experts to consider how it could transform working practices in a range of settings—a hospital emergency department, aircraft maintenance, an oil and gas operation, a grocery store, and a mortgage brokerage. The results, though hypothetical, are striking. Measured as a percentage of operating costs, the changes deliver benefits ranging from 15 percent in a hospital emergency department, to 25 percent for aircraft maintenance, and over 90 percent for mortgage origination.

While labor substitution accounts for some of this value, additional performance benefits are considerable in all cases, and sometimes greater than the value of labor-cost reductions. In oil and gas operations, for example, performance gains in the form of higher throughput, higher productivity, and higher safety—all unrelated to labor substitution—account for fully 85 percent of the potential value unlocked by automation. And that's just one example. Automation is enabling companies to make the following far-reaching set of moves:

  • Get closer to customers. Affectiva, a Boston-based company, uses advanced facial analysis to monitor emotional responses to advertisements and other digital-media content, via a webcam. Citibank works with Persado, a start-up that uses AI to suggest the best language for triggering a response from email campaigns. The results are a purported 70 percent increase in open rates and a 114 percent increase in click-through rates. And Kraft used an AI-enabled big data platform to reinvent its Philadelphia Cream Cheese brand by better understanding the preferences of different consumer segments.
  • Improve industrial operations. GE uses machine-learning predictive-maintenance tools to halve the cost of operations and maintenance in certain mining activities and so extend the life of its existing capital. Rio Tinto has deployed automated haul trucks and drilling machines at its mines in Pilbara, Australia, where it says it has seen a 10 to 20 percent increase in utilization in addition to lower energy consumption and better employee safety.
  • Optimize knowledge work. It's becoming more common for a software robot to receive a user ID, just like a person, and then to perform rules-based tasks such as accessing email, performing calculations, creating documents and reports, and checking files. Besides scalability and higher throughput and accuracy, the results include built-in documentation of transactions for audit, compliance, and root-cause analyses. Meanwhile, numerous financial institutions and other companies deploy robotic process automation to collect and process data.
  • Harness the power of nature. Land O'Lakes' WinField United compiles data on US crops to help farmers make key decisions throughout the year, including which seeds to purchase, soil and nutrient requirements, and yield potential. Meanwhile, the Coca-Cola Company's Black Book model uses algorithms to predict weather patterns and expected crop yields to inform procurement plans for their Simply Orange juice brand, so that no matter what the quality and quantity of the crops, they can be blended to replicate the desired taste. The model also enables the company to overhaul its plans within minutes if weather conditions threaten to damage crops.
  • Increase scale and speed. The potential for AI-enabled automation to create scale, boost throughput, and eliminate errors creates a range of opportunities for discovery in R&D. For example, GlaxoSmithKline's machine-learning-enabled model-selection process helps the company analyze many times more models in a matter of weeks as it could in several months using traditional processes. In the automotive industry, Nissan has cut in half the time it takes to move from final product design to production, thanks to digital and automation. And BMW has reduced machine downtime significantly in some of its plants through AI-enabled condition-based maintenance, effectively generating fresh economies of scale with minimal investment.
Mritunjay Kumar
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