You’re probably feeling it—the pressure to be faster, smarter, and more competitive.
Most of the time, businesses find their solution to that pressure in technology. After all, the more day-to-day processes you can automate, the more time your staff will have to focus on more value-adding activities.
And no one wants to be slowed down by monotonous tasks like responding to emails, scheduling appointments, and paying bills.
But what’s the difference between a process that’s simply automated and one that actually augments your productivity?
Here’s a clear explanation from Kevin Hakman:
“Augmented productivity takes information relating to the work at hand and injects suggestions and recommendations into the workflow so as to empower us to get things done better and faster… Spellcheck is a simple example of augmented productivity that has been around for decades.”
“However, advances in artificial intelligence (AI) are today powering a much broader range of ‘augmented productivity’ applications all designed to save us time, reduce errors, and make better decisions.”
Augmentation, Machine Learning, and AI
Businesses invested an estimated $5 billion in machine learning software in 2016. This new kind of software gives systems the ability to automatically learn and improve from experience without being explicitly programmed.
Likewise, corporate investment in artificial intelligence was predicted to triple in 2017 – with some believing it will become a $100 billion market by 2025. Almost every industry is already being affected, from agriculture to transportation to manufacturing.
Harvard Business Review contends that unlike with the internet—an innovation with which latecomers often benefited more than those who were first to market—it’s more likely that the companies that get started immediately with machine learning and AI will enjoy a lasting advantage.
But which processes should be augmented by software? Here are some key areas where augmentation (not just automation) can provide real value to your business.
Current estimates say that 44 percent of U.S. consumers already prefer chatbots to humans for customer relations. Obviously, complete customer service automation is not feasible, but automation technologies do leave room for considerable savings. If 29 percent of customer service positions in the US are automated (as suggested by Public Tableau), companies could save $23 billion in annual salaries, in addition to other workforce costs like health insurance.
Even when a physical person is required to handle exceptions, the algorithm can study the customer service representative’s response to learn what to do the next time around.
Hiring and HR
The average corporate job posting generates 250 applications. Over half of surveyed recruiters say sifting through résumés to come up with a shortlist of qualified candidates is the most difficult part of their job. Software can quickly sift through thousands of job applications and shortlist candidates who have the desired credentials.
Such technology is not just limited to helping fill white-collar jobs. Find out how Worthwhile recently helped match truck drivers and motor carriers to help fill a critical need in the transportation industry through our work with Blue Bloodhound.
Predictive Equipment Maintenance
When a piece of equipment breaks, thousands to millions of dollars can be lost in production. Machine learning algorithms fed by connected devices collecting data can detect anomalies in equipment that indicate when it’s at risk—so maintenance can be carried out before it stops working.
Another example of how this could be helpful is in the transportation industry. Predictive maintenance for a train axle could prevent hundreds of passengers from being stranded in the countryside, waiting for an expensive repair. Instead, once a potential risk is identified, the train can be diverted to maintenance before it fails, and passengers can be transferred to a different train.
Logistics and Navigation
One of the best examples of software that has revolutionized transportation by gathering real-time traffic and road information is the WAZE app. Information about accidents and other delays is shared by other drivers, saving everyone time and gas money as they plan their travels accordingly.
Worthwhile recently created similar, real-time software for South Carolina’s forestry and logging transportation industry. On any given day, around 900 trucks are on the road in the state, transporting wood to and from sawmill locations. But without information from the sawmills themselves, logistics coordinators had no way of knowing which locations needed more trucks and which already had long wait times. Read more about the solution that uses crowdsourced data to make the industry more efficient and reduce carbon emissions.
In the insurance industry, determining whether a claim is eligible or not is a decision with significant financial and customer-satisfaction implications. But it can be difficult for employees to make the right decision in a time-effective manner.
This is another area where augmentation via machine learning can help. By recommending a decision, software can help people work quickly and ensure the optimum decision time after time. Worthwhile has worked with multiple companies to build solutions like these, and they have made a big difference.
With so many opportunities for augmentation, it can be hard to know where to start. What are the priorities?
* The process that’s using the most resources. This may seem obvious, but if you can free up finances by making a costly process more efficient, you may be able to direct more money to tacking other processes.
* The process that’s your pain point. Which process is the most frustrating or the one that leads to delays in other areas? Tackle this one, and everyone will thank you.
* The process that’s used the most. You’ll get the most bang for your buck when you augment processes that are used most frequently by the most people.
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