In the age of digital disruption, even the world’s largest companies aren’t impervious to agile competitors that move quick, iterate fast, and have the capacity to build products faster than their peers. That’s why many legacy organizations are taking a closer look at business process management.
Simply speaking, business process management is the practice of reengineering existing systems in your firm for better productivity and efficiency. It takes a proactive approach towards identifying business problems and the steps needed to rectify them. And while business process management has traditionally been the forte of management consultants and other functional experts, rapid advancements in artificial intelligence and big data means this sector is also undergoing a fundamental transformation.
So it begs the question—how do you start “plugging AI” into your company’s existing data and systems?
Where to Begin
Artificial intelligence is exciting because it promises to introduce a totally new way to business operations. However, most traditional organizations don’t have the necessary infrastructure and/or computing power to deploy these technologies.
Moving your data and applications to the cloud is a very popular solution to unlocking the necessary computing resources, but there's a catch. You can’t just copy-paste your files to the cloud and start using AI. Older systems weren’t built with a cloud deployment in mind, so leveraging the cloud usually requires rebuilding your existing software using a common cloud-ready platform like Kubernetes, Pivotal Cloud, and Docker Swarm.
The point is that once you make a decision towards digital transformation, you need complete buy-in from all areas of the business, and a commitment to process and technology changes. Getting that commitment typically involves showcasing the real benefits that AI can unlock. Let’s take a closer look at how artificial intelligence is actively impacting the way companies do their business.
1. Analyzing sales calls
When it comes to simulating business processes and operations, one crucial aspect is definitely sales calls. That’s because sales—and the ensuing revenue that comes from it—are the bread and butter of your business. Top-tier sales representatives will ensure your firm keeps chugging along and reaching new boundaries.
In the past, analyzing sales calls was a manual process. There might have been a standard sales playbook with generic questions that each individual would be expected to ask. But now, AI conversational tools like Gong are automating this process entirely.
Gong is able to record each outbound sales call that your team makes and pick up on cues that help it determine how the call went. So, for example, a successful sales call will probably see the prospect talking more than the sales rep.
2. Converting voicemail into text
Have you ever heard the phrase, “Your unhappiest customers are your greatest source of learning?” These famous words were said by none other than Bill Gates. But how can you even accurately quantify customer sentiment if you don’t take the requisite steps to track it?
It’s certainly possible that a large chunk of your customers don’t want to remain on hold while waiting for a customer support agent and prefer to leave a voicemail instead. Intelligent automation tools like Workato are making it possible to automate voicemail follow-ups, thereby ensuring that no customer falls through the cracks and each one is given an appropriate response to their concerns.
For example, Workato was able to help automate voicemail follow-ups for a large chain of cafes. Whenever a new voicemail came into its system, the intelligent tool would use speech to text conversion to create a transcript of the voicemail. It would then take that text and add it on the service ticket—giving customer support agents a much better idea of the nature of the complaint and allowing them to resolve it quicker.
3. Detecting fraud
Occupational fraud causes organizations to lose about 5% of their total revenue every year with a potential total loss of $3.5 trillion. Machine learning algorithms are actively quelling this trend by spotting discrepancies and anomalies in everyday processes.
For example, banks and financial institutions use intelligent algorithms to detect suspicious money transfers and payments. This process is also applicable in cybersecurity, tax evasion, customs clearing processes, insurance, and other fields. Large-scale organizations that are able to leverage AI are potentially looking at cost savings in the millions of dollars each year. These resources can then be spent in other critical areas of business such as research and development so companies can stay competitive and ahead of the curve.
Artificial intelligence isn’t just a fancy buzzword that people are tossing around with willful abandon. In fact, every time you take advantage of Google’s typo detection feature (when you see ‘did you mean’ in the search engine) you’re actually plugging into its DeepMind platform—an example of AI in everyday use.
AI has the potential to promote greater efficiency, output, less interruption, and, ultimately, higher revenue across businesses of all shapes and sizes.