Make Data-Driven Decisions With AI

Make Data-Driven Decisions with AI

Using AI to Increase Business-Side Results and Make Data-Driven Decisions

Is there a hotter buzzword than artificial intelligence (AI)? Certainly, AI is on the short-list of promising technologies that could reshape the future. The AI market is projected to reach $37 billion by 2025, with many predicting that it will dramatically shakeup workforces and business management practices.

In fact, some 72% of business executives, according to PricewaterhouseCoopers, believe that AI will produce competitive advantages and of those executives who have already seen AI implemented, 54% report increased productivity.

A Sloan Review survey likewise found that 84% of employees will need to change their skill sets. 47% of respondents believe that AI could cause organizational workforces to shrink. At the same time, however, 79% of respondents believe that current workers will have their skills augmented.

However, we can’t overlook the possibility that AI could reduce jobs. An Oxford University study argues that 47% of jobs could be automated by 2033. This raises some important questions about how the workplace itself will change and what types of jobs people in the future might hold. Technology and jobs have evolved hand-in-hand over the years, but the pace of change is only increasing.

Unsurprisingly, 84% of respondents to a Boston Consulting Group survey acknowledged that employees will have to learn new skills in the future. About 70%, however, don’t fear automation taking their job. Instead, many believe that AI could eliminate some of the duller tasks.

Artificial Intelligence is Already Here

Once upon a time, Artificial Intelligence was a figment of fiction. Now, it’s a reality and many companies are currently using AI for a variety of functions. No, artificial intelligence hasn’t developed a true “conscious,” however, bots and software are now able to perform limited problem solving, thinking, and analysis. The most advanced AI programs of the day can incorporate data into automated decision-making processes and execute actions entirely on their own.

So, what is AI anyway? Artificial intelligence refers to a large variety of concepts and practices. Some subsets of AI include machine learning, robotics process automation, deep learning, and cognitive analytics. As you explore artificial intelligence you will come across these concepts and many others as well.

Often, AI is being unleashed to take care of repetitive processes and to crunch vast amounts of data. SAP, for example, has launched its HANA cloud platform. This platform can automatically analyze and crunch vast amounts of data from databases. In the past, data scientists might have to spend weeks just trying to make sense of all the sales and transaction data. Only then could they start to analyze it.

Often, by the time these data scientists got a grip on the data, it was already out of date. However, with HANA data scientists can quickly compile the data which allows them to focus more on the actual analysis of the data. The data scientists, in this case, aren’t being replaced but instead is augmented and can focus on higher value areas of work.

Another popular and perhaps more tangible use for AI is in chatbots. These chatbots are being rapidly rolled out to greatly increase customer service experiences. In the past, contacting customer service often meant spending long periods of time on the phone listening to elevator music, or waiting a week or more for a reply via email. Chatbots can handle many of the more mundane questions and inquires. They can also escalate issues to the appropriate customer service rep. No more getting transferred from department to department.

Empower Sales and Marketing

A company is only as good as its sales and marketing team. Landing a sale is often a long and intensive process. On average, a sales rep will spend roughly 80% of his or her time qualifying leads and just 20% closing deals. AI, however, can be used to offload some of the burdens of qualifying leads so sales teams can focus on closing deals.

Epson America, for example, found itself overwhelmed by the roughly 60,000 leads it receivers per year. Sales teams were slogging through leads, finding many of them to be cold. So, the company set up an AI program to email leads and to gauge interest. In just 90 days, Epson reported that its AI efforts generated $2 million in incremental revenue!

Before AI, sales reps might send out a hundred emails and perhaps get a handful of responses. Now? If a rep sends out 100 emails, he or she can expect 50 or so responses. As a result of the program, qualified leads have surged by 75%.

Sales reps will spend roughly 80% of their time qualifying leads and just 20% closing deals. Click To Tweet

Increase the Value of Market Analysis

Many managers want to make “data informed” decisions. Rather than relying on gut instinct and luck, business managers can glean insights from data. As already pointed out, data can be difficult to work with. However, AI will make it much easier to compile and analyze vast quantities of data. McKinsey has found that better analysis can generate an ROI of 10 to 20% and can grow profits by 14%. AI will make better analysis much easier to conduct.

What AI-Empowered Predictive Analysis Looks Like

Let’s look at some specific ways AI can be used in analysis. Keep in mind, this list is far from exhaustive and is, but a sample of the potential AI has.

• Scoring leads based on behavior (such as clicks and responses).
• Setting up and assisting with workflow management.
• Integrating data from multiple tools and sources to increase prediction accuracy.
• Identifying the highest performing segments and most valuable customers.
• Enabling data-driven decisions that can be made quickly and pro-actively.
• Track and achieve KPI’s and other goals more quickly.

Conclusion: AI is Here but It’s Just Getting Started

We’re only scratching the surface of AI’s potential. That’s because AI itself is a relatively new tool. Think about how much computers shook up businesses in the 1980’s, 1990’s, and beyond. Or the more recent emergence of the smartphone revolution. Experts believe that in the next 10 to 20 years, AI could prove to be extremely disruptive, greatly out-pacing its current impact.

Ultimately, it doesn’t matter if you see Artificial Intelligence as a threat, opportunity, or something else, you need to pay attention to the evolution of this important technology.