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Incentives are a great tool that can help align sales behavior to corporate goals, but its efficacy depends on the quality of the plan itself, and on the process of calculating and communicating what each sales rep or dealer will receive as reward for their performance. The three key pillars of incentives compensation management are: data, technology and people.

Data is key for accurate sales planning and designing a compensation plan. The strongest sales organizations are those with the deepest insight and visibility, which means the most accurate and complete data.

Technology is the enabler of process automation when it comes to designing and calculating complex plans. But if the technology is right, it can also be the lever to turn data into useful insights.

People, as always, are at the center of everything. Incentive compensation plans are created by people to influence the behavior of other people. Compensation analysts design, calculate and manage plans that will have a direct impact on sales reps and dealers. They are also responsible for handling disputes if there are discrepancies between expected and actual payouts.

When someone realizes how challenging it is to design and manage an effective incentive compensation plan, and considers the benefits that artificial intelligence can provide, it becomes inevitable to wonder, what impact can artificial intelligence have on the sales compensation process?

Let’s look at some of the major challenges that sales organizations face, and compensation analysts in particular:

1. Reviewing incentive compensation plans

90 percent of U.S. companies change their incentive compensation programs on an annual basis, and service providers are no exception. But what exactly are these adjustments based upon? Are they going to lead to the desired business outcomes? How confident are you that they will be successful? Is there a better way to identify which changes need to be made?

Most operators already have dedicated analysts that design, monitor and adjust these programs, but they are manual processes that require a lot of human oversight.  Often these adjustments are made well after there is any potential to change employee behavior when it is needed most. Typically, before the end of the quarter or end of the year. In other words, they are not timely enough.

What if optimal changes could be identified mid-period and put in place well before it is too late? Better yet, what if the incentive compensation solution itself could identify, recommend and implement plan changes?

2. Managing disputes and operational inefficiencies

Conflicts over incentive compensation always occur more often than they should, especially in a complex sales environment and with inefficient systems. The process of resolving disputes places a huge administrative burden on sales operations, and is costly, both in terms of revenue and wasted time. In fact, payment inaccuracies often result in “shadow accounting” – sales reps verifying manually that their real sales stats match their latest paycheck.

Every organization tries to avoid this by streamlining processes and keeping track of all the activities, but have you reached your optimal point? Probably not.

What if sales reps and dealers could have a self-service interface to handle their most common queries? Better yet, what if the incentive compensation solution itself could monitor and audit the accuracy of events prior to calculating commissions?

3. Preventing dealer fraud

According to the Communications Fraud Control Association (CFCA), dealer fraud is responsible for $3.1 billion in annual losses to telecom carriers. This problem is something service providers are aware of, but that doesn’t mean they are truly protected against it.

Dealer fraud is typically detected after the damage is done, and by that time, revenue leakage is inevitable.

What if you could measure the risk each of your dealers represents, and manage incentive compensation plans and timings accordingly?

As the business environment becomes increasingly competitive, service providers need better insights and more data-driven processes to gain a competitive advantage. That’s why artificial intelligence and machine-learning are becoming popular in the field of incentives compensation management. Considering all of these challenges, here’s how artificial intelligence (AI) and machine learning (ML) can transform the incentives compensation practice for service providers: 

- Optimizing incentive compensation plans

Data-driven sales planning is what AI and the right data enable. The technology continually retrieves data, analyzes different compensation models and incentive scenarios, to detect patterns and suggest optimizations regarding performance, resource capacity and costs, thus enabling automated plan optimization.

- Managing disputes and operational inefficiencies

Chatbots are a tangible form of AI that gives sales reps and dealers the flexibility to manage common issues in a self-service fashion. The bot uses natural-language processing to understand the questions being asked, interpret responses, and generate follow-up questions. Instead of submitting tickets and waiting for a resolution, sales people can resolve their questions by themselves, accelerating response times and freeing up analysts.

- Preventing dealer fraud

The risk of a new dealer acting fraudulently, or breaching service level agreements may lead to higher costs, revenue losses and reputational damage. AI technologies can be used to increase the precision of dealer scorecards, which output numerical values that rank-order the probability of a certain outcome, such as new dealers engaging in fraudulent behavior. These scores make it easy to set thresholds, above and below which different automated actions are triggered.

Artificial intelligence and machine learning are about applying learned data to help guide your decisions, and ultimately achieve more efficient outcomes. Incentives compensation is about creating rewards to shape sales peoples’ behavior. When you base these rewards on the accuracy of data science and machine learning, you create the potential to optimize your sales performance, achieve the expected business outcomes, and create more value for the organization.

WeDo Technologies is committed to harness the transformative potential of AI and embed it into its full solution portfolio. RAID Incentives, part of the Business Management portfolio, is commission management software tailored to the telecom industry. It empowers its users to ensure error-free commission and compensation payments, enhances operational efficiency through automation, and drives productivity, powered by artificial intelligence and machine-learning features.

If you want to learn more about how we are using AI and ML to transform incentive compensation management, reach out to us.

 

Ebook Incentives Management

Mafalda Póvoas

Product Marketing