The Impact of AI on Sales Performance Management

Artificial Intelligence (AI) will change our world. Though there have been many technology hypes in the last few decades (i.e. cloud computing, big data, robotic process automation, blockchain, etc.), AI will undoubtedly change how we interact with the world around us quicker than we realise. This year, after the release of ChatGPT, businesses are rushing to change existing processes and technologies, and the field of Sales Performance Management (SPM) will adapt to this. This provides the reader with insight into how the SPM technology space will change. 

What New Functionality?

In the short term, functionality will focus on predictive analytics and basic chat bots.  

We foresee the following uses cases: 

  1. Identifying data anomalies in inbound and outbound data, perhaps most crucially payout results
  2. Assisting with sales plan effectiveness analysis, and identifying sales team behaviours that impact sales 
  3. Increased sales forecasting accuracy – though data from SPM may be exported to allow this to happen elsewhere
  4. End user chatbots – helping common commission inquiries and individuals to work through help pages. Some tools already have these allowing simple questions to be responded to, but AI will increase the overall accuracy and proportion of inquiry responses that can be automated 

In the mid-term, functionality will focus on text prompts improving ability of sales reps and admins to interact with the tool.  

The following use cases are expected to deliver benefits: 

  1. Sales reps can get useful answers to complicated questions, for example: 
    a.
    Which deals should I prioritise to make quota?
    b. W
    hich deals haven’t been touched in a while?
    c. W
    hich deals are at risk and why?
  2. Managers will be able to ask for more complicated analysis, such as, “show me the top 10 sellers for new business.”
  3. Admins will be able to complete operational tasks quicker through text prompts for general operation tasks. For example, the command “run calculations from April to June 2023, send me an email when done with a link to the report for John Smith”. Note: Expect that instructions for changes in the configuration of the tool, will require an intermediary approval step.
  4. In the slightly longer term, admins will be able to complete configuration tasks through text prompts. For example ,“create a Business Development Representative (BDR) plan which works the same as the Inside sales plan, but with no revenue component.”
  5. Help page chatbots – helping admins and developers to answer questions quickly from the help documentation, such as, “what formula do I use to calculate an attainment?” 
When and which technologies will leverage AI soonest? 

Most leading technologies have some AI functionality as part of their tool, but the uptake has been slower than many have expected. This in part is because the use cases so far have been admin focused on predictive analytics, which is not always an additional responsibility that system owners are looking to take up. We expect that once companies benefit from the more advanced AI offerings out there, to the core purpose of their SPM, in particular the use of chat bots, this will change. We expect most companies to be using AI as part of their SPM within the next 1-2 years.  

Which technologies will be quickest in developing this?  

Technologies that will develop AI capability soonest will: 

  1. Invest in their roadmap
  2. Have the most to gain from reducing implementation time and costs (the more enterprise tools perhaps)
  3. Have the most to gain from reducing operating time and costs
  4. Be the easiest for AI to learn. My expectation is that those with structured data models, and less configuration complexity, will be easiest to learn.  

Some of the factors that determine this are: 

Training data availability– Training data, perhaps from knowledge bases and community forums, but potentially also created examples. We may see contractual changes here, to allow technology providers the use of customer data for training purposes, with some new frontiers opening up in data protection language. 

Transference – How readily the AI can apply its existing knowledge to the tool. For example, the AI may have ability in SQL that it can reapply easily.

Complexity – Simpler tools, may have a higher knowledge requirement (more formulas to remember) but lower conceptual complexity (less tables). The more free-form tools require less knowledge but deeper understanding of concepts.  

What secondary effects will AI have on the SPM technology landscape? 

AI capabilities are not featured in many SPM technology selection processes today. As benefits of AI are proven, the AI capabilities of SPM technologies and roadmaps will become a key differentiating factor. The ability to calculate complex incentives and provide flexible and visually appealing reports was the battleground for SPM vendors five years ago. AI is likely to form the next arms race in the SPM space. It will be interesting to see how the SPM vendors differentiate themselves here. 

Other than the new functionality detailed above, we expect AI will change the SPM technology space in the following ways: 

  • Separated licence cost – Expect that once AI technology matures, companies with large existing customer bases may sell AI as an extra module at additional cost. Potentially a significant benefit of being an early adopter here. 
  • Direct data integration a must – Not all AI analysis will not be done within the SPM tool, some will accumulate to the system with most data, such as the CRM, ERP and marketing automation platforms. This will push vendors to develop more robust APIs and integration capabilities, leading to a more interconnected technology ecosystem  SPM Technologies with weaker data integration capabilities will adapt or see difficulties.  
  • Broadening of SPM offerings– As AI becomes more powerful, there will be a benefit of using it in areas connected to, but not directly linked to, SPM. The SPM technology providers that offer territory management and sales planning activities will ultimately be able to offer more powerful AI features. 
  • Humans as checkers – The current use of AI that we have seen, often requires human validation. It is an open question, how quickly we want to remove humans from the loop completely, and in which cases. In the mid-term expect that humans will spend more time validating/confirming actions required by the AI (which will further improve the AI). 
  • Code language change – In mid-term expect that SPM technologies may move to more general technologies for customisations and move away from custom dialects such as xSQL and Groovy, to take benefit of more advanced AIs trained on more standard code dialects. 
  • Enhanced reliability – Back-end teams managing cloud architecture will also benefit from the benefits of AI. In the mid-term we expect self-healing tools, which could further reduce down-time. 
  • Redefined sales roles – As AI takes over more administrative and data-driven tasks, the role of sales reps will shift. Sales teams will spend less time on routine tasks and more time on building relationships, understanding customer needs, and providing value-added services. 
  • Increased demand for customization –  No two businesses are the same, and as AI becomes more sophisticated, there will be a growing demand for customizable AI models that cater to specific industry needs, regional sales patterns, or unique business models 
What effects will AI have on implementing an SPM? 

OpenSymmetry expects that the impact of AI on implementing an SPM technology will be significant in the short, mid and long term.

1. Reducing build time and cost – 

In the short term, the cost of some customisations will be drastically reduced. New implementations where customisations are made through commonly used coding languages such as SQL or JavaScript will benefit most. Where coding languages are specific to the SPM technology, these will benefit less. 

In the mid to long term, configuration costs will reduce once admin text prompts become more robust. An example text prompt, shows the potential benefit: “Create a direct and indirect credit rule, that filters for new business transactions”. Expect that an intermediary approval / confirmation step will be required. There is certainly some risk here that moving too fast may break too many things as a result of the unintended consequences of actions.

2. Reducing testing time and cost 

In the short term, expect that testing timelines will reduce slightly. It will become common practice for test data to be created through the use of AI instead of through excel spreadsheets.  

In the mid-term, admin operational text bots will further reduce the cost of running test cases.

3. Resource Expectations – In the longer term, as simpler work becomes completed or is at least sped up by the AI, only those with extensive knowledge of technologies or deep consulting skills will be able to continue to provide value. The expectations of consulting resources will increase.

Larger benefits of an AI with SPM  

AI capabilities will bring significant benefits to users of SPM technology.  Some of the key ones we foresee below:  

  1. Less sales time wasted – Sales people will be able to understand their compensation quicker, through the use of AI chatbots, further reducing shadow accounting
  2. Improved sales and management decision making – Ability to coach sales reps will improve with managers and sales reps receiving custom coaching advice
  3. Better forecasts – Predictive analytics will improve forecasts, which are important for executive decision making and commission accrual
  4. Fewer inquiries  – Inquiries handled through better chatbots, fewer compensation errors through anomaly detection, this saves sales and admin time
  5. Fewer, more powerful administrators –  Each administrator will be able to get more done, quicker
  6. Enable more tailored compensation plans – Although a tension will remain between plan complexity and understandability, some comp plans which are not used due to perceived maintenance or implementation complexity will be used – think monthly plans.
  7. More profitable revenue through better compensation plans – Over time compensation plans will improve based on what is shown to be effective, ultimately driving more profitable revenue for businesses
  8. Reduced implementation costs – Implementation costs for the same scope will reduce 
How can you benefit? 

If you’re thinking about SPM technology – Talk to OpenSymmetry for more details on how the different technologies compare, and how they can help you. 

If you’re implementing, or have an SPM technology in place –  OpenSymmetry will help your organization become an early adopter. Early adopters may receive significant benefit in exchange for input and feedback at very limited risk. Expect that as SPM technologies mature in terms of AI, additional changes may be levied for this additional functionality, so it could benefit you to take action sooner rather than later.

Article written by: Edward Moss

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