What's in this article?
In a recent conversation, an industry peer referenced a point made by Kara Swisher about Apple’s success. Apple has mastered the art of focusing on its core competencies while leveraging outside experts for tasks not central to its business. This got me thinking about how companies approach their sales and lead management systems, especially when replacing outdated, rule-based systems with predictive models.
AI in sales management is widely recognized as more efficient and reliable than traditional methods. It helps sales teams make better decisions and achieve better results over time. So, why aren’t more organizations adopting this technology? The answer lies in recognizing what is and isn’t a core competency.
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Benefits of Predictive Models in Sales
Predictive models use data and machine learning to forecast outcomes, such as which leads are most likely to convert. This allows sales teams to:
- Prioritize their efforts
- Allocate resources more effectively
Unlike fixed rules, which can become outdated and rigid, predictive models adapt to new data and changing market conditions. This makes them a better long-term solution for improving the future of lead management and sales performance.
Why Some Organizations Hesitate
While many organizations agree that predictive models in sales are the right solution, they also understand that building and maintaining these models is not easy. Creating production-ready predictive models requires specialized skills in data science and machine learning. For many companies, this is not a core competency. Attempting to build these systems in-house can be:
- Time-consuming
- Expensive
- May not yield the desired results
The Role of Experts
This doesn’t mean that companies should stick with their old methods. Instead, they can leverage the expertise of companies specializing in predictive modeling. Organizations that partner with experts like ProPair can implement advanced AI solutions without developing them internally. This allows them to benefit from the latest technology while focusing on their core business activities.
Moving Beyond Legacy Systems
Staying with outdated systems just because building new ones isn’t a core competency can hold companies back. Legacy systems often rely on fixed rules that do not adapt well to change. This can lead to:
- Missed opportunities
- Less efficient sales processes
Predictive models, on the other hand, continuously learn from new data, making them a dynamic tool that evolves with your business.
Focus on What You Do Best
The key takeaway is to focus on what your organization does best. If building predictive models isn’t a core competency, it’s wise to work with experts who can handle this complex task for you. This allows you to adopt the best technology without taking on the risks and costs of developing it yourself.
Final Thoughts
Organizations that recognize the benefits of predictive models but understand their limitations in developing them internally are making smart decisions. They know that to succeed, they must focus on their core strengths and partner with experts to handle specialized tasks. By doing so, they can move beyond outdated systems and embrace a future where data-driven decisions lead to better sales and improved outcomes brightening the future of lead management.
