Artificial Intelligence

Leading Next-Generation Sales Teams: The Mandate for Predictable Revenue

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The sales landscape has fundamentally shifted. I keep reading posts and stories about AI replacing sales teams, and it may be for more commodity-type sales, but it will be some time before it replaces Enterprise sales teams. Building relationships and trust is the foundation for an executive to take a risk on your product, especially when it is critical to their success. AI is currently not at that level, and with behavior changing with every key release, building trust with an AI will be challenging for many years to come. But today, AI can be a powerful enablement tool for your team when leveraged correctly.

Your prospects no longer need salespeople for information; they need us for Insight. They have done their research. They expect their time to be an investment, not a discovery exercise. Does your presence and knowledge project confidence and inspire trust? Does the prospect view you as someone interested in helping their business, or just someone trying to close a deal? Impress them, and you could earn the opportunity to dig deeper. Disappoint them, and good luck trying to recover.

Two years ago, I was selling to a Fortune 100 Financial Services company. I understood their business needs, which we easily achieved. We demonstrated that we could take a key manual process that typically took 7 weeks to complete, automate it and maintain full compliance, and complete the task within 10 minutes. The SVP told me his priorities for selecting any new vendor were: 1 – Company Stability; 2 – Relationship with the Vendor; 3 – Product Quality; 4 – Product Value to their business; and 5 – Total Solution cost. Prior to selling their IP, the company fired the sales team, and the remaining execs went in and offered the deal at an even greater discount. It never sold because the executive team did not understand what was important to this buyer. The company had a high-level relationship with the stakeholders, but lacked the trust and credibility that I had built over several months. This is one of the main reasons why I believe AI won’t take over Enterprise Sales anytime soon.

So, how do you get it right?

The question for every CRO or VP of Sales isn’t whether their team is busy, but whether their activity is revenue-focused and leads to predictable and scalable results. There is much money to be made by everyone, but following the same old tired formulas seldom works.

For leaders aiming to build next-generation teams that deliver zero surprises in the forecast, the approach must be recalibrated around three core pillars: Strategic Preparation, High-Agency Coaching, and Outcome Focused Messaging (“context.”) It is much more than cold calling for two hours a day or having 5-10 meetings per week. Things like that are important, but they are just activities if you are not targeting the right companies and people, or if your team blows it once you have found those people. This will be a significant cultural shift for many companies.

Strategic Preparation: From “Discovery” to “Insight”

When a prospect books a meeting, they are giving us one of their most precious assets: time. If we treat that time as a standard discovery call, we set negative expectations, which signals the lack of perspective (the ‘P’ in PIE) and perceived value. This isn’t theory—it’s the PIE framework (Perspective, Insight, Experience) I’ve used to sell large deals, turn around at-risk customers, and scale teams for many years.

The C-Suite Mandate: Accelerate deal velocity by focusing on specific quantifiable impact for your prospects, and increase win rates by targeting identifiable business pain.

  • Come with an Understanding of their Market, Changes, and Competition. Before the first call, we must demonstrate that we’ve already invested time in understanding their operational constraints, their competitive pressures, and their budget priorities. The goal is to move the conversation immediately from the tired, “What keeps you up at night?” to “We have seen [problem] with companies in your industry. Is that something you have experienced or have concerns about?”
  • Long Discovery Calls or Presentations Typically Won’t Work. Customers are fatigued by generic questions. Every interaction must be purpose-driven and meaningful. If the call runs longer than planned, it must be because the conversation has become mutually valuable, not because we were ill-prepared and just keep talking.
  • Discussions Must Be Targeted to the Problems They Are Most Likely Experiencing. This is where we leverage Insight (the ‘I’ in PIE). Use your background and AI to hypothesize the top three pain points before you dial. Our role is to validate these points, quantify the impact, and then introduce a Shared Vision of Success (our solution) anchored by measurable business outcomes.

Player-Coach: Enhancing Team Capabilities, Not Just Motivating Activity

If you are a sales leader who only focuses on closing your team’s most challenging deals, you are creating a dependency, not a capability. A Player-Coach must be accountable for the team’s numbers and its health.

The C-Suite Mandate: Drive organic growth by building repeatable processes and cultivating high-agency talent.

  • Not a One Size Fits All Proposition. True coaching is not a template. It requires a methodical but human approach to diagnostics. That takes time, effort, and a genuine desire to help people grow.
  • Identify Skills Gaps and Tailor Efforts. Test skills, identify gaps, and then create targeted efforts around building skills that address someone’s specific deficiencies. This personalized attention is how we build the high-performance culture and accountability required to sustain long-term success.
  • Leverage the Team – Role Playing and Team Reviews. We must create a culture where knowledge sharing and feedback loops are the norm. Leverage team reviews and structured role-playing to sharpen execution. This is how we transform luck into a predictable process.

Give teams the latitude to adjust their messaging and test approaches. Adapt messaging to business trends, changes in the competitive landscape, and changing terminology. Then, have your team share their experiences and findings (good and bad) with the team to review, provide feedback, and refine. Structured agility helps your team maintain its competitive edge.

The Leadership Mandate: Context Over Content

We are past the hype cycle of AI. The C-Suite doesn’t care about the tool; they care about the ROI and the risk of poor execution. As leaders, we cannot just hand our teams a login and say, “Go use AI.” That’s a recipe for chaos and a quick erosion of professional credibility. We must lead by example.

We need to teach our teams that AI generates content, but humans generate context.

  • Do use AI to deepen your understanding of the prospect’s industry so you can become a true consultant. Use the technology to gain understanding and market intelligence and tie it to your Experience (the ‘E’ in PIE) as preparation before any call.
  • Don’t use AI to automate a thousand bad emails. Mass communication is cheap; individualized insight is priceless.
  • Do use AI to research the one hundred prospects that actually matter. Focused efforts yield significantly better results.
  • Don’t use AI to fake expertise. This leads to the quick death of credibility, as any good consultant will tell you.

The Million Dollar Deal isn’t won by a bot. It’s won by a human who understands the nuances of the prospect’s business, builds trust, and navigates the internal structure and politics. AI is simply the tool that clears the path so you can do that work faster and with better data. AI is leverage, not a crutch.

Call to Action: Are You Building a Team or a Capability?

The next-generation sales leader understands that customer success is at the heart of everything we do. We win when they succeed. Your most valuable asset isn’t your pipeline—it’s the predictable capability of the individuals on your team. Consistently doing the right things is critical to success.

The challenge for every business leader today is this: Are you enabling your teams to sell like consultants, or are you still measuring them (and driving their behavior) on activity-based metrics? Focus on building intelligent and creative teams that deliver consistent results with zero surprises. It doesn’t happen overnight, but it is an investment in your future success.

Let’s discuss how we can implement the PIE framework and position your team to deliver scalable, organic growth in your organization.

Lessons Learned from GTM Consulting

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For the past two years, I have performed part-time, contract go-to-market consulting. My wife had a surgery that had gone wrong 18 months ago, so I needed something that would allow me to take care of her, stay sharp, earn money, and help companies grow.

A generated image of a male consultant working with a sales team.

Most of the work was with small to midsize companies, but the problems and needs mirrored what I have encountered at larger companies. The main difference is that large companies tend to look to software to address problems. In contrast, smaller companies lack the budget for what they view as an unproven solution that increases complexity.

Here are my Top 5 findings:

  1. GTM plans are often developed at the highest levels, often in isolation, without market testing and validation.
  2. Sales teams are pitted against one another, rather than working together to help everyone achieve more (i.e., “A rising tide lifts all boats.”)
  3. Sales teams are focused on selling features rather than solving business problems.
  4. CRMs are not consistently used and often reflect idealized fiction rather than reality.
  5. Sales management and teams are not leveraging AI to help focus their efforts.

Here are the related Lessons Learned:

  1. Identifying common business problems and describing how your product or service solves them should be the foundation of the plan. Perform market analysis. How do companies describe those problems? Their terminology, often found in job ads, can help create effective messaging that resonates. Work to become the natural fit for what your prospects are seeking.
  2. Individual contributors get paid to win, but sales management needs to create incentives for collaborative efforts that lead to wins.
    • For one company, I convinced them to implement a 2% SPIV (like a SPIFF, but team-focused) for every team member who actively contributed to team improvement. SPIV payments were quarterly, and there was a running total so the team could see the fund growth. Initial indications of a positive impact are good.
    • Another benefit of collaboration is that it helps teams focus on approaches that work due to ongoing testing and refinement. Collaboration also helps teams focus on a more accurate ICP (ideal customer profile). Sales management can then feed their findings back to Marketing to improve and tailor their efforts.
  3. Selling is a byproduct of problem-solving. You can’t solve problems if you don’t know what they are. Every interaction with a prospect should focus on gathering information, building trust and relationships, and leveraging prior interactions to demonstrate that your solution will solve their problem and ease their pain.
  4. CRMs often either lack information or are full of wishful thinking. They focus on activities, and not progress and next steps. Using MEDDIC/MEDPICC as a foundation for reporting is a much better start. Sales managers need to independently validate the information to ensure their teams are being upfront and honest. Trust, coaching, and collaboration work together for the win.
  5. AI is not a panacea, but it is very effective for research, market validation, prospecting, and meeting preparation. Going in prepared builds respect and credibility, saves time, and lets you quickly qualify prospects in or out. There may be a nurturing program for some of the prospects qualified out for immediate deals, but your time is valuable, and you will go hungry chasing deals you can’t close.

So, what are your thoughts? Have you seen some of these problems yourself? How did you handle them? Let me know in the comments below.

And if you are looking for a Consultant to help your business grow or someone who can add immediate value to your team, then contact me.

Lessons Learned from Selling Kubernetes

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Cloud-native, containerization, microservices, and Kubernetes have become very popular over the past few years. They are as complex as they are powerful, and for a large, complex organization, these technologies can be a game changer. Kubernetes itself is a partial solution – the foundation for something extraordinary. It can take 20-25 additional products to handle all aspects of the computing environment (e.g., ingress, services mesh, storage, networking, security, observability, continuous delivery, policy management, and more).

Consider the case of a major Financial Services company, one of my clients. They operated with 200 Development teams, each comprising 5-10 members, who were frequently tasked with deploying new applications and application changes. Prior to embracing Kubernetes, their approach involved deploying massive monolithic applications, with changes occurring only 2-3 times per year. However, with the introduction of Kubernetes, they were able to transition to a daily deployment model, maintaining control and swiftly rolling back changes if necessary. This shift in their operations not only allowed them to innovate at a faster pace but also enabled them to respond to opportunities and address needs more promptly.

Most platforms utilize Ansible and Terraform for creating playbooks, configuration management, and other purposes. Those configurations could become very long and complex over time and were prone to errors. For more complicated configurations, such as multi-cloud and hybrid environments, the complexity is further amplified. “Configuration Drift,” or runtime configurations that differ from what was expected for various reasons, leads to problems such as increased costs due to resource misconfiguration, potential security issues resulting from incorrectly applied or missing policies, and issues with identity management.

The surprising thing was that when prospects identified those problems, they would look to new platforms that used the same tools to solve them. Sometimes, things would temporarily improve (after much time and expense for a migration), but then fall back into disarray as the underlying process issues still needed to be addressed.

Our platform used a new technology called Cluster API (or CAPI). It provided a central (declarative) configuration repository, making it quick and easy to create new clusters. More importantly, it would perform regular configuration checks and automatically reconcile incorrect or missing policies. It was an immutable and self-healing Kubernetes infrastructure. It simplified overall cluster management and standardized infrastructure implementation. 

All great stuff – who would not want that? This technology was new but proven, but it was different, which scared some people. These were a couple of recurring themes:

  1. The Platform and DevOps teams had a backlog of work due to existing problems, so there was more fear about falling further behind than confidence in a better alternative.
  2. Teams focused on their existing investment in a platform or on the sunk costs spent over a long period, attempting to solve their problems. The ROI on a new platform was often only 3-4 months, but that was challenging to believe, given their own experiences on an inferior platform.
  3. Teams would look at outsourcing the problem to a managed service provider. They could not explain how the problems would be specifically resolved, but did not seem concerned about that lack of clarity.
  4. There was a lack of consistency on the versions of Kubernetes used, the add-ons and their versions, and one-off changes that were never intended to become permanent. Reconciling those issues or migrating to new, clean clusters both involved time and effort. That became an excuse to maintain the status quo.
  5. Unplanned outages were common and usually expensive. Using the cost of those outages as justification for something new was typically a last resort, as people did not like acknowledging problems that put a spotlight on themselves.
  6. Architects had a curiosity about new and different things, but often lacked the gravitas within business leadership to effect change. They were usually unwilling or unable to explain how real changes happen within their company, or introduce you to the actual decision-makers and budget holders.

Focusing on outcomes and working with the Executives most affected by them tended to be the best path forward. Those companies and teams were rewarded with a platform that simplified fleet management, improved observability, and helped them avoid the risky, expensive problems that had plagued them in the past. And, working with satisfied customers who appreciated your efforts and became loyal partners made selling this platform that much more rewarding.

Six Ways AI Can Become a Sales Management Enhancer

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As a VP of Sales, I would spend the first 60-90 minutes of every day reviewing a dozen different news sources, looking for information about new technology, competitor announcements, proposed legislation, and M&A news. I looked for anything relevant in critical industries, news about our customers or their top customers, and staffing changes within their companies.

My goal was to identify anything that could negatively impact deals in play, threaten the customer base, disrupt the run rate business, as well as seize opportunities to break into a new company or displace a competitor. You feed your findings and speculations back to your team, along with suggestions, talking points, or specific directions to help them maintain or increase their success for the current quarter plus the next few quarters.

You look for trends and leading indicators that could help your team and your organization achieve greater success. Winning feels good, and the rewards make you want to achieve even more.

Artificial Intelligence (AI) will be able to do all this and more. It will be more consistent, analyze information without bias, and do so on a more timely basis.

1. Automated Intelligence Gathering

Focus your efforts where they add the most value. AI can automate the collection and analysis of data from multiple sources, including news feeds, legal updates, social media, and competitor websites. This automation can save considerable time and minimize the chances of missing relevant information. Natural Language Processing (NLP) can identify, categorize, and correlate relevant information, providing actionable insights without the need for manual review.

2. Enhanced Lead and Opportunity Identification

In addition to the correlations above, Machine Learning (ML) models can analyze trends and patterns in data to identify potential leads or opportunities for expansion. By understanding market movements, customer behaviors, historical behavior, and presumptive competitor strategies, AI can suggest new targets for sales efforts and highlight areas where teams could gain a competitive edge.

3. Improved Internal Communication and Collaboration

Sales is not just about selling but also about collaborating internally to create the best possible products and services to sell and identify the best approaches to generate awareness and interest in your offerings.

AI systems can serve as a central hub for information that benefits various departments within a company. By integrating with CRM, marketing, support, and other internal systems, AI can distribute tailored information to different teams, ensuring that everyone has the best insights to perform their roles effectively and promoting a more cohesive and coordinated approach to achieving long-term business objectives.

4. Forecasting and Predictive Analytics

With the ability to process vast amounts of data, AI should significantly improve forecasting accuracy. Predictive analytics can estimate future sales trends, customer demands, and market dynamics, providing businesses with more opportunities to make better-informed decisions—better resource allocation, optimized sales strategies, and, ultimately, higher revenue will be the result.

5. Increased Efficiency and ROI

By automating routine tasks and providing deep insights, AI can free up sales and management teams to focus on strategic activities. The efficiency gains from AI can result in significant cost savings and a higher return on investment (ROI) as teams do more with less, capitalize on opportunities faster and more effectively, and ultimately make more money for themselves and their company.

6. Continuous Learning and Improvement

Machine learning models will improve over time as they process more data, meaning the insights and recommendations provided by AI will become increasingly accurate and valuable, helping businesses continuously refine their strategies and operations for better outcomes.

Future Perspectives

While it’s true that AI may not yet be ready to take over complex roles like enterprise sales, its potential to enhance these roles is undeniable. As AI technology continues to evolve, its ability to provide highly accurate forecasts, improve win rates, shorten sales cycles, and enhance competitiveness will only grow. The future of AI in sales and business management is not just about automation but about augmenting human capabilities to create more effective, efficient, and thriving organizations that are better able to compete in an increasingly competitive global landscape.

So, what do you think? Will this work? Will it be good enough if everyone is doing it? Leave a comment and let us know.

Using Themes for Enhanced Problem Solving

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Thematic Analysis is a powerful qualitative approach used by many consultants. It involves identifying patterns and themes to better understand how and why something happened, which provides the context for other quantitative analyses. It can also be utilized when developing strategies and tactics due to its “cause and effect” nature.

Typical analysis tends to be event-based. Something happened that was unexpected. Some type of triggering or compelling event is sought to either stop something from happening or to make something happen. With enough of the right data, you may be able to identify patterns, which can help predict what will happen next based on past events. This data-based understanding may be simplistic or incomplete, but often it is sufficient.

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But people are creatures of habit. If you can identify and understand those habits and place them within the context of a specific environment that includes interactions with others, you may be able to identify patterns within the patterns. Those themes can be much better indicators of what may or may not happen than the data itself. They become better predictors of things to come and can help identify more effective strategies and tactics to achieve your goals.

This approach requires that a person view an event (desired or historical) from various perspectives to help understand:

  1. Things that are accidental but predictable because of human nature.
  2. Things that are predictable based on other events and interactions.
  3. Things that are the logical consequence of a series of events and outcomes.

Aside from the practical implications of this approach, I find it fascinating relative to AI and Predictive Analysis.

For example, you can monitor data and activities proactively by understanding the recurring themes and triggers. That is actionable intelligence that can be automated and incorporated into a larger system. Machine Learning and Deep Learning can analyze tremendous volumes of data from various sources in real-time.

Combine that with Semantic Analysis, which is challenging due to the complexity of taxonomies and ontologies. Now, that system more accurately understands what is happening to make accurate predictions. Add in spatial and temporal data such as IoT, metadata from photographs, etc., and you should be able to view something as though you were very high up – providing the ability to “see” what is on the path ahead. It is obviously not that simple, but it is exciting.

From a practical perspective, keeping these thoughts in mind will help you see details others have missed. That makes for better analysis, better strategies, and better execution.

Who wouldn’t want that?