AI
Leading Next-Generation Sales Teams: The Mandate for Predictable Revenue
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
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.
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:
- GTM plans are often developed at the highest levels, often in isolation, without market testing and validation.
- Sales teams are pitted against one another, rather than working together to help everyone achieve more (i.e., “A rising tide lifts all boats.”)
- Sales teams are focused on selling features rather than solving business problems.
- CRMs are not consistently used and often reflect idealized fiction rather than reality.
- Sales management and teams are not leveraging AI to help focus their efforts.
Here are the related Lessons Learned:
- 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.
- 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.
- 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.
- 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.
- 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.
Biometric Identity Theft
Recently, I have been researching the potential for fraud and identity theft using fingerprints from photos posted on social media. Last week Amazon released its “Amazon One” Palm Scanner to pay for purchases when shopping. That announcement made me wonder, what are the potential implications for fraud and identity theft using biometric data taken from images?
Technology continues to improve rapidly, which often means, “Where there is the will, there’s a way.”
There are a surprising number of ways to accurately identify someone from a photo or video. Moreover, there is technology to copy fingerprints from social media photos taken up to three meters away. New technology has been proven effective at using 3D printing technology to create “fake fingerprints” that bypass many fingerprint scanners.
Since fingerprints can be copied from photos taken up to three meters away, can a palm print be copied from a photo taken 5-10 meters away? That question led to an interesting but unscientific experiment where I took pictures of my hand, enlarged them, measured the distance between the ridges and furrows of my fingers and my palm, and compared the results. Spoiler – probably not (yet) – but likely not far away given the rapid advancement of AI.
There are several areas where that distance was similar for both my fingers and palm. But, there were also areas on my palm where the average distance between “landmarks” was 3-5+ times greater. It turns out that a palm image is often segmented into 3-4 distinct regions for identification purposes, likely due to this type of variation. This link was helpful in understanding the process.
This research led to an idea for a chip-based embedded filter for smart devices and laptops. It would obfuscate key biometric information when extracting the data for display without affecting the integrity of the original stored image. This functionality would automatically provide an additional layer of privacy and data protection. It would require optimized object detection capabilities (possibly R-CNN) that were highly efficient and run on a capable but low-energy processor like the Arm Cortex-M. Retraining and upgrades would be accomplished with firmware updates.
Edit 2020-10-13: This article on “Tiny ML” from Medium.com is the perfect tie-in to the abovementioned idea.
While Amazon’s technology is much newer and presumably at least partially based on their 2019 Patent Application (which does look impressive), it makes you wonder how susceptible these devices might be to fraud given reports of the scans occurring “almost instantaneously.” Speed is one aspect of successful large-scale commercial adoption, but the accuracy and integrity of the system are far more important from my perspective.
Time will tell how robust and foolproof Amazon’s new technology really is. Given their reach, this could occur sooner rather than later. Ultimately, multiple forms of biometric scans (such as a full handprint with shape, palm, and fingerprints or a retina scan 2-3 minutes prior to the palm scan to maintain performance) may be required for enhanced security, especially with mobile devices.
Additional Resources:
- In-depth NIH document that is helpful in understanding the process and issues.
- A Simplified Guide to Fingerprint Analysis
- This is a 2012 Fingerprint and Palmprint Recognition Approach Report from the European Journal of Scientific Research that has many images and very good explanations.
- “A Textural Approach to Palmprint Identification“
The Coming Changes to Manufacturing
Recently, I spoke with a person on a team analyzing ways to “mitigate the risk of exclusive manufacturing in China” while not fully divesting their business interests in a growing and potentially lucrative market. This bifurcation exercise got me thinking about how many other companies are evaluating their supply chain relationships, inventory management, and the predictability of their cost of goods sold.
In the mid-1990s I had done a lot of work with the MK manufacturing software that ran on the Ingres database. Some of the issues were performance-related and fixed by database tuning, some were fixed by using average costs instead of a full Bill of Materials (BOM) explosion using dozens of screws in a window, but some were more interesting and also more business-focused.
After NAFTA became law, one manufacturer built a facility in Mexico and started manufacturing a few basic but important parts. When I arrived as a Consultant the main problem they faced was a reject rate of roughly 20% and additional related QA costs. My suggestion was to treat this part (a single piece of steel like the rotor from a disk brake system) as a component and build in the cost of both the scrap and the QA. They could then benchmark the costs against other suppliers in an apples-to-apples comparison to determine if they saved money. That approach ended up working well for them.
While that approach helped manage costs, it did not address the timeliness of orders or lead time required – important aspects of Just-in-Time (JIT) manufacturing. Additionally, it should be possible to estimate shipping costs by considering changes in petroleum costs or anticipated changes in demand or capacity.
There are systems out there that claim to estimate the cost and availability of commodities based on various global factors and leading indicators. It is tricky, to say the least, and we can’t anticipate an event like a pandemic. But, companies that are able to manage their inventory and production risk the best will likely be the ones that succeed in the long run. They will become the most reliable suppliers and have increased profits to invest in the further growth and improvement of their businesses.
The next 2-3 years will be very interesting due to technological advances (especially AI) and geopolitical changes. Those companies that embrace change and focus on real transformation will likely emerge as the new leaders in their segments by 2025.
New Perspectives on Business Ecosystems
One of the many changes resulting from the COVID-19 pandemic has been a sea change in thoughts and goals around Supply Chain Management (SCM). Existing SCM systems were up-ended in mere months as it has become challenging to procure raw materials to components, manufacturing has shifted to meet new unanticipated needs, and logistics challenges have arisen from health-related staffing issues, safe working distances, and limited shipping options and availability. In short, things are a mess!
Foundational business changes will require modern approaches to Change Management. Change is not easy – especially at scale, so having ongoing support from the top down and providing incentives to motivate the right behaviors, actions, and outcomes will be especially critical to the success of those initiatives. And remember, “What gets measured gets managed,” so focusing on the aspects of business and change that matter will become a greater focus.
Business Intelligence systems will be especially important for Descriptive Analysis. Machine Learning will likely play a larger role as organizations seek a more comprehensive understanding of patterns and work toward accurate Predictive Analysis. And, of course, Artificial Intelligence / Deep Learning / Neural Networks should accelerate as the need for Prescriptive Analysis grows. Technology will provide many of the insights needed for business leaders to make the best decisions in the shortest amount of time, which is both possible and prudent.
This is also the right time to consider upgrading to a collaborative, agile business ecosystem that can quickly and cost-effectively expand and adapt to whatever comes next. Click on this link to see more of the benefits of this type of model.
Whether you like it or not, change is coming. So, why not take a proactive posture to help ensure that this change is good and meets the objectives your company or organization needs.
Changes like this are all-encompassing, so it is helpful to begin with the mindset, “Win together, Lose together.” In general, it helps to have all areas of an organization moving in lockstep towards a common goal, but at a critical juncture like this, that is no longer an option.
Where Ideas, Experiences, and Lessons Learned Intersect 