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Lessons Learned from Selling Kubernetes
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:
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
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.
Finding the Right Fit in Sales
I won’t sell a product or service if I don’t believe in it or in the company behind it. But that is only part of the picture. Not all products or services fit everybody, but most are a fit for somebody. Whether you are a seller or leading a sales team, understanding the best-fit use cases helps you create a repeatable sales motion that allows you to:
- Find and prospect the best candidate companies.
- Demonstrate benefits for a credible and relevant use case.
- Find a sponsor who benefits from your offering.
- Accelerate the deal velocity – even in a large enterprise business.
- Close large deals faster – and more of them!
When I started at my last company, I was told that the typical deal size was $75K-$80K, having a 9-12 month sales cycle with a midsize company. I was selling a Kubernetes Fleet Management platform, and I quickly found that most midsize companies lacked the containerization needs that Kubernetes provides. Most also needed to gain the skills required for fairly complex solutions, which can take months.
Large Enterprise companies had the need and the expertise to support Kubernetes, which started my profile development exercise. Large companies with a corporate standard containerization product were less likely candidates with a much longer sales cycle. Financial Services companies require strong end-to-end security and cannot afford breaches (reputationally and actual costs). Therefore, they had larger budgets and immediate needs, so they became a primary focus.
While looking at the environments for these companies, it became clear that an initial deal size could easily be in the $500K – $1 million range. And, if you successfully delivered what you promised, there could be several more significant follow-on deals. The icing on the cake is that by selling those companies what they need, solving significant problems or concerns, and treating them like the valued customers they are, they would reward you with loyalty and long-term business.
Finding the right fit for your product or service takes analysis, investigation, testing, and time. Getting this right provides the perfect opportunity to be successful and scale the results through the entire team. It also provides credibility when new customers are willing to speak with prospects and sing your praises. Success breeds success.
Knowing When to Stop
What’s the hardest decision you’ve ever had to make? Why?
Jetpack Question of the Day
In 2000 we started developing a Franchising System for Business Consulting. We had invested over $100K and were making progress, but we were about 6 months behind schedule when 9/11 occurred.
Everything came to a standstill for a few months. In early 2002 we reevaluated the situation. We were about $50K and less than 6 months from completion. But the total addressable market had shrunk considerably, and there was no telling if or when it might recover.
We had to decide whether to invest more and potentially lose more or kill the project and cut our losses. The decision was difficult. We ultimately decided to cut our losses and walk away from our investment in time and money. It was probably the right decision, but it was still very difficult.
For anyone interested, this post goes into more detail on this topic.
The Million Dollar Deal How-To
Eight years ago, one of my peers asked me to produce a two-hour sales training session for the combined global sales team. He suggested a session named “The Million Dollar Deal How-To,” which would show people how to go about finding and closing large deals. It was a good idea, so I went ahead and did it.
The presentation started with a list of my Top 20 deals to date and a brief description of each deal, the biggest of which had an $8.5M+ ARR and a 7-year total value of over $60M. I included an additional negotiation for a deal closed by another VP shortly before he left the company. It was a complex deal with a very large System Integrator worth $1M-$2M/year over five years.
The underlying assumption is that the seller performed proper qualification before this step. While this would be considered a “given” by many, I have seen far too many sellers focus on deals that would never happen. To be successful, you need to spend your limited time on the opportunities that you are most likely to win. The better your upfront qualification and ongoing validation, the more likely you will succeed.
My goals with this section were:
- Demonstrate credibility.
- Demonstrate how the concepts apply to both products and services.
- Help the team see some commonalities between the deals.
- Explain how a lack of attention to negotiations or the contract can ruin a great deal.
Next, I presented a comprehensive list of the key topics, providing examples of each, followed by a very active Q&A session. The session was well-received and resulted in an increase in deal size and sales volume over the next year.
The contracting part showed examples of how a simple missing or additional word (e.g., “Discounts calculated based on the Annual Cumulative purchase volume, where the word “annual” was a mistake that reset the value that would have cost us over $5M in revenue over the life of that agreement) and similar mistakes. As an aside, I was negotiating a deal a year ago, and someone in our Operations team made a small mistake (adding a period to the annual increase language) for a multi-year deal that would have cost us over $40K on the first renewal. The point of this section was that you only assume the deal is complete once it is correct and complete.
Below are the Top 10 concepts from that training session that were common to all wins:
- Relationships Matter – People buy from people they like and trust. Moreover, they tend to like and trust people with integrity who have the customer’s best interest at heart. Create Customers for Life.
- Just because you can sell something to someone doesn’t mean you should – especially if it is not a good fit or won’t bring them value.
- Understand the Needs and Quantify the Impact – Use their terms, phrasing, and figures to increase the relevance of their use case and seek their validation.
- Understand Their Constraints – Document the various assumptions to determine how real or rigid they may be.
- What Happens if They Do Nothing? – Ask questions like, “Why Now?” and “What is the impact of waiting a year or more?” The answers will help with qualification around genuine business needs.
- Understand their Timeline and Milestones – Working back from the targeted end date can create a sense of urgency and avoid unnecessary delays.
- This is where Project Management can help you close the deal.
- Be Creative – The key is to get the prospect to focus on the outcomes (the “Fundamental Objectives”) rather than the approach (the “Means Objectives”). Focusing on “what they need” versus “how it is done” can be more challenging. Consider other aspects of their business that could be impacted and proactively raise any potential concerns and your ideas to address them.
- Remember, you are trying to solve their problems and not hide things that will become apparent later.
- Don’t Discount Someone Based Solely on Title – Many mediocre salespeople dismiss everyone except the Economic Buyer. A better approach is to ask various stakeholders about their roles in the purchase process and how they make decisions.
- Alienating people you will need to develop a long-term relationship with doesn’t make sense.
- Learn about the Alternatives and the Competition – How does our offering fare against the others? Why would they choose us over the competition?
- It pays to be brutally honest when you are doing this.
- Dream Big – You only know if you ask, and if it was too easy for the prospect to say ‘Yes,’ then you left money on the table.
- It doesn’t mean you must extract every penny from the deal. Instead, consider what else you could have included to make things easier for the customer, accelerate the project, increase the probability of success, etc.
- Create a Shared Vision of Success – Help people “see and feel” what success is like. That can be very compelling, especially if challengers come forward later in the process or some other issues arise.
- The worst thing you can do is sell something that does not solve their problem. You make your Economic Buyer and Champions look bad, which helps ensure you will not do more business there anytime soon.
While there are still several other components of the overall approach, these provide the foundation. Selling is not easy, but it is rewarding to help your customers prosper and grow, and financially beneficial to exceed your quota by selling large deals. Good Hunting!
Where Ideas, Experiences, and Lessons Learned Intersect 