Project Management
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!
Good Article on Why AI Projects Fail
Today I ran across this very good article as it focused on lessons learned, which potentially helps everyone interested in these topics. It contained a good mix of problems at a non-technical level.
Below is the link to the article and commentary on the Top 3 items listed from my perspective.
https://www.cio.com/article/3429177/6-reasons-why-ai-projects-fail.html
Item #1:
The article discusses how the “problem” being evaluated was misstated using technical terms. At least some of these efforts are conducted “in a vacuum.” Given the cost and strategic importance of getting these early-adopter AI projects right, that was a surprise.
In Sales and Marketing, you start the question, “What problem are we trying to solve?” and evolve that to, “How would customers or prospects describe this problem in their own words?” Without that understanding, you can neither initially vet the solution nor quickly qualify the need for your solution when speaking with those customers or prospects. That leaves room for error when transitioning from strategy to execution.
Increased collaboration with Business would likely have helped. This was touched on at the end of the article under “Cultural challenges,” but the importance seemed to be downplayed. Lessons learned are valuable – especially when you are able to learn from the mistakes of others. This should have been called out early as a major lesson learned.
Item #2:
This second area had to do with the perspective of the data, whether that was the angle of the subject in photographs (overhead from a drone vs horizontal from the shoreline) or the type of customer data evaluated (such as from a single source) used to train the ML algorithm.
That was interesting because assumptions may have played a part in overlooking other aspects of the problem, or the teams may have been overly confident about obtaining the correct results using the data available. In the examples cited, those teams figured out those problems and took corrective action. A follow-up article describing the process used to determine the root cause in each case would be very interesting.
As an aside, from my perspective, this is why Explainable AI is so important. Sometimes, you just don’t know what you don’t know (the unknown unknowns). Understanding why and on what the AI is basing its decisions should help with providing better quality curated data up-front, as well as identifying potential drifts in the wrong direction while it is still early enough to make corrections without impacting deadlines or deliverables.
Item #3:
This didn’t surprise me but should be a cause for concern as advances are made at faster rates, and potentially less validation is made as organizations race to be first to market with some AI-based competitive advantage. The last paragraph under ‘Training data bias’ stated that based on a PWC survey, “only 25 percent of respondents said they would prioritize the ethical implications of an AI solution before implementing it.”
Bonus Item:
The discussion about the value of unstructured data was very interesting, especially when you consider:
- The potential for NLU (natural language understanding) products in conjunction with ML and AI.
- This is a great NLU-pipeline diagram from North Side Inc. in Canada, one of the pioneers in this space.
- The importance of semantic data analysis relative to any ML effort.
- The incredible value that products like MarkLogic’s database or Franz’s AllegroGraph provide over standard Analytics Database products.
- I personally believe that the biggest exception to this assertion will be from GPU databases (like OmniSci) that easily handle streaming data, can accomplish extreme computational feats well beyond those of traditional CPU-based products, and have geospatial capabilities that provide an additional dimension of insight to the problem being solved.
Update: This is a link to a related article that discusses trends in areas of implementation, important considerations, and the potential ROI of AI projects: https://www.fastcompany.com/90387050/reduce-the-hype-and-find-a-plan-how-to-adopt-an-ai-strategy
This is definitely an exciting space that will experience significant growth over the next 3-5 years. The more information, experiences, and lessons learned are shared, the better it will be for everyone.
Failing Productively
As an entrepreneur, you will typically get advice like, “Fail fast and fail often.” I always found this somewhat amusing, similar to the saying, “It takes money to make money” (a lot of bad investments are made using that philosophy). Living this yourself is an amazing experience – especially when things turn out well. But as I have written about before, you learn as much from the good experiences as you do from the bad ones.
Innovating is tough. You need people who always think of different and better ways of doing things or question why something has to be done or made a certain way. It means shifting away from the “how” and “why” and focusing on the “what” (outcomes). It takes confidence to ask questions that many would view as stupid (“Why would you do that, it’s always been done this way.”) But, when you have the right mix of people and culture, amazing things can and do happen, and it feels great.
Innovating also takes a willingness to lose time and money, hoping to win something big enough later to make it all worthwhile. This is where many companies fall short because they lack the patience, budget, or appetite to fail. I personally believe that this is the reason why innovation often flows from small companies and small teams. For them, the prospect of doing something cool or making a big impact is motivation enough to try something, and the barriers to getting started are often much lower.
It takes a lot of discipline to follow a plan when a project appears to be failing, but it takes even more discipline to kill a project that has demonstrated real potential but isn’t meeting expectations. That was one of my first and probably most important lessons learned in this area. Let me explain…
In 2000 we looked at franchising our “Consulting System” – processes, procedures, tools, metrics, etc., developed and proven in my business. We believed this approach could help average consultants deliver above-average work products in less time. The idea seemed to have real potential.
Finding an attorney who would even consider this idea took a lot of work. Most believed it would be impossible to proceduralize a somewhat ambiguous task like solving a business or technical problem. We finally found an attorney who, after a 2-hour no-cost interview, agreed to work with us. When asked about his approach, he replied, “I did not want to waste my [his] time or our money on a fool’s errand.”
We estimated it would take 12 months and cost approximately $100,000 to fully develop our consulting system. We met with potential prospects to validate the idea (it would have been illegal to pre-sell the system) and then got to work. Twelve months turned into 18, and the original $100K budget increased nearly 50%. All indications were positive, and we felt very good about the success and business potential of this effort.
Then, the terror attacks occurred on Sept. 11th and businesses everywhere saw a decline. In early 2002 we reevaluated the project and felt that it could be completed within the next 6-8 months and would cost another $50K+.
After a long and emotional debate, we decided to kill the project – not because we felt it would not work, but because there was less of a target market, and now the payback period (time to value) would double or triple. This was one of the most difficult business decisions that I ever made.
A big lesson learned from this experience was that our approach needed to be more analytical.
- From that point forward, we created a budget for “time off” (we bought our own time, as opposed to waiting for bench time) and other project-related items.
- We developed a simple system for collecting and tracking ideas and feedback. When an idea felt right, we would take the next steps and create a plan with a defined budget, milestones, and timeline. If the project failed to meet any defined objectives, it would be killed – No questions asked.
- We documented what we did, why we decided to do it, our goals, and expected outcomes and timelines. Regardless of success or failure, we would conduct postmortem reviews to learn and document as much as possible from every effort and investment.
We still had failures, but with each one, we took less time and spent less money. More importantly, we learned how to do this better, which helped us realize several successes. It provided both the structure and the freedom to create some amazing things. Since failing was an acceptable outcome, it was never feared.
This approach was more than just “failing fast and failing often”; it was “intelligent failure,” which served us well for nearly a decade.
Profitability through Operational Efficiency
In my last post, I discussed the importance of proper pricing for profitability and success. As most people know, you increase profitability by increasing revenue and/or decreasing costs. However, cost reduction does not necessarily mean slashing headcount, wages, benefits, or other factors that often negatively affect morale and cascade negatively on quality and customer satisfaction. There is often a better way.
The best businesses generally focus on repeatability and reliability, realizing that the more you do something – the better you should get at doing it well. You develop a compelling selling story based on past successes, develop a solid reference base, and have identified the sweet spot from a pricing perspective. People keep buying what you are selling, and if your pricing is right, money is available at the end of the month to fund organic growth and operational efficiency efforts.
Finding ways to increase operational efficiency is the ideal way to reduce costs, but it takes time and effort. Sometimes this is realized through increases in experience and skill. But, often optimization occurs through standardization and automation. Developing a system that works well, consistently applying it, measuring and analyzing the results, and then making changes to improve the process. An added benefit is that this approach increases quality, making your offering even more attractive.
Metrics should be collected at a “work package” level or lower (e.g., task level), which means they are related tasks at the lowest level that produce a discrete deliverable. This project management concept works whether you are manufacturing something (although a Bill of Materials may be a better analogy in this segment), building something, or creating something. This allows you to accurately create and validate cost and time estimates. When analyzing work at this level of detail, it becomes easier to identify ways to simplify or automate the process.
When I had my company, we leveraged this approach to win more business with competitive fixed-price project bids that provided healthy profit margins for us while minimizing risk for our clients. Bigger profit margins allowed us to invest in our own growth and success by funding ongoing employee training and education, innovation efforts, and international expansion, as well as experimenting with new things (products, technology, methodology, etc.) that were fun and often taught us something valuable.
Those growth activities were only possible because we focused on doing everything as efficiently and effectively as possible, learning from everything we did – good and bad, and having a tangible way to measure and prove that we were constantly improving.
Think like a CEO, act like a COO, and measure like a CFO. Do this and make a real difference in your own business!
Connecting the Dots Faster
When I started consulting, an experienced consultant told me, “The best Consultants are experts at becoming Experts.” I started my consulting career with that goal in mind. After a few years realized that “Good consults are people who can learn enough quickly to ask intelligent questions and then connect the dots faster.” This is a great skill for anyone, regardless of the industry or business.
It’s impossible to be an expert at everything. I believe having great depth in a few areas (true expertise) and breadth of knowledge in many areas (enhancing context and insight) is important. Both types of knowledge alone are valuable, but combined, they add a dimension that allows a person to be far more effective and potentially much more valuable because it leads to the ability to pick up on the dependencies and nuances that others miss.
Just think – How much more effective is a salesperson who understands technology and project management concepts when working to demonstrate fit and create a sense of urgency? Or, an Attorney who understands the complexity of service offerings and delivery – enhancing their ability to construct agreements that are highly protective yet not overly complex or onerous. Or a programmer who thinks beyond the requirements and looks for ways to improve or simplify the process. Extra knowledge helps with the big picture understanding, and that often leads to providing more value by “thinking outside the box.” Additional knowledge and skills almost always help us become more effective, regardless of what we may be doing.
Increased knowledge and a desire to do amazing things create opportunities to make a huge and immediate impact. Sometimes it is because you are asking the questions that others may be thinking but simply cannot articulate in a clear manner. It helps you see the gaps and holes that others miss. And most importantly, it helps you “connect the dots” before others do (often many months before something obvious to you becomes obvious to others). A large consultancy once used the phrase “seeing around corners” to make this concept tangible.
So, if you buy into the concept that knowledge is good, the next question is usually, “What is the best way to learn?” People learn in different ways, so there really is no one single best way to learn. Understanding how you learn best will help you learn faster.
I’m a fan of reading. A good book may reinforce ideas you already know, introduce you to a few concepts or ideas that seem like they could help (giving you something to test), and often present many ideas that you know or feel just won’t work. Just don’t become one of those people who changes their beliefs and approach with every book they read (or what I refer to as “The book of the month club manager.“)
I’m also a fan of hands-on learning. The experience of doing something the first time is important. Keeping detailed notes (what works, what doesn’t make sense, what you did to figure it out, workarounds, etc.) enhances the value of that experience. It’s amazing what you can learn when you “get your hands dirty.”
What about formal education? I’ve never been a fan of the person who wants to get a degree in order to get a promotion. There are certainly some professions where education is critical to success (often through legitimacy as much as anything else). My advice to people is to work towards a specific degree because it is important as a personal goal and because it could possibly help you get a different or better job in the future. I will never criticize anyone for learning, going to school, or getting another certification or degree.
I believe the best way to get ahead is to learn the position, innovate, optimize, and deliver incredible results. You won’t “knock it out of the park” every time, but those “base hits” will help you score and ultimately win.
This is not to say that formal education is bad; I don’t believe that at all. I was working on my MBA at the same time I was expanding my consulting business from the US to the UK. I had a concentration in International Business, so I could apply many things I was learning right away. This bit of serendipity both enhanced my learning experience and helped me make better decisions that had real implications for my business. The funny thing was that I was working on that degree to raise the bar for my children, so this was just a bonus for me.
There are also other great ways to learn – ways that only require an investment of your time. There are many good free online courses. If you are interested in learning something or need to know more about it, there is almost always a place to find free or low-cost training. These are great investments in yourself and your future, and may help you learn to connect those dots faster.
Below are links to a few good free learning websites. Do yourself a favor and check them out. And, if you know of others, leave a comment and recommend them to others. Enjoy!
OpenCulture (directory with content from multiple sources)
Open Education Database (directory with content from multiple sources
Where Ideas, Experiences, and Lessons Learned Intersect 