About Relevant Software
Here’s the short version
Proposals are bets on the future with many uncertainties. The US Government’s competitive proposal process doesn’t make it easy for businesses, and enormous resources are spent to try to win that (sometimes) lucrative Government contract. Winning one out of three is a very good record; one out of five or six is more common. The odds are not good, but it’s the only way to play. So if the rules are set, maybe we can make the rules work more in our favor? The concept and design of Relevant Match is the convergence of Lean Six Sigma, data analytics, and 20 years of experience working in Government contracting (GovCon). All of business is managing uncertainty. But if we have to live with uncertainty, maybe we can be more efficient and consistent. That’s the motivation behind Relevant Match software.
About Relevant Software
Why focus on software for Proposals?
My career as a Technology Program Manager began as a US Army Captain, graduating in 1990 from the Defense Acquisition University PM Course. That was a 6 month course learning the Project Management Institute (PMI®) approach to project management, as implemented by Department of Defense. The process was (and continues) to be methodical and specific and in general, it worked. Despite the inefficiencies and challenges always found in very large organizations, common language plus flexible discipline tends to get the job done.
Ten years later on retiring from the Army as a Lieutenant Colonel, that experience did not fully prepare me for life on the other side of the military-industry enterprise – working in corporate America doing business with the Federal Government. I found that management here could be divided into three primary efforts:
- winning a contract
- fulfilling that contract
- pursuing the next contract
Repeat – forever. I spent 15 more years leading teams, fulfilling contracts, and working in multiple corporate roles. I’m happy to count more than 150 technology projects and a quarter Billion dollars to my personal management efforts.
And yet, over those many business relationships, I found that few business development efforts — and specifically proposal management – had very little of the discipline of project management that I had learned and practiced. Across many teaming agreements, prime and sub contracts, pursuits, wins and losses, I found that most decision making came down to how the Executive-in-Charge felt about the Pwin, the win themes, and the proposal itself. And I also found that some proposal managers would double down on inefficient or unsuccessful techniques, because there’s no time to retool the proposal team, or it’s worked sometime in the past on some big win (but not lately), or the VP won’t buy it, or it was price, not our proposal, or some other excuse. Later as a consultant, occasionally I heard the VP say something like “we’ve got to educate the Government on what they really need” – not infrequently a company proprietary solution. That was usually not a winning proposal.
I went to ShipleyWins! training. I think Shipley has done a great service to the GovCon industry by developing their proprietary process which they have sold to the community for decades – my last formal exposure there was on the order of 130 steps in the Shipley process. That’s a big and long-term commitment for most companies. Often bits of Shipley process were incorporated with mostly gut judgment by the Executives.
That’s not wrong, but can it be better?
Now I’m a quantitative person. I believe in data-driven decision making. While my advanced degree is Management not Computer Science, I hit my career stride at the same time of the Internet Revolution in the early 2000. Amazing technology advances happened in that decade (and continue). I worked on projects with DARPA and the US Intelligence Agencies – underlying their challenges was always this problem: having too much information, and not enough resources to analyze and make it actionable.
Enter Algorithms and Artificial Intelligence. For a quick review – algorithms are patterns, and this method of analysis has been around a very long time. It is essentially the approach of transferring human knowledge and logic to software. AI is similar but reverses the direction. It tries to enable software to mimic human logic, so it can discover its own knowledge and present it to humans. Algorithms are very stable. AIT is unpredictable. Algorithms are all around us and take the form of “when this happens, make that happen.” AI is … well, it’s so new that we’re not sure yet.
I continued doing proposals – sometimes as a manager, sometimes a consultant. Managing proposals is a very difficult role. Across all businesses, writing proposals bring together the least pleasant tasks of running a business – straddling the line of hyperbolic marketing and truthfulness, assembling content from diverse inputs and writers (aka herding cats), meeting the Exec’s preferences while addressing the customer’s requirements. Few people trained for it. Very few enjoy it. Most put in their time and try to pass the proposal baton to the next in line.
Intelligence, but not artificial
Nagging me was the question: instead of gut-feel, why not use an algorithmic approach to proposal management, and take out a lot of the uncertainty. I felt compelled to figure out how to distill a proposal to a mathematical formula. 2018 I solved it by using a technique related to what’s called the least squares regression. Good, but now how do we put this into action? That’s what Relevant Match software does!
A year later In 2019, I launched Relevant Software Corporation, and built a team and processes around Relevant Match, our first and flagship software. With it, our goal is to provide a tool that dramatically cuts down on the deliberation, hesitation, rework – and yes, the gut-feel judgments – of writing competitive proposals. Relevant Match will raise the quality of proposals for every company, because using data-driven proposal analysis supports well-written proposals that respond to the customer’s real intentions, which are sometimes subtle, sometimes cryptic, but always present, in their written work statements.
Relevant Match will show you what the work statement is really asking for, and help your proposal be responsive. And produce a winning proposal – easier, faster, better.
About the Founder – Mark E. Salesky
I started as a soldier, learning discipline and tactics. Always a student, I emerged as the teacher of technology, management, systems engineering, and leadership. I’m a published author, and an entrepreneur. I build value.
I’m the Leader and Strategist. I’m the one that gets the job done. I handle the good programs, the bad and the ugly programs – doesn’t matter – I focus on the deliverables and client satisfaction. I understand the big picture, and align every task to the program goals.
I’m the Architect, Builder, Advisor. I have skills and experience across many domains to bring revenue and profit for my company, and program success for my clients. I bring more than 30 years in the field, trained as a CIO, with certifications as Defense Acquisition Professional, Program Management Professional (PMP), and Six Sigma Black Belt, Agile, Cloud.
I’m the Expert, the Navigator. I have a personal track record of winning $125 million of new revenue, managing $293M portfolio, and leading 80+ proposals for various services and technologies. I manage P&L, contracts, proposals, establish program management offices, champion best practices, and oversee complex portfolios of R&D, development and deployment. I straighten twisted paths, and simplify complexity at the intersection of tech and people.
I’m the Mentor and Champion. I don’t do it alone. I lead teams of 3 to 103, and I respect the value that each person contributes. I don’t know their job as well as they do, but they can depend on me to know my job exceptionally well. With humility and courtesy, I speak the truth to them, to my client and to my boss.
I am the Program Management Professional, dedicated to competence and accomplishment, and tempered by also being a father, husband, brother, and friend to many.
And I am far from done…
