Part 2: Vision - Where MGP Is Going
Continuing the Journey
In the first part of this short-series, I shared the background that led to where I am today - from my early experiences studying abroad during the Global Financial Crisis, through my MBA, to my 12+ years working in partnerships in the B2B data space. I outlined some common challenges I observed across markets and explained why I decided to start MGP. I recommend starting there to understand the foundation of what we're building if you haven’t read it yet.
Today, I want to focus on where we're headed - not just with MGP Trading Company, but how I see the macro evolving and the approach we're taking to address challenges that exist seemingly everywhere.
The Illusion of Overnight Change
One of the most impactful books I read in 2024 is Morgan Housel's "Same as Ever." Housel makes a compelling argument that while technology and circumstances change rapidly, human behavior and the fundamental patterns that drive business remain remarkably consistent over time.
We often view dramatic shifts as happening overnight - whether it's the rise of AI, blockchain technology, or any other technological revolution. In reality, meaningful transformation happens gradually, while building on legacy foundations rather than replacing them entirely. This perspective helped shape how I approach business challenges as well as opportunities.
My own journey to founding MGP didn't just happen overnight. It was ultimately through years of observing patterns across different markets, companies, and use-cases. Similarly, the problems I see that businesses facing today have pretty deep historical roots - they've just evolved and shifted with changes to technology and/or market conditions.
Today's B2B World: New Tools, Same Challenges
When I look at the current state of the B2B, I see companies struggling with the same fundamental challenges I outlined in Part 1:
The data-knowledge gap has widened as companies collect and create more data each day, but still struggle to derive useful insights and take action on them. The noise-to-signal ratio (not signal-to-noise) has increased exponentially, making it even harder to focus on what truly matters.
The "shiny-object syndrome" has gotten out of control with the seeming boom in AI, as companies chase the latest AI-apps without building strong foundations within their own processes, systems, or data management. It's similar to prior tech cycles, where companies rushed to adopt solutions before clearly defining the problems they needed to solve - or if the new tech was needed to solve such a problem.
The human elements of collaboration, trust, and shared vision remain the most critical as well as challenging aspects of success in business. No amount of technological advancement can overcome poor organizational architecture and alignment or ineffective teamwork and poor communication.
The default approach and bias towards "do-it-ourselves" or "do-nothing" persists, with companies grossly underestimating the costs of delayed action (opportunity cost to capture value) or poor execution (wasted time and money). This is especially clear when it comes to how companies approach emerging technologies, where the gap between the required specific knowledge and internal capabilities is often vast.
The shift towards more transactional relationships continues, even as the increased complexity of our collective business challenges demands deeper, more sustainable partnerships. The irony is that as problems become more complex, many companies are becoming more short-term focused in their approach to address them.
The MGP Approach: People, Data, Technology
So how do we want to address these challenges? Our approach is built around three core elements: People, Data, and Technology. This is not a novel framework, but unlike many orgs that treat these as three separate domains, we recognize they are interconnected at the foundational level.
People: The Foundation
Everything starts with people - full stop.
The right team with the right skills, experience, and mindset towards collaboration makes all the difference. That said, finding, developing, and retaining the right people is becoming harder as more people seek to work for value-aligned companies.
This is where one of our key philosophies becomes relevant: Building WITH Partners. As I outlined in a recent post, the traditional "build vs. partner" framework presents a false choice. The most effective approach is usually a hybrid model that combines internal capabilities with external experience and expertise.
This collaborative approach allows organizations to:
Access specialized skills that would be difficult to develop or maintain internally
Accelerate timelines by leveraging existing expertise
Create flexible paths to knowledge transfer and capability development
Scale resources up or down based on evolving needs
The key is moving beyond traditional outsourcing models toward true collaborative partnerships. This requires an acute attention to team integration, knowledge sharing, and governance structures that support long-term success.
Data: The Fuel
Data is actually the lifeblood of modern business, but its value is not within its quantity as many like to suggest, but instead in its applicability to specific business challenges. I've seen too many orgs struggle with a syndrome of being data rich and insight poor, where they collect perhaps enough 1st and 3rd party data, but have minimal intelligence to act on it, and then they blame the data.
The approach I've developed and refined through my time at NetProspex, Dun & Bradstreet, and LeadIQ focuses on connecting data to specific use-cases and outcomes. This means:
Starting with the business challenge or opportunity, not the data itself, and even asking “what am I trying to do or achieve?”
Identifying the minimum amount of data needed to address the specific challenge, whether 1st party, 3rd party, or both - usually the answer is a combination of the two
Building processes that transform raw data into contextual insights, which usually comes with experience in understanding what you want to derive from the data
Creating feedback loops that continuously improve data quality and relevancy - and many really miss this part even if they get the first three
This practical approach cuts through the BS, the noise, and all the current hype around big data & analytics, and especially AI, to focus on what truly matters: using data to make better business decisions.
Technology: The Enabler
Technology should serve business goals, not drive them. At the same time, I've continually seen companies implement technical solutions in search of problems to solve, rather than carefully selecting the relevant tech that address specific challenges.
Our approach treats technology as an enabler, not an end in itself. This means:
Evaluating technologies based on their ability to solve specific business problems, even if that means building out bespoke solutions that fit your business, not fitting SaaS to meet your needs
Prioritizing integration and interoperability over nice-to-have features - there are plenty of SaaS solutions out there, and not enough work together well
Building flexible architectures that can evolve with changing business needs - think of future proofing your business based on where you may want to go
This thinking applies whether we're looking at CRM systems, data platforms, AI applications, or any other tech. The value isn't in the tool itself, but in how effectively it supports people and companies in realizing their desired outcomes.
Looking Ahead: Practical Evolution
As I do my best to look into the future, I see an evolution that mirrors my own professional journey: one that is practical, grounded in experience, and focused on creating sustainable long-term value. Our growth won't be driven by chasing market trends or raising external capital, but by consistently delivering results for our clients and partners.
In the near term, our focus is on continuing to build our network of the right partners as well as developing more structured approaches to the common challenges we observe across industries. We're documenting methodologies, refining processes, and creating frameworks that make our collective expertise more accessible and applicable, especially to the small and medium-sized businesses in the United States.
More long-term, I envision MGP as a [trading] hub for connecting specialized knowledge with practical application by way of helping companies navigate complex challenges by bringing together the right people, data, and technology in ways that create actual value.
A Final Thought: The Value of Perspective
If there's one thing I've learned so far, it's the value of perspective. The ability to identify and act on patterns regardless of context - to recognize what changes and what remains the "Same as Ever," is perhaps the most valuable capability in the world today.
This is ultimately what we offer - not just general consulting services or generic technical solutions, but a perspective shaped by diverse experiences as well as a commitment to understanding the patterns that drive business success.