Q&A with Dr. Tim Naddy & Rob Brinson

[Tim Naddy, Founder/CEO]

Having started my career with PwC and Deloitte, I learned very quickly that Public Accounting, while certainly technical in nature, is less about regulation and policy and more about human emotion and how it influences decision making. Even with all the financial and operational data in front of you, there is still a larger influencer on the ultimate business decisions made and that is wrapped up in human behavior. Accounting is behavioral and the data that drives it behaves, too; sometimes it bends towards the will of the human and sometimes doesn’t. That’s the key. The underpinnings of this behavioral science are what interested me to step in the world of fraud examination where time and again the fraud rationale would trump rational decision-making. If the data can tell you what’s “right” and “wrong”, why would humans accept it in one case and choose to ignore it in others? The real issue is why humans are making the decisions they are making. My passion for the true data story and how it affects decision-making is what drove me into starting Baker Street Scientific (BakerSCI). We have created a proprietary solution that visually reveals the behaviors in the human decision-making process, which allow us to finally see how influencers catalyze other decisions so we can understand and communicate it clearly for better decision-making.

BakerSCI was founded in April 2014. In short, our mission is to save lives and catch bad guys. We do this by employing our proprietary science and technology within software and hardware tools to generate data applications, models and results that can stand alone AND significantly aid and augment current competitors’ solutions in data analysis, interpretation, manipulation, and prediction. BakerSCI exposes the vital associations, deep context and unknown unknowns that exist within the data so that the data can tell the story.

[Rob Brinson, Principal, Acting CTO]

I got my start in software development and commercialization at a young age. At age 15, I wrote my first application and sold it. While my code writing was amateurish at best, I was stronger in reading and architecture; however, I knew I needed additional training to be proficient in the technical development side of the business. My strength from the beginning though was in my ability to identify what human, and beyond human, processes could be successfully written into software and, more importantly, if and where that was a market for its commercialization. From 1984 to 1996, I worked in middle and upper management in various technology-consulting firms. Between 2004 and 2010, I founded two data analytics software companies, sold them, retired, got bored, duly came out of retirement to use my skillset to help the next generation of IP entrepreneurs find their way in a fast moving and complicated marketplace. Since 2010 when I organized a consortium of 8 successful “exited” entrepreneur founders who collectively commanded a vast network of technical, operational and legal resources, we have taken nearly 200 young tech companies, in nearly every industry, from startup to success. Beyond my work in startups and turnarounds, I also advise the Department of Defense and the intelligence community on best practices in the areas of advanced technology, operations, process flow, etc.

So how did my consortium meet Tim? Firstly, let me tell you that Tim is not your typical CPA. Yes, on paper he has the pedigree: he has the advanced degrees, a doctorate and, unbeknownst to me when I met him, he was a professor at a local university actively teaching (and consulting) on Forensic Accounting and Fraud Examination. In 2014, I was in need of a forensic CPA for a client, couldn’t find one in the network who didn’t already have a COI or was otherwise engaged in other client work, so I expressed my frustration to my wife who very quickly said that I knew one and that I he was closer than I thought. Turns out, Tim and I both share an affinity for local theater and he was starring as the obnoxious Kenicke in Grease. There was no way this guy was a forensic accountant. Intrigued, I invited him to meet for lunch at a local wing joint and not five sentences into asking him about doing some work for the consortium, he stopped me, said he Google’d me and asked if I was an inventor and did I have any patents. Answering yes, he pulled over a napkin and started drawing out his concept for, get this, mapping the data behavior of random humans engaged in various conversations and how a catalyst could be used to get them all talking about the same topic. Not wanting to be pitched in my own hometown, I almost drove him back to “my” purpose for them meeting, however, having substantial background in analytics and IP, I recognized immediately that he was on to something that looked novel and foundational to data analysis. In less than 24 hours, we were under an NDA.

[Tim Naddy, Founder/CEO]

Our target audience is made up of those who earnestly have a desire to better understand their data. For some, this is discovering tactical and/or strategic intelligence they did not know existed within their own data. For others, this may be looking for innovative ways to interact with their data to anticipate certain behaviors from, say, a target market. In our experience, we have found that when speaking with different audiences, they all tend to have some sort of issue with which they’ve been struggling for some time and are desperate to find a solution. We happen to be very good at seeing inside the data that our audiences have been pouring over without success for months, sometimes years, and revealing intelligence that helps them understand and make better decisions. Our solutions can help individuals, organizations, current and potential investors, partners and customers who have been collecting data for years finally identify the missing pieces so they may be better positioned to make critical decisions. Our goal is that they will ultimately recognize that BakerSCI helps them reap the benefits of better decision-making around data.

[Tim Naddy, Founder/CEO]

Education. Hands down, the first challenge for any startup – and even large companies – is properly educating WHY the market needs you. Even though we are well into the Internet Age where data is everywhere, the marketplace still does not yet understand that they truly need data analytics as part of their normal operations. It has not yet been accepted that data is the lifeblood of their organizations. Unfortunately, because this chasm of understanding exists, the tipping points happen on an individual basis whereby eventually some kind of event will eventually take place where the organization finds that they have all of this data, have no idea what to do with it, and now they are completely outside their internal depth to do anything about it. Most learn the hard way and until that big event happens, they are purely content with merely managing their data. It’s easy and it makes them feel like they are doing something with it. However, when something big does happen (and it will happen), say a competitor gets a leg up during a financial crisis, then the sobering moment will occur when that organization finally realizes they either engage and activate their data or they may perish in the fallout. Educating the masses on how to avoid the above is an enormous task, but our industry is learning and we are getting better day by day.

Adoption is the second challenge. Even if a company has subject matter experts in their fields, they need to recognize and acknowledge when they need outside assistance to understand their data from a macro point of view, so that they can decide how to do better from a micro point of view. A CEO’s job in a data analytics company is to move a potential client from the unwilling chair to the willing chair as it pertains to their acceptance that data analytics is as important to their operations as is hiring the right people. Will they get the right solution for their issue? There is no single silver bullet, but multiple silver bullets that can address a vital organizational issue. BakerSCI just happens to have multiple silver bullets to address many different data issues of import.

[Tim Naddy, Founder/CEO]

Frankly, anybody who engages in data analytics is a competitor, but we must break this question into Large and Small competitors.

Large. We have been very strategic in our approach towards large companies who have multi-million dollar advertising spends. Many of these companies believe they have everything it takes within their own end-to-end solutions to meet all of their customers’ needs, and sure, they do have solutions that work…fine. But, from a macro perspective, their solutions can most certainly be improved. BakerSCI’s solutions play nice with these industry stalwarts because we don’t have to compete with these entities. Through a white label approach, we can complement their offerings to see deep context within the data they’re already processing so they can transparently innovate their indwelt legacy systems and increase the value of their service deliverables to their end customers through a premium service.

Small. This industry is ever-increasing. Opportunities are everywhere for small companies who desire to exploit a particular niche, which is why there are many small data companies in this industry. However, they tend to stay within their niches because they do not have an offering such as ours. We have technology that is ubiquitous. We operate in all sectors and verticals because we deal in the currency that spans them all, which is data. To BakerSCI, data is data is data. The key is in the discovery of unknown unknowns, how those are interpreted, and finally, how they are incorporated into strategic decision making, no matter the industry.

[Rob Brinson, Principal, Acting CTO]

Larger companies’ solutions are not as they would like, so they are acquiring smaller more nimble companies and technologies to add cutting edge capabilities and substantially broaden the capabilities of their own solutions. Many large companies that have large marketing budgets advertise very capable solutions in AI or analytics, but realistically, they are actively acquiring others to be able to attempt to deliver what they promise, and thus how we can turn any competitor into a partner.

[Tim Naddy, Founder/CEO]

Context is everything. We find the Unknown Unknowns. What are they? There are known things inside data that are right in front of you that you accept because you see them. For example, you are new in town and driving down a building-lined city street and can see everything in the upcoming intersection. Then, there are known unknowns inside the data that you as a person acknowledge are there but you have yet to understand them. For example, as you approach the intersection, you know, but don’t really “know”, that there are cars approaching the intersection around a blind corner. Then, there are the unknown unknowns. For example, who would have expected that bird to swoop down from above resulting in you hitting the brakes and spilling your coffee. Had you only known that this street was known for its vibrant aviary activity, you may have been looking for them and had driven a little more carefully. You are now aware of the unknown unknowns, thus your behavior has changed and so has your decision making. Those birds, that street, your driving, in any other scenario may have been different, but in the CONTEXT of the data story and all the influencers in play, the unknown unknown becomes relevant and therefore vital to the scenario. Unknown unknowns provide deep context for better understanding. We find intelligence that is contextually relevant and therefore better informs the conversation.

There is data inside datasets that you don’t know is there, so you’ve never thought to ask and therefore it has never affected your decisions. Think about it: What piece of information, if you were to know it, would change everything? That’s what we do. We find the deep context of the Knowns and discover the Unknown Unknowns that better inform decision makers. What we’ve found time and time again is that we’re changing the way people are making big data decisions. The kicker is: they’ve had the data all along but never knew it was in there. We are adding a whole new introspection from inside their own data; and because of that we are tackling Big Data one byte at a time. After all, Big Data is the collection of Small Data and the saying goes, “dynamite comes in small packages”. Because Big Data spans essentially all industries, our solutions are transformational in all of them.

[Rob Brinson, Principal, Acting CTO]

There is an extreme level of context in data, and we’re finding far greater amounts in the data compared to our competitors. We show higher levels of intelligence, relevance, and context inside the data that others haven’t even touched. We have been in rooms with leaders from the Defense Department and big corporations telling us they’re never seen anyone who can discover what’s in the data the way BakerSCI can.

[Tim Naddy, Founder/CEO]

We are looking for $5M for BakerSCI. We are already in talks with parties interested in possible industry-specific spinouts that employ narrow exclusivity, who are interested in doing something inside data analytics within their areas of expertise, such as: large life insurance company, oil & gas companies, and healthcare advanced imagery clinics. In order to play in those spaces, we can’t just dip our toes, we need the capital to make an impactful entrance thus, in our preliminary discussions we have eyeballed each spinout to be approximately $2.5M to stand up. As such, we are looking for $5M for the parent company, but it is entirely possible to participate in the spinouts as well with an additional $2.5M.

BakerSCI’s ideal investor is multifaceted. We would like a smart money investor who appreciates what we have built over the last four years with the team that is in place. I’ve heard and read horror stories about investors who decidedly took an overbearing role in their investments and ended up destroying the creativity and innovation that made them desire investing in the first place. We want to work alongside someone who supports management’s goals, even if it seems a bit unorthodox, as long as milestones are achieved in a timely and financially responsible manner. We want investors who have experience and expertise (or at least have access to them), who can engage with us so we, as a collective team, can elevate the Company to the next level. Our culture does not engage in negativity. There is nothing wrong with professional skepticism and constructive criticism if communicated with the right spirit. Of added importance, many people on our team have made sacrifices to get this company where it is today. Our ideal investor will put the Company’s interests over above their own personal socioeconomic and/or political ideals. Lastly, but by far most importantly, our ideal investor is somebody we can trust.

[Rob Brinson, Principal, Acting CTO]

We are looking for smart money.

[Tim Naddy, Founder/CEO]

We want to save lives and catch bad guys. We’re very good at doing this and we want to help others do it as well. We are doing this by aiding decision makers in the medical community in early cancer detection, working with local and national security elements to help people feel safer, and assisting domestic and foreign intelligence gathering to root out nefarious characters who only seek to destroy rather than unite. This is why we do what we do.

[Tim Naddy, Founder/CEO]

Right now, we are in the final stages of courting significant contract opportunities that may come to fruition over the coming quarters. These, of course, would be great for topline revenue generation and would also certainly aid in increasing our valuation. There’re no shortage of opportunities for what we are offering. Our desire is to use our Series A funds to scale our software development, IP development and protection, internal human infrastructure, BD efforts, etc. so we can bolster client activity as well as increase our level of engagement on our expanding IP road map, both of which will allow BakerSCI to offer more on a broader spectrum.

In terms of management, I see this position with a lot of clarity. I’ve been in a lot of organizations where founders get attached to the CEO position and then come to find that their shortcomings lead to organizational hardships. Often times, the team who got you HERE is not the same team who will get you THERE. From my standpoint, what the Company is trying to accomplish is bigger than me sitting in the CEO chair, so if the Board were to decide that someone else with a next-level skillset were needed to sit in this seat to elevate BakerSCI to a mature stage, then I would remain Chairman of the Board and likely shift over to a CFO or a Chief Evangelist role. I thoroughly enjoy the people side of business and cultivating culture, which comes from my background in teaching and mentoring. As we grow, my skillsets may be needed elsewhere in the organization and, if so, I’m willing to consider those roles in the future.

Should we be fortunate enough to we have a liquidation or merger event in the near future, my desire is to remain engaged in data analytics in the health and fitness arenas. Currently, what’s out there is very subpar and I would personally love to do something with this technology in those areas as well as share that knowledge and expertise with students in a university setting.

In summary, our team has worked hard to have everything set up internally (converting to a C Corp, converting all debt to equity, showing marked progress on our IP Road Map, having three years of independently audited financial statements, building out solid governance and advisory boards, etc.) for this step to be taken with confidence with the right party who is ready to take this journey with us.