Strategic Consortium of Intelligence Practitioners is the leading non-profit dedicated to competitive intelligence training, education, and certification. Today, the guest will grace us with his expertise in leading a successful organization with an intelligence-driven environment. Paul Santilli, the Chief Executive Office and Executive Advisory Board Chair Emeritus of the Strategic Consortium of Intelligence Practitioners (SCIP), navigates through running an intelligence-based organization. He identifies three concepts that perpetual disruption illustrates in organizations. Paul also provides insights into the fundamental components of an intelligence-based organization. He emphasizes the importance of navigating the intelligence ecosystem for startups and smaller organizations. You better not miss this episode if you want to know how your organization will succeed in an intelligence-driven environment.
—
Watch the episode here
Listen to the podcast here
Running An Intelligence-Based Organization With Paul Santilli
It is my pleasure to introduce you to Paul Santilli, the CEO of SCIP, which is the Strategic Consortium of Intelligence Professionals. You may be wondering why that has to do with you as a business owner and you are going to know all about that in this episode. Paul, thank you for joining me.
Thank you so much, Allison. It’s a pleasure being here.
Our world is changing so fast. I’m pretty sure that every generation says that. I feel pretty old saying that but why is the intelligence narrative so important to you, SCIP, and the community in general?
This is a fundamental thought process that organizations and individuals as a whole need to grasp. The reason is that as many folks know, the competitive intelligence discipline has been around for decades. It’s been instrumental in helping organizations compete in the marketplace. What happened is the advent of this pandemic and the outcome of the pandemic has amplified and shown organizations how unprepared they are, especially from a digital transformation perspective.
A lot of organizations were caught exposed without having a lot of ability to adjust to the environment around them and came to the realization that the intelligence-driven environment is one that’s super critical for organizations to succeed. I’ve talked many times about these three concepts that the pandemic, or what I call perpetual disruption, will usually illustrate in organizations.
I call these the three A’s. One of them is Amplify. It’ll amplify your business value proposition and your strengths and weaknesses in the organization. It could be on your infrastructure, digital transformational abilities, nimbleness of the organization, and so forth. Secondly, it’s the ability to accelerate your value proposition, where the trajectory of your value proposition is going, how well you are prepared to meet these challenges going forward, and being able to adapt to certain concepts within the marketplace. The third A is around Augmentation. It’s your ability to augment your product and services portfolio to fit the needs of this constantly changing business and client-customer relationship.
What this pandemic has done is exposed organizations in these three A areas and has required organizations to take a hard look at their infrastructure, IT infrastructure, and the use of data, especially in a world where everything is data-driven, and use that data to drive an intelligence behavior within those organizations that allows them to become much more in tune with changing climate, customer needs, business conditions, and having their organizations adapt accordingly. It’s been extremely important, especially from a digital transformation element for organizations to realize that. You’ll witness that through a lot of titles in organizations. You see chief data officers, chief intelligence officers, and things like that, realizing the need for this capability within the organization.
The need is quite broad. I don’t know an organization that doesn’t need intelligence to be competitive. What are the fundamental components of an intelligence-based organization?
There are a few. I could go and speak for hours on this topic alone because it’s a pretty in-depth topic so to speak. You need intelligence organizations that are integrated and entrenched in the culture of the company. You need this to be a horizontal function such that the intelligence is pulled from all different organizations within the company. You need to have this intelligence function that’s integrated into the strategy and the culture of the organization.
Many times, intelligence activities, functions, and organizations are relegated to a corner unit or a silo base that maybe reports to the marketing or sales organization. That is a traditional and very inappropriate place to put intelligence. It needs to be ingrained into the whole culture and the executive and leadership decision-making capabilities and the strategy itself. It’s got to be something that’s part of the organizational DNA so that it becomes a data-driven organization through intelligence.
If you look at the intelligence value chain, which is what I call it, you have data that drives intelligence, insights, execution, and an outcome. That value chain is integral to the success of an organization. It’s all around this intelligence and data-driven perspective that helps organizations compete and help to satisfy customer needs.
Can you talk a little bit about the best way to evolve from siloing intelligence into bringing it to the organization as a whole?
A lot has to do with organizational structure. Flatter organizations are quick in decision making but it’s the ability to pull intelligence from all different areas. Traditionally, intelligence has been looked at as more siloed in a competitive intelligence sort of nomenclature or lexicon. What I’m trying to do is to use that competitive intelligence core foundation and open it up to what I call the intelligence ecosystem.
That’s talking about the intelligence that comes from human intelligence. It could be product intelligence, R&D intelligence, financial intelligence, and so on within an organization that needs to pull all of that together to have a comprehensive intelligence model, ideally real-time because I will change it so quickly. Our ability to pull this together and act upon this intelligence will differentiate a successful organization from other organizations that don’t know how to use that and frame it up.
Let’s use an example from my world and maybe we can frame this for people. In my world, data has been very unavailable or opaque. You get part of the data but you don’t get the whole thing. You certainly don’t get enough to do any predictive analytics or any true understanding of what’s driving your costs.
I’m in the health insurance, healthcare space. Healthcare and health insurance are not the same thing. Healthcare is healthcare. That’s how we take care of the humans. Health insurance is how you finance it. One has nothing to do with the other. We are just starting to see great analytics tools come into the market so that we can say, “This is what you had. This is what’s coming. This is where you benchmark against a small, medium, and large population,” but it is a cultural change. Some people are like, “We don’t want to know.” “You can know.” Others are like, “How do I get my hands on that? How much does it cost? When can I do it?” How do you bridge that gap? I imagine that both kinds of people exist in any organization.
The challenge we have as intelligence and data professionals is to bridge that gap. You brought up a good point about healthcare versus the financial aspects of health insurance and stuff like that. The ability for us to gather and scrape the data fields and mine better data is because of the fact that we are in a huge data-populated world. That’s the whole reason why artificial intelligence is becoming to such fruition because of two capabilities. 1) The availability of data, which we’ve never had in the past. 2) The computing power of our technology. When you have those two things together, you can provide almost real-time AI-type solutions.
We need to remember that AI is a tool that’s in your toolbox. You use that tool to mine and hopefully decipher the vast amounts of data to bring those golden nuggets to the surface that you can act upon. You have those individuals that are wanting to gather that new information to understand how to frame this up for the future, and then you have the other folks that are saying, “I’d rather stay the course and keep things the way they are. I don’t want to get outside of my box.” I hear that a lot in the intelligence community as well, especially when I talk about this intelligence ecosystem.
To effectively compete in the marketplace, there’s no such thing as returning to normalcy. Normalcy is not going to exist. Normalcy is what I call a constant or a perpetual state of disruption. It could be a minor disruption, like a flat tire in your delivery truck, or major disruptions like wars, pandemics, typhoons, or things like this. You cannot have an organization in the world that ignore these sorts of impacts on your business model without suffering the consequences.
To effectively compete in the marketplace today and tomorrow, there's no such thing as returning to normalcy. Normalcy is not going to exist. It is a constant or perpetual state of disruption. Share on XHistory is wrought with the number of organizations that have failed to see this behavior coming across. They put their heads in the sand because they’re like, “I don’t understand it. I don’t want to know about it because I feel comfortable in this box.” You can’t operate that way in the world. This is where it’s critical around data-driven intelligence operations, the ability to mold your company in such a way that it reacts effectively to the signals that come out of your intelligence. Your organization is structured to be nimble enough to pivot into an environment that’s favorable to the customer as well as favorable to your infrastructure requirements.
I found that those things are often not mutually exclusive. Typically, what’s right for the customer is often right for the organization long-term but maybe not short-term. Has your experience been the same?
No. It depends on the products or services you’re offering and the scope of what you’re doing. Local companies versus global companies have different implications associated with this. In the long run, you need to look at the bottom line, which is the customer is king. You need to look at how you best satisfy customers’ needs.
Organizations, historically, when you get done with a program, the customer’s happy, and everyone’s patting themselves on the back, when you turn around, you see a lot of dead bodies that you had to go through to get to that success factor with the customer. I use that metaphor and analogy quite often. You have to have an organization that’s run efficiently and effectively to keep your cost models in place so that you can satisfy these customers on an ongoing basis rather than a one-and-done thing. That is why we need to be very careful. Not only satisfy the customers’ needs but how did we get there? What’s the process? How many dead bodies do we have behind us in getting to that point?
There’s often a perception that competitive intelligence is only available to extremely large employers. The average employee size is nineteen. Many employers have 50, 80, and 200 employees. Competitive intelligence is almost more important for them than for the big guys.
There’s a need for intelligence in startups, incubation areas, and smaller entrepreneurial-type behaviors. I’ve been engaged with many organizations in that. I’ve also been engaged in the Fortune 100 and Fortune 50 companies. Surprisingly, many of these larger companies have very small intelligence organizations. The misnomer that I want to clear the air on is that we need to not have people with intelligence in their title as only being the intelligence people.
Anybody in an organization has an inherent intelligence requirement, behavior, and role to provide to the centralized organization. If you’re going to look and try to satisfy a customer need, are you going to go research only on the customer, business, and everything else without talking to your sales organizations, backend operations, or anything like that? No. These people have a ton of intelligence that you need to pull together. We all have that intelligence job title inherently in our position and role. That’s an important concept to note.
Do you think that the popularity, maybe a better way to say it, of AI tools and the availability of large language model data sets is a competitive advantage for a smaller or mid-size employer?
In this environment, I highly stress for small or large organizations to use tools for them to acquire, analyze, and process data. The answer to your question is a resounding yes. AI-driven tools can not only collect, analyze, and provide solutions but also are predictive and prescriptive in nature. That’s the key part there, the prescriptive. Predictive is coming into play with foresight’s abilities. With prescriptive, what do we do about it? How do we behave?
This is an expansion of what we call in the industry a scenario planning situation where, manually, you would do these things, have a dozen or so scenarios that you would play out, and understand the what-ifs in this sort of a playground. With AI tools and compute horsepower, you can do hundreds if not thousands of these what-if simulations together. That would only take minutes. This helps you understand what you need to do probability-wise and the prescriptive nature of things. That is a long answer to your question about yes, it needs AI capabilities to help support it.
We use AI tools here as much as we can. I use AI tools as much as I can. If you ask the right question and there’s some art to that, to figure that out, what you will get back is remarkable. In my experience, it’s never a finished product. You still have to go back in and verify what information they give you. You might have to clean up the writing and you need to make it your own a little bit but it has been a remarkable tool for us. Is the prescriptive part what disturbs people so much? Is that what they’re afraid of?
There are a couple of things I want to comment on for what you asked. The prescriptive part is a challenge because there are so many what-ifs out there. It’s trying to predict the unpredictable and that’s always a challenge. I want to get back to the part about how AI tools can help influence and develop your needs and so forth.
What we have to be careful about is when we start talking about generative AI capabilities, we need to understand that those AI capabilities are usually based on all the content that resides on the internet, for example. As you get outputs from the internet, you’re only going to get as good of an output as what the input was. You have the GIGO, Garbage In, Garbage Out, scenarios but moreover, you have the aspect of introducing bias.
Regardless of whether you’re trying to minimize or design out the effects of bias, there are hundreds of different types of biases that you need to take into consideration. These become somewhat of a controversial topic to talk about in terms of what is bias, what is fact, and what is truth. I don’t want to get into that conversation. That’s a whole other episode we can do. The bottom line is understanding how these tools can aid you in getting to a certain point but you have to apply the human intelligence, that differentiation and uniqueness that yields you the result to fit your narrative. That’s what it all boils down to.
What about evolving your narrative? When you can access the huge quantity of data that is available and you are looking to research or learn something, what are your best strategies for filtering that? You do have to filter it in some way. Otherwise, you’d be under this mound of data.
I’m a big advocate of triangulation. You’re getting multiple sources of content to validate, substantiate, or maybe invalidate the findings of others. You’ll have many organizations. This is a competitive practice that happens all the time. You have your basic organization that will publish information that’s wrong purposely to make you go in a different direction. That happens all the time.
Certainly, one data point is a data point but you shouldn’t base your major decisions on a one data point scenario. You need to triangulate multiple locations, a third party unbiased, and so on to make sure you can validate and have more credibility in that data that would allow you to make the decision-making process that much more believable and realistic.
You need to triangulate multiple locations to ensure you can validate and have more credibility in that data to make the decision-making process more believable, realistic, and sound. Share on XHow has SCIP and the concept of the intelligence consortium fulfilled the needs of the intelligence community? By intelligence community, we’re not talking about spies running around in trench coats. We’re talking about people who need to make decisions every day.
Speaking of the spy thing, I tell people I’m in the intelligence business and they say, “You’re with the CIA?” I’m like, “No, I’m not with the CIA.” We have people as part of the consortium and from the government with three-letter names, as they like to say. To your point about this whole concept, we changed the name to Strategic Consortium of Intelligence Professionals. That’s a very important concept to understand. The intelligence ecosystem is broader and much more depth than a traditional competitive intelligence format.
By all means, I want to make sure everyone is very clear on understanding that the win-loss, Porter’s five forces, scenario planning, and all the kinds of things that are part of that competitive intelligence foundational toolbox are intact with SCIP. We have thousands of assets, best practices, tools, templates, and PPT files that relate to equipping intelligence professionals with the necessary skill sets they need to be effective intelligence professionals within their organizations. We’re building on top of that as part of this consortium to include other intelligence disciplines around human intelligence, social intelligence, and economic intelligence.
Think of it this way. We live in this big large data environment where data is boundless and edgeless. It’s pervasive in everything we do. By definition, data drives intelligence. Through association, theoretically speaking, intelligence is all around us in the same way. If we use that as an ecosystem that is part of the consortium model, then the consortium is pulling in all of these different intelligence-related functions around AI, tool sets, innovation, and entrepreneurialism.
We have a big program within sustainability and social responsibility elements of how we’re building up how to use intelligence to improve infrastructure in developing countries, sanitation systems, water supplies, natural habitats and woodlands, and things of that nature. We’re building these intelligence centers of excellence around the globe. There’ll be dozens of them in 2024 that would be focusing on what we call these ITT, Intelligence Think Tanks, that’ll be looking at the intelligence needs of those local communities around the world. We’ll have them in Europe, Asia, Africa, and so forth.
We’re establishing partnerships and what we call affiliates with a number of organizations around the world that bring in other perspectives in the intelligence ecosystem that’s part of this consortium feel. The cool thing about this is it’s all happening globally. This is something we’re building upon this foundation we have and pulling this consortium concept into play on a global basis. It’s very exciting. I’m very passionate about it. It’s going to make an impact.
What I took from that is that, yes, this is a global activity for you but intelligence is still local to a certain extent. You need that local feel and experience as well.
The cool thing about that is you can’t have an intelligence model that’s cookie-cutter. 1 cut out and it’s going to fit in 50 other locations. This is the whole concept around these centers of excellence where we have these intelligence locations in Eastern Europe, Africa, Asia, Japan, India, and so forth that have localized needs around their intelligence community so that you get a customized bespoke solution set that fits theirs, that’s different from the US, Argentina, and Ireland, for example.
This is where you have to bring that together. That’s the power of the consortium where you can get this localized concept to bring it all together. You have a tremendous powerful opportunity here to change the world. We like to call it intelligence for the betterment of people and the planet. That’s how we want to put a foundation in place.
What you’re doing is remarkable. What would be your best piece of advice for an employer with between 105 and 100 employees to enhance their intelligence?
I share these thoughts. I can go into my sales pitch but I’m not going to do that. It’s essentially the realization and understanding that data and intelligence approaches are an absolute must in organizations. It’s not a nice-to-have. It’s a must-have. You need to have a culture and an infrastructure that supports this intelligent mind and have it driven by executive leadership and CXOs of the organization to fully engage and then grasp the concept around data-driven intelligence and decision-making to be successful.
Once you have an organization that’s centered on that concept, the rest of the execution and business outcomes that get generated from that is the next things that happen almost in a production-like environment. It’s critical for the engagement of the C-Suite and the business leadership to internalize this.
Bring it down to the rank and file.
It’s got to be ingrained in the corporate DNA and the culture. That’s how it boils down to it.
We will leave it at intelligence is for everybody in your organization, not just the sales and marketing folks and the finance folks but for everybody to help you compete on a bigger level. Thank you for joining us. I always appreciate you. If you liked the episode, leave a review, and give us a share or a thumbs up. It helps us spread the word. We will see you next time. Paul, thank you for joining us. I appreciate it.
Allison, it’s been a pleasure. Thank you for having me.
Important Link
About Paul Santilli
Paul Santilli is the Chief Executive Office and Executive Advisory Board Chair Emeritus of the Strategic Consortium of Intelligence Practitioners (SCIP) organization and is active in several advisory roles to industry conferences and forums. Paul presents worldwide on Intelligence, Innovation, and Strategy in keynote and executive coaching capacities, and has published numerous papers in industry and academic journals related to Intelligence Modeling, Innovation, Disruption, and Strategy. He is a recognized thought leader around Industry Intelligence, Insights and Strategy, and chairs Executive Customer Councils and Industry Advisory Boards globally.
