MassChallenge interviews Stephen F. DeAngelis, Founder, President and CEO of Enterra Solutions, LLC.
The business world is flush with stories about big data, artificial intelligence (AI), machine learning (ML), and digital transformation. The cord that ties those things together is data analysis. As a result, a lot is written about data science and one can find many misunderstandings between AI, machine learning, and decision making. We came to meet Stephen DeAngelis, CEO of Enterra Solutions, and get more insights into Artificial intelligence and Autonomous Decision Science™.
Can you please give us some background on Enterra?
Enterra Solutions is the leading Autonomous Decision Science™ company providing data-enabled prescriptive and anticipatory analytics and insights for companies across a broad range of industries. Enterra automates a new way of problem-solving and decision-making, going beyond advanced analytics to answer queries, generate insights, and make decisions at the speed of the market. This powerful capability allows clients to uncover and understand the inter-relationships that lead to innovative new product development and innovation, heightened consumer understanding and targeted marketing, revenue growth tactics, and intelligent demand and supply-chain planning. Enterra’s analytics and insights help the world’s leading brands and organizations operate smarter by finding higher meaning in their data.
AI and machine learning are popular buzz words these days – can you help us to understand why there is so much interest?
Heightened competition, changes to customer expectations, digitization, and massive amounts of data creation occurring in nearly every industry – especially Retail and CPG – have solidified the value and interest in AI. Not only can AI help companies make more intelligent, agile decisions, but it can also anticipate problems and drive rapid solutions.
The abundance of data available to companies have driven a need for companies to make more data-driven and analytics-informed decisions. Marketplace disruptions, such as COVID-19, have only increased the need to generate actionable insights from data in faster and more market responsive methods. We’ve found that these competitive and marketplace resilience drivers have accelerated investment in corporate digital transformation efforts and increased the need and demand to implement AI systems to enable data driven insights. The ongoing labor shortage has also increased reliance on AI as companies automate to help keep operations moving smoothly.
Have companies been successful adopting AI?
We continue to see strong, successful adoption of AI, especially as companies continue to navigate the uncertain business environment driven by COVID-19, inflation, geo-political unrest and other market forces. The Retail and CPG industries are a good example of this. Believe it or not, optimally placing products on a shelf in a grocery store is a science. What product do you first see when you walk down an aisle? What’s the optimal shape, size, and color? Should you put conditioner next to shampoo? When is the best time to discount the product to maximize sales while minimizing shortages? CPG brands are drowning in decisions and AI is helping them make sense of their data at scale and at the speed of the market to improve decision making.
There seems to be an abundance of companies in the market that provide AI solutions – can you help us to sift through the noise and understand what is truly AI and what’s not?
The global AI and Advanced Analytics market is defined by solutions that assist in the autonomous or semi-autonomous analysis of data using complex techniques and tools that are more advanced than those of traditional business intelligence offerings. These solutions allow organizations to gain deeper insights into their business, make predictions, and generate recommendations to achieve specific business outcomes.
The most advanced analytical techniques include AI capabilities, which enable technology to draw conclusions from data, understand complex concepts, and interact with humans in a human-like manner. The techniques Enterra uses to draw insights from data – specifically Autonomous Decision Science™ (ADS™) – are amongst the leading methods currently being used in the market today.
However, as a buzzword, I believe “AI” has been overattributed to define technologies that would be more suitably dubbed as machine learning (ML). Some may say this is semantics, but there is nothing artificial, nor intelligent, about a machine learning algorithm. Machine learning technology has strong pattern recognizing capabilities but does not allow for insights and recommendations to be made with the subtle, judgement-based, reasoned approach of your best Subject Matter Expert or Data Scientist.
How is Autonomous Decision Science™ (ADS™) different than other AI technology?
Enterra’s ADS™ technology is the next wave of the analytical innovation journey after data science, combining a human-like reasoning AI, glass box mathematics, and non-linear optimization into one integrated platform. With ADS™, business teams can perform advanced analytics and activate natural language-expressed insights at scale — all at the speed of the market and without the use of data scientists. We combine our unique ADS™ technology with an industry knowledgebase of how products go to market to deliver insights and recommendations with best-in-class accuracy and actionability.
How scalable is ADS™? Can business users leverage the technology or is it geared towards data scientists? Will companies need to staff up data scientists as the solution is rolled out across the organization?
Our technology is absolutely scalable. ADS™ analyzes disparate data sources at the speed of the market and informs business teams in simple natural language regarding what recommendations have been made, why they have been made and how to action upon them. This reduces latency and dependency on data scientists and increases scalability across the organization.
We believe in democratizing analytics and delivering results in easy to understand, natural language so that action can be taken, and results can be achieved without the use of data scientists. In fact, our human-like reasoning AI software can serve as your data scientist, subject matter expert, and trusted counselor. It can analyze data, understand business processes quickly, accurately and with limited human intervention.
What competitive advantage can ADS create for businesses?
ADS™ is far more advanced than traditional data analysis – it’s the future of AI and the next step in the data science journey.
Global markets are constantly changing, and enterprises need the agility to identify and adapt to that change quickly. ADS™ enables enterprises to be systemically resilient and capable of decoding and navigating complexity in an increasingly uncertain and changing competitive business landscape. Intelligent Agents powered by ADS™ technology can autonomously monitor data, perform analysis, and to enable business users to proactively anticipate and dynamically respond to competitive and market changes, the result of which is faster, more informed decisions and decades of competitive advantage.
ADS™ is also one step ahead of any other semi-autonomous decision-making technology because it’s replacing the need for human intervention. Labor continues to be costly, and, in this case, extremely technical data scientists are hard to hire and retain. With ADS™, businesses can circumvent the need for advanced data analysts.
Has the power of ADS been proven in the market? What type of value has it created for companies?
ADS™ enables companies to streamline their business processes and achieve optimum results at scale with greater speed and lower cost. In doing so, ADS™ provides businesses with, in some cases, more than 1000% annual ROI.
ADS™ is being used by some of the most complex organizations in the world. The world’s largest CPG brands have adopted this technology because it leverages the most advanced analytics techniques in the market to deliver superior explainability and actionability of insights and recommendations. It is essentially the “brain inside” their organization, generating insights and making decisions faster and more accurately than ever before. ADS™ is >90% as accurate as human experts and has the capability to replace thousands of hours of labor to produce actionable results in minutes.
Why did you decide to join MC?
Utilization of data and AI is crucial for today’s emerging technology companies and in our advisory role with MassChallenge, we can offer our expertise and help guide the next generation of startups. We want to play our part in advancing the entrepreneurs and technologies of tomorrow and in order for them to grow, they need the tools and strategy of the future. It’s an exciting opportunity to help MassChallenge businesses and entrepreneurs disrupt the status quo.
What advice would you give to corporations and startups wanting to leverage the power of ADS?
Businesses ready to take the next step with ADS™ technology must prepare by:
- Identifying a high-value use case within the business that, if optimized, could generate an attractive financial return
- Verifying that data is available and stored in an accessible place (preferably the cloud)
- Securing subject matter expertise and operational staff to help support the system integration process
The intersection of these three areas will ensure that a company is ready to drive differentiated value for their organization, today.
We are delighted to officially be a part of the MassChallenge family, and we are excited to help our community of talented businesses embrace the latest innovation in enterprise analytics and decision making, ADS™.
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Stephen F. DeAngelis is a technology entrepreneur and patent holder with over 25 years of experience helping pioneer the application of advanced cognitive computing technologies and applied mathematics to commercial industries and government agencies.
Mr. DeAngelis was recognized as one of Esquire magazine’s “Best and Brightest” honorees as “The Innovator” and Forbes magazine named him one of the “Top Influencers in Big Data.” He earned a B.A. in International Affairs from the School of International Service at the American University in Washington, DC, where he concentrated in Sino-American Affairs and U.S. Security and Defense Policy.
