Less stress
and better,
trustworthy
decisions at scale.
Learn how our novel solutions can put the pieces together and help you optimize your data assets in the AI Era.
The Challenge
Generative AI (gen AI) has accelerated competitive evolution to an historic rate, forcing leaders to keep pace and finally resolve long-standing impediments, capability gaps, and data quality issues.
Bain: “You’re out of time.”
"Products and services seem likely to evolve quickly over the next six months, particularly since the establishment of large foundation models means that the cost for experimentation is relatively low.
"Waiting to see what competitors will do is tantamount to yielding the field."
Gartner: “The current state of decision-making is unsustainable.”
"65% of decisions made [in 2019] are more complex (involving more stakeholders or choices) than they were two years ago. The current state of decision-making is unsustainable."
2008: Leaders were already hitting a "complexity ceiling"
"The factors that come into play when making major decisions are so many and so complex that they exceed human decision-makers' capacity to make the right choices."
McKinsey: Market-leading adopters of generative AI report an array of implementation challenges.
"[70%] percent say they have experienced difficulties with data, including defining processes for data governance, developing the ability to quickly integrate data into AI models, and an insufficient amount of training data, highlighting the essential role that data play in capturing value."
McKinsey: "It's not just tech."
"Finally, leaders must understand that gen AI models generally comprise just 15 percent of any given solution. In other words: it’s not just tech. To create value, organizations must have all the elements in place—domain reimagining abilities; relevant skill sets (including the upskilling of nontechnical colleagues); a robust operating model; proprietary data. It’s only when those factors are in place that organizations will be able to unlock impact and move from experimentation to scale.."
HBR: Creation of data cultures has not been a priority for many companies
"Finally, and most discouraging,. a meager 20.6% of executives — barely one in five — reported that a data culture had been established within their companies...."
Now, imagine
a world where you can immediately identify that you trust the information you use to make crucial decisions and that your team's efforts are efficient and focused on the most important tasks.
Skillful implementation of AI-enabled processes and data management practices can make that a reality. No more last-minute realizations that something someone gave you isn't right, exhausting all-nighters for your team, missed opportunities, or strained relationships—just reliable, efficient, and impactful work.
It may be hard to imagine. Because if you are like many leaders, you have a lot on your mind.
Until then, uncertainty
How do you know if the information you use is trustworthy?
Did you ask the right questions, and were the instructions precise for the team?
Is the data complete and accurate, or does your team shoehorn the data you have?
Is your team synthesizing just the data you need, or are they wasting time boiling the ocean?
Have all potential actions and consequences (including unintentional) been identified and appropriately weighted?
What about the second and third derivative implications of an action?
How will you ensure that the shiny new black box of AI dropped into the middle of your decision-making process makes things better and not worse?
Why does everyone have to be a visualization artiste?
Why can't they give you synthesized information that doesn't take five minutes of orientation before you can apply your expertise?
Is it really that hard?!
Competitors
are also trying to answer those questions; someone will soon get it right.
When they do, your employees will prefer working for organizations that get it right because it will improve their lives the most.
So, will you gain a competitive edge or play catchup?
Leaders are concerned about challenging AI initiatives.
That may be because 2/3 of companies defer to leadership rather than being data-driven.
12% & 17%
Success rates of generative AI initiatives in Revenue & Growth and OPEX Cost Reductions (respectively).
85%+
Business leaders report feeling they are behind or only on par with their competition.
65%
Companies surveyed reported they will make decisions, usually by deferring to the most senior person in the room, and then justify the decision with data.
Why hasn't this been solved?
We perceive the decision-making chain as a complex entity, consisting of five intricate phases:
Ask: The formulation of the decision and the request for inputs.
Assemble: This is a complex process that involves data identification, acquisition, engineering, and governance.
Articulate: The analysis and synthesis of insights from data.
Act: Using information to commit resources and take action.
Assess: Retrospective analysis of the process.
The Assemble phase has seen widespread adoption of software and infrastructure engineering practices governance during the past ~ twenty years. That is possible because systems can automate oversight when process standards exist.
The adoption of automated governance for decision-making and the creation of presentation materials is rare. The primary obstacle is the necessity for defined standards, leading to the absence of the metadata crucial for automation.
Certification
Imagine that when you see a simple visual cue like a gold medal, you know the information your team is about to use to make a crucial decision is GMD™-certified.
This certification is not just a label but a confirmation of a rigorous process tailored to your organization that ensures vital information is trustworthy, synthesized, and easy to understand.
You should expect to find the gold medal on presentation slides, Excel workbooks, reports, and dashboards. Why? Because GMD™-certified information allows you to use pattern recognition to consume what you need intuitively quickly: insights synthesized from reliable data. That means you can use all of your cognitive focus to apply your expertise and confidently take action.
This is what application of the unified DI-to-PI™ framework and enabling GMD™ certification can give you and your team: Trustless confidence to make the big decisions.
What we do
Our offerings of data-related advisory, implementation, and change management support services are dedicated to assisting medium and large organizations.
Gold Medal Decision-making™
Our novel Decision Intelligence-to-Presentation Intelligence™ (DI-to-PI™) framework is revolutionary for businesses navigating the AI Era.
By implementing DI-to-PI™, you can set a new standard for your organization: certified Gold Medal Decision-making™ (GMD™).
Adopters jump ahead of competitors and improve employee morale by reducing stress while making better, trustworthy decisions at scale.
Strategic assessments
Building a new data platform or optimizing an existing one starts with understanding your current capabilities, tech limitations, and risks. We can help you focus on the most impactful steps to achieve the desired outcomes.
Properly scoping initiatives, creating roadmaps, and quantifying the impact of changes can accelerate time-to-value and optimize ROI.
Decision Intelligence (DI)
"DI is a methodology and set of processes and technologies for making better, more evidence-based decisions by helping decision makers understand how actions they take today can affect their desired outcomes in the future."(11)
"The key concept of DI is the idea that you can design decisions."(11)
Our distinctive combination of problem-solving approaches and a disciplined, agile method of crafting precise inquiries ensures that advanced analytics yield useful insights efficiently.
Presentation Intelligence™ (PI™)
Inputs to high-value decision-making should be unambiguous and easy to understand. Adopting generative AI can make this more difficult since most firms have yet to define standards for how the opaque "black box" should present visualizations.
We help clients define and implement presentation standards that ensure humans and AI consistently synthesize and present information so executives understand implications at a glance.
That means more time spent applying expertise and less wondering what the inputs mean and whether they are consistent.
Data ecosystem implementations
The acceleration of the AI Era has exacerbated the need for clients to have modern data ecosystems that can manage data and reveal high-quality insights at scale.
We can help you take advantage of the increasingly rapid pace of information creation while preserving confidence that data are timely and reliable.
About us
We deliver novel and innovative solutions backed by more than 700 years of data-related expertise.
Jeff Polack
Founder and Principal
Jeff is the creator of the DI-to-PI™ framework and the concept of certifying decision-making processes (Gold Medal Decision-making™).
He blends 30+ years of experience in financial services and data consulting with Agile principles to serve as a translator and facilitator for executives and data and analytics teams.
During that time he helped clients in Investment Banking, Capital Markets, Wealth Management, Private Equity, Healthcare, Media (TMT), Automotive, and Retirement Plan Sponsor sectors.
The Data Consortium
Expert talent network
The Data Consortium members are down-to-earth Caserta and McKinsey & Company alums with an average of 27 years of data-related experience. The group is dedicated to preserving our exceptional collaborative culture while helping our clients achieve their goals by transforming the utility of their data.
Members of the group have collectively served 80+ clients, many of them Fortune 500 firms, and acquired 20+ distinct professional certifications.
Selected client solutions
Innovative relationship and capital markets management platform for a private equity firm: Jeff designed and developed a novel, multi-platform solution that revolutionized Wall Street idea generation and financing processes for financial sponsors.
Jeff also collaborated with members of The Data Consortium to help implement these solutions with clients:
Data analytics platform for a streaming Media client: Jeff led a team that created an analytics platform based on Google Vision and BigQuery and an innovative shopping cart application that enabled non-technical users to search billions of records and retrieve documents and individually tailored reports. Personally developed data marts and dynamic dashboards using Tableau.
Strategic redesign of data ecosystem for a global investment bank: Jeff was a team leader for an assessment that cataloged data and gap-fit analyses across seven financial systems and provided senior executive-level education regarding data mesh concepts and a multi-year road map to resolve regulatory deficiencies.
Self-serve data science sandboxes for a Healthcare client: Jeff led a team that developed a migration solution that used AWS, Matillion, and Snowflake to enable the creation of on-demand, self-serve, and HIPPA-compliant data science sandboxes for use by cancer researchers.
Data analytics and data science platform for a Media client: Jeff led a team that replaced Alteryx ingestion pipelines and built an ML analytics platform that optimizes value creation by more accurately forecasting viewership before acquiring rights to content.
The combination of 'Novo' and 'Acuity' expresses the essence of our mission:
Novo is Latin for "make new, renovate; renew, refresh, change."
Acuity is the "ability to hear, see, or think accurately and clearly."
Together, NovoAcuity™conveys what we offer clients: New ways to see things that improve clarity, confidence, and lives. Novo is italicized because we are leaning into the opportunities and challenges of the AI Era. The upward blue arrow represents improvement; the gold arrow represents progress and the DI-to-PI™ framework. The gold circle represents Gold Medal Decision-making™ (GMD™).