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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.
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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."


(1) Bain, "You're Out of Time to Wait and See on AI"

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."


(2) Gartner, "How to Make Better Business Decisions"

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."


(3) Lorien Pratt and Mark Zangari,

co-creators of Decision Intelligence

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."


(4) McKinsey & Company, "The state of AI in early 2024: Gen AI adoption spikes and starts to generate 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.."


(5) McKinsey & Company, "The state of AI in early 2024: Gen AI adoption spikes and starts to generate value"

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...."


(6) Harvard Business Review, "Has Progress on Data, Analytics, and AI Stalled at Your Company?"

Painted Lightbulb
Painted Lightbulb

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?!

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Title for image

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).


(7) Lucidworks, "2024 State of Generative AI in Global Business"

85%+

Business leaders report feeling they are behind or only on par with their competition.


(8) Lucidworks, "2024 State of Generative AI in Global Business"

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.


(9) Gartner, "Maximize Your Data and AI to become a Decision Centric Enterprise"

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.

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DI to_PI_Framewor_Status_Quo
1. The assumed levels of optimization are illustrative. For the sake of discussion, the Assemble and Act phases are assumed to be optimal.

The Answer

Here's some excellent news: You can alleviate most of those concerns and frustrations and reduce stress throughout your decision-making process!


The combination of standards for crafting decisions and presentations, retrieval augmented generation (RAG), and vision AI, each with unique roles, enables the governance of the decision-making process from end to end and at scale. RAG aids in efficiently retrieving and generating data, while vision AI enhances interpreting and visualizing complex information.


With our novel AI-enabled, end-to-end decision-making process and data management framework, Decision Intelligence-to-Presentation Intelligence (DI-to-PI), we introduce a new standard: Gold Medal Decision-making (GMD). GMD aims to achieve the highest level of decision-making efficiency and effectiveness, ensuring that every decision is a 'gold medal' decision, leading to optimal outcomes.


The DI-to-PI framework consists of three integrated and automated operations protocols:


Integrated Decision Intelligence Operations (DIOps) is a data-driven process that empowers you to make faster, more accurate, fact-based decisions. It is centered on a Causal Decision Diagram (CDD) that serves as the "decision blueprint" for creating AI digital twins. This meticulous approach mitigates cognitive biases and creates artifacts that enable process auditing, giving you confidence in your decisions.


Data Ecosystem Operations (DataEcoOps) include using software-as-a-service (SaaS) solutions to monitor and automate many IT and software development operations (e.g., DevOps, DataOps, MLOps). Integrating those governance tools into the DI-to-PI framework gives confidence that the data used to make critical decisions is trustworthy.


Presentation  Intelligence Operations (PIOps) play a crucial role in the 'last mile' of the data highway, where data is transformed into insights. By applying AI, we ensure that information is synthesized and easily and quickly interpreted. This eliminates the traditionally slow and inconsistent business intelligence (BI) development process, allowing you to scale your decision-making at the same pace as technological evolution.


Certification of critical decision inputs is possible once governance protocols are integrated from end to end.

The unified DI-to-PI framework ensures consistency and the ability to scale cognitive processes to keep up with technology.
DI to_PI_Framework
DI to_PI_Framework
1. The assumed levels of optimization are illustrative. For the sake of discussion, the Assemble and Act phases are assumed to be optimal.
GMD Concept_Transparent
GMD Concept_Transparent

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.

Less stress and better, trustworthy decisions at scale.

What we do


Our offerings of data-related advisory, implementation, and change management support services are dedicated to assisting medium and large organizations.
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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.

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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.

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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.

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ex 1_1_13_square
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.

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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.
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Headshot Seated_Cropped_v_Enh_Brand
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.

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TDC Logo_and_Name_Trimmed_Background
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.

NovoAcuity

The combination of 'Novo' and 'Acuity' expresses the essence of our mission:

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).

Let's reduce stress and make better decisions.


Get in touch so we can explore how we can help you.