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Horizon Media today unveiled 11 companies named to the third cohort of HorizonOS Labs, the agency’s structured innovation accelerator. With more than 50 partners having gone through the program, Horizon serves as a curator of emerging technology, simplifying the often time-consuming process of identifying, testing and scaling solutions so clients can build bespoke operating platforms around their unique business challenges. The program is designed to distinguish viable innovation from vendor promises through a transparent, client-centric process focused on real-world application.
“The market is moving faster than annual technology reviews can accommodate,” said John Koenigsberg, EVP and Head of Platform Partnerships at Horizon Media Holdings. “One clear shift emerged from Cohort 3: the vast majority of partners are focused on growth, closing the loop between surfacing, modeling and finding – and actually driving action. What makes these capabilities valuable isn’t any one of them alone, but what happens when they connect with each other and with what a brand already knows.”
Cohort 3 is organized around three Growth Frontiers. They include:
Each frontier unifies what was once fragmented: paid, owned and consumer insight; media and creative; and human strategy and intelligent workflows. The 11 Cohort 3 partners, chosen from more than 600 RFI submissions, reflect Horizon’s commitment to an open ecosystem where clients can access best fit technologies without vendor lock-in or proprietary constraints.
The 11 were selected on what they can do: how readily they connect to the systems a client already operates, their willingness to work alongside other companies in the cohort, and concrete evidence that the work drives business outcomes.
“AI is changing the rules for how brands grow,” said Bob Lord, President of Horizon Media Holdings. “The brands that will drive growth aren’t looking for a better way to buy media. They’re solving for customer value by building an operating platform that brings their data, customers, technology and people together around the problems that matter most to their business. There’s no off-the-shelf answer to that. Horizon is committed to bringing the open ecosystem together to build the right capabilities for each customer.”
The Cohort 3 Partners — Grouped by Growth Frontier — Include:
Unlocking Growth from the Customers You Already Know
Creative Supply at the Speed of Everything Else
Winning Customers When Machines Shape Discovery
The Cohort 3 partners will be showcased at an in-person event in New York on October 1, where they will present to Horizon clients and engage in discussions around potential pilot deployments. Following the showcase, partners will be matched with interested client brands to scope and advance specific pilots, with client participation helping determine which opportunities move forward.
Looking ahead, HorizonOS Labs will open its next RFI process in early 2027.
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Turn BI insights into clear boardroom narratives that help executives understand what the data means, why it matters, and where action is needed.
In 2026, it’s no problem for enterprise organizations to capture data. Most are able to provide more info than their leadership teams can possibly absorb. The more challenging task is to take this information and make it accessible to an executive if a decision needs to be made.
Analytics teams can discover a significant change in how customers use your products or services, or they might be able to find a problem that’s hidden far down in your operational records. However, the learning becomes redundant in the boardroom! An in-depth story, perfectly intuitive for a data team, can leave an executive scratching his or her head and asking, “What do you mean this has implications for business?”
With a BI dashboard, you can display changes in performance. A discussion in the boardroom (or a more appropriate forum) must determine the significance of that change and the need for action.
This needs more than an over-simplification of charts. It calls for conveying the analysis in a written story that aligns with the decision-making process of a business.
Table of Contents:
Why Dashboard Delivery Fails the Boardroom
The Executive Translation Framework
Start With the Business Context
Bring Forward the Evidence
Connect the Insight to the Decision
Where Organizations Misread the Problem
Balancing Rigor With Readability
Turning Intelligence Into Executive Action
A dashboard and an executive presentation are not trying to accomplish the same thing.
A dashboard gives analysts room to investigate. They can move between metrics, trace changes, and look for patterns. That flexibility is valuable during analysis, but it can become a burden when the same dashboard is presented to senior leadership.
The executive should not have to work through the analysis to find the business issue.
Consider a company seeing weaker mid-funnel conversion. A dashboard might contain dozens of metrics showing where the decline appears across channels, segments, and periods. The board does not necessarily need to see all of them. What matters is whether the decline threatens the growth plan, what is causing it, and whether the economics justify intervention.
The underlying analysis still matters. It simply needs to sit behind the conversation rather than become the conversation.
That is where many BI presentations fall short. They communicate the discovery process instead of the significance of the discovery.
A useful translation process begins by changing the starting point. Rather than presenting what the analysis found, begin with the business issue that leadership needs to understand.
The first question should be about the business, not the model.
Instead of opening with “Our multi-touch attribution model shows a decline in organic conversions,” the presentation could begin with a more direct observation: “Customer acquisition has slowed in our primary market, putting pressure on the current growth trajectory.”
That framing gives the analysis a purpose. The attribution model can then explain what is happening beneath the surface rather than forcing executives to interpret the significance themselves.
Technical detail should not disappear from the discussion. It should appear when it helps answer a question or withstands scrutiny.
Once the business issue is clear, the analysis needs to establish what is driving it.
This is where BI teams can add real value. Instead of reproducing the full dashboard, they can isolate the part of the analysis that changes the decision. If conversion has declined, for example, the presentation might show that the decline is concentrated within one customer segment rather than spread across the entire business.
That distinction can change the conversation. Leadership is no longer debating whether the number is interesting. They are considering what the finding means for the strategy.
The final step is where many BI presentations become incomplete. They establish what happened but stop short of explaining what leadership needs to decide.
The presentation should make the decision visible. If action requires additional investment, executives should understand what that investment is expected to achieve. If the recommendation depends on an assumption, that assumption should be made clear.
This also affects the design of the presentation itself. A single focused visual will often do more work than a dashboard crowded with metrics. The language should stay close to the business issue rather than the mechanics of the analysis.
The objective is not to make the data simpler. It is to make its significance easier to see.
Many organizations respond to poor executive communication by investing in better analytics skills or more sophisticated visualization tools. Those investments can improve the analysis without solving the underlying communication problem.
A team can produce technically sound work and still struggle to explain why the finding matters to the business. The missing skill is often judgment: knowing which part of the analysis deserves attention and which detail can remain in the supporting material.
There is also a tendency to equate more evidence with greater credibility. In practice, an executive presentation can become less persuasive when every metric and methodological detail is brought into the room. The quality of the analysis should be evident in the argument, not measured by how much information appears on the screen.
Another issue is the treatment of historical data. A dashboard may show that margins have fallen or churn has increased, but neither observation tells leadership what happens next. The value comes from connecting that history to a forward-looking view.
That might mean showing how the trend affects the next planning cycle or testing whether the conclusion holds under different assumptions. Historical data becomes strategically useful when it helps leadership think about what comes next.
Making a BI narrative easier to follow does not mean reducing the quality of the underlying analysis. The analytical work should remain rigorous. What changes is the way that work reaches the decision-maker.
A strong presentation usually makes its central conclusion clear early. The evidence that supports it can then follow without forcing executives to reconstruct the argument themselves.
It is equally important to show the cost of waiting when the analysis supports such a calculation. If a deteriorating trend could materially affect the next two quarters, that consequence belongs in the discussion.
Uncertainty also needs to be visible. When an outcome depends on factors outside the company’s control, scenario analysis can show where the recommendation remains sound and where it begins to change.
This gives leadership something more useful than another view of the dashboard. It gives them a reasoned interpretation of what the data means for the decision in front of them.
The value of BI is ultimately determined by what happens after the insight is found.
A sophisticated analytics environment can reveal an important shift long before it becomes visible in financial results. But if the finding reaches leadership as a collection of charts and technical observations, its commercial value can be lost.
The answer is not to remove complexity from the analysis. It is to separate analytical complexity from executive communication.
The dashboard should continue doing what it does best: helping teams investigate the business. The boardroom needs something different. It needs a clear argument built from that investigation, with enough evidence to support the conclusion and enough context to make the decision understandable.
When that translation becomes part of the BI process, analytics stops being something leadership reviews and becomes something leadership can act on.
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