Sports Nutrition Co

    Property Management Co

    Kydosa approach to outcome dream enablement

    The company was rebuilt from a half-dozen disconnected applications into a governed AI-native operating model. Codex / AI FDE helps the human builder create durable system changes through a controlled change path, while also generating disposable dashboards, tools, and views from the digital enterprise twin.

    Property management outcome dream enablement diagram A property management company case diagram showing human builders, Codex AI FDE, knowledge workers, disposable software, a governed change node, applications and agentic workflows, OpenAI models, the ontology digital enterprise twin, and the stack of OpenAI, Cloudflare, DigitalOcean, Ubuntu, Postgres, and Kanban-style workflow tooling. Humans + digital workers Before: six disconnected apps After: governed AI-native operations Human builder ops / data / product Codex / AI FDE digital worker plans, edits, proposes Knowledge workers use the applications Disposable software dashboards, tools, views from ontology context returned to builder Governed Change Node durable changes only branch validate approve + merge Applications & agentic workflows portfolio ops, leasing maintenance, reporting OpenAI models run the stack retail OpenAI refined custom Ontology / Digital Enterprise Twin properties, leases, work orders reads ontology Stack: OpenAI + Cloudflare + DigitalOcean OSS: Ubuntu + Postgres + Kanban + etc. No side-door durable updates

    Appliance Manufacturing Co

    Outcome Deal Example

    The client was behind in retail.com sales at top home-improvement partners. An IT tatical ask would not achieve the outcome, commercial model pivot to the business sales commission: trade spend, go-to-market execution, and a flexible 3-year partnership.

    $400Kinitial IT ask
    $500M+target annualized revenue lift
    0.95%of in-scope retail.com sales
    3 yearsflexible partnership term

    1. Establish the goal

    Close the online sales gap without treating it like a narrow technology project.

    The company was behind competitors in online sales at major retail partners. The value case was not just e-commerce conversion; better retail.com content and lower-funnel execution would also influence store sales.

    Online mix shift value bridge A graphic showing online mix moving from about twenty percent to about twenty two percent, which combines retail.com growth and store influence to create a five hundred million dollar annualized sales ambition. Online mix shift +2 pts Current ~20% Target ~22% small mix move Retail.com growth + Store influence = $500M+ Small mix movement on a large revenue base creates the annualized sales ambition.

    2. Wrong buying path

    IT budget would have locked the work into scope, not value.

    1. Problem framed as techNeed tools to improve retail.com sales.
    2. Small strategy effort~$400K available, but not enough to change outcomes.
    3. Fixed scope pressureDeliverables become documents, integrations, or a narrow roadmap.
    4. Business distrustCommercial leaders will not fund a path they do not believe wins.

    3. Trusted and Incentive Aligned

    Move to bigger trade spend budget line item. Bundle product and services

    1. Business value poolFund from the spend already meant to drive retailer growth.
    2. Outcome productBring strategy, control tower, FDEs, inference, and execution muscle together.
    3. Flexible teamShift capacity across the work as the bottleneck moves.
    4. Shared incentiveCompensation ties to a small percentage of total sales.

    Flexible goal aligned operating team

    The team can solve for the constraint instead of defending a statement of work.

    Joint business planningRetailer plans, priorities, cadence, and governance.
    Marketing spend reviewShift from broad spend to lower-funnel retail media.
    Product page executionTitles, bullets, imagery, A+ content, ratings, and reviews.
    Control tower + dataSales, inventory, content health, share of voice, and signals.
    FDEs + strategyBuild the operating tools while shaping the commercial moves.
    Leadership governanceDecisions, issue escalation, and monthly performance readouts.

    4. Commercial model

    A small percentage of total sales keeps both sides aligned without creating a cost roller coaster.

    A percentage of incremental revenue would be too volatile: either zero payment, huge upside, or a higher client price for the same outcome risk. A small percentage of total in-scope retail.com sales creates steadier economics while still tying compensation to the business result. Simple calculation, no debates about dozens of variables.

    Annualized benefit run-rate $500M
    Three-year annualized benefit ramp Annualized benefit builds from one hundred million dollars in year one, to two hundred fifty million dollars in year two, to five hundred million dollars in year three. $100M Prove it Year 1 $250M Expand it Year 2 $500M Full run-rate Year 3 Value accrues as the team scales the playbook.

    5. P&L value tree

    Changing where the budget comes from, moving to business buyer - 400k 3 month tatical IT project becomes 24M 3 year partnership.

    Built from public FY2025 company financials and an illustrative internal P&L cube. Brand names are scrubbed; channel structure reflects the case context.

    $15.5BFY2025 net sales
    $2.4Bgross margin
    $1.6BSG&A expense
    $389Mcapital expenditures
    P&L value tree for the commercial pivot A P&L tree showing the internal brand, product, and channel cube feeding gross commercial sales, trade spend as a revenue reduction, net sales, cost of products sold, gross margin, SG&A with the IT budget, and net earnings. Internal P&L cube Commercial value tree Enterprise P&L Brands Scrubbed portfolio global, premium, mass, value, regional Products Large + small + CPG refrigeration $4.8B, laundry $4.4B cooking $3.7B, dishwashing $1.2B Channels P&Ls by route to market builders, top retailer A, top retailer B next-tier group, buying groups dealers and distributors Gross commercial sales pool Where revenue is created plans, assortment, pricing, media, content and retailer execution Highlight: trade spend lives here Incentives, allowances, co-op, promo Public P&L anchor $15.5B FY2025 net sales net of sales incentives Product economics ~$13.1B COGS implied from net sales less gross margin Operating value pool $2.4B gross margin $500M run-rate is material Highlight: IT budget lives here $1.6B SG&A the original ~$400K ask was a cost-center strategy item Enterprise result $318M net earnings FY2025 Deal implication Do not sell a scoped tech project into SG&A. Sell a commercial operating model into the value tree that controls trade spend and net sales.

    Problem frame

    Planning is still wired for scarcity, but the constraint moved to demand quality.

    Sports Nutrition Co’s legacy operating ontology treated retailer POs and co-man capacity as the primary planning truth. The new graphic shows the flip in one view: most weeks now need better demand sensing, while summer still carries real supply pressure from seasonal protein and co-man constraints.

    150-180dingredient to shelf
    ~50%RTD capacity at Co-Man 1
    summerseasonal supply exception
    weeklylocked command plan

    Ontology map

    Constraint flip

    The operating constraint moved from scarce supply to noisy demand signals, but summer remains a supply-sensitive exception that the outcome twin has to preserve.

    Current flow

    From noisy demand to weekly command plan

      Outcome twin input gap

      Do not optimize until the decision questions are answerable.

      The first outcome twin tab is intentionally a question system. Once the priority questions are answered, the next version can convert assumptions into objectives, constraints, confidence bands, and weekly scenario recommendations.

      6question domains
      18locked inputs
      Teamshuman loop
      Snowflakesystem of analysis

      Value tree

      Make the right flavor, in the right region, for the right store.

      The outcome twin’s value is not just a better forecast. It protects revenue by preventing avoidable stockouts and protects cost by reducing transfers, markdowns, and trapped inventory when flavor demand splits by geography.

      Outcome twin value weekly feasible plan Revenue capture demand Cost avoid waste + moves On-shelf availability by store, week, flavor Flavor-store match right item, right shelf Promo + LTO capture upside without stockout Transfer avoidance fewer emergency moves Markdown/write-off less trapped inventory Run + freight cost co-man and lane fit Key revenue metric Store-flavor service fill rate at retailer x region x SKU Key cost metric Imbalance cost transfer miles + markdown + lost sale Example mismatch Strawberry sold out East / extra West; Chocolate is reversed.
      Store-flavor serviceAre the right flavors in the right stores?
      Regional imbalanceWhere do stockouts and excess inventory coexist?
      Avoidable transfer milesHow much product movement is caused by bad placement?
      Gross margin savedLost sales + freight + markdowns avoided.