Explore three product walkthroughs for APO-to-IBP assessment, HPA readiness and S&OP Consensus. Understand the problem, the workflow and the business case in about a minute.
Cognto is an AI-native enterprise software company focused on SAP transformation and supply-chain planning. Our demonstrations help teams examine migration gaps and reconciliation choices. Findings, assumptions and unresolved decisions stay visible to the people responsible for the outcome.
We combine SAP and supply-chain experience with AI-assisted product development. Our internal AI workforce is separate from customer SAP environments.
SAP partnerInspect a representative APO landscape, proposed mappings and exceptions before shaping a migration plan.
Review a sample planning-area score, categorized gaps and a proposed action plan.
Compare functional positions and conditional alternatives, then review a draft Executive Pack.
Recommendations remain proposals. Unresolved conflicts stay with the human owner to decide.
Sample-data labels and explicit assumptions show what the demonstration and its effort model can support.
A demonstration deployment is available on SAP BTP. Production connectivity requires separate validation. Joule integration is a future direction.
Choose the planning question you need to answer. Watch a short product overview, explore the capabilities and see how the SAP architecture fits together.
Make mapping decisions and exceptions visible before committing to a migration plan.
Explore APO-to-IBPSee which readiness findings need attention and the evidence behind the proposed next steps.
Explore HPA readinessBring the disagreement into the S&OP review with the evidence already visible.
Explore S&OP ConsensusTurn a representative APO landscape into a structured discussion of functional gaps, proposed mappings and review gates before committing to the next stage of a migration.
Follow a representative APO landscape through functional gaps, proposed mappings and review gates.
Representative or synthetic data. Human review remains part of the workflow. No production SAP writes.
See SAP architectureAn APO transition involves planning areas, key figures, custom logic and integrations. Reviewing these separately can hide dependencies, repeat expert analysis and create false confidence that every capability moves directly to IBP.
Bring landscape context, exceptions and proposed next steps into one review. The aim is to reduce repeated comparison work, focus specialist attention on the difficult decisions and avoid building a plan around unresolved assumptions.
Review the scope represented by each sample landscape before discussing migration choices.
Keep gaps and architecture branches visible alongside the proposed review sequence. PP/DS and gATP need separate target-design decisions.
Documented demonstration on SAP BTP Cloud Foundry.
Application deployment foundation
Business Application Studio · subscribed tooling
Account services available · app integration unverified
Outside the current demonstration flow
SAP AI Core, HANA Cloud, XSUAA and Destination are available account services; their use by this app remains unverified. BAS is development tooling. Joule and live SAP integration are future directions.
Assume the same accepted assessment takes 600 person-hours manually and 300 with assistance, including human review and rework. At an assumed $150–250/hour, the released capacity represents $45,000–75,000 of gross modeled labor value before tool and setup costs.
Assessment and planning demonstration with representative data. It does not perform a live migration or change SAP systems. The scenario is hypothetical, not a measured customer saving or a shorter project-calendar promise. Released hours reduce cash costs only when they avoid actual spending.
See how a representative planning-area assessment organizes a readiness score, categorized gaps and a proposed action plan for a move toward the Harmonized Planning Area.
Follow a sample planning landscape through readiness findings and a proposed migration plan.
Representative or synthetic data. Human review remains part of the workflow. No production SAP writes.
See SAP architecturePlanning-area dependencies, custom key figures, master data and integration choices can scatter the evidence needed for an HPA assessment. Teams need to know which findings require validation before planning remediation or cutover.
Use a common view of the findings to prioritize expert review. The aim is less time assembling the assessment, clearer ownership of open questions and fewer assumptions carried into the next phase.
The demonstration offers three sample tenant profiles with different key-figure counts, master-data scope and integration patterns.
Categorized gaps make it easier to discuss where specialist judgment is needed, rather than treating one score as permission to migrate.
Documented sample-data application on SAP BTP Cloud Foundry.
Application deployment foundation
Business Application Studio · subscribed tooling
Account services available · app integration unverified
Outside the current demonstration flow
SAP AI Core, HANA Cloud, XSUAA and Destination are provisioned account services; app integration remains unverified. BAS supports development. Joule and live IBP connectivity remain future integrations.
Assume a scope-matched assessment falls from 720 to 360 person-hours, with human preparation, review and rework included. At an assumed $150–250/hour, that represents $54,000–90,000 of gross modeled labor value before tool and setup costs.
Representative-data demonstration. A sample score does not establish customer-tenant readiness or authorize cutover. The effort reduction is an assumption, not a measured result; remediation, implementation and migration execution are outside this model. Released hours reduce cash costs only when they avoid actual spending.
Compare functional positions, surface missing evidence and weigh conditional alternatives in a shared reconciliation workflow. Keep the final decision with the human S&OP owner.
Follow a synthetic capacity conflict through functional positions, conditional paths and a draft Executive Pack.
Representative or synthetic data. Human review remains part of the workflow. No production SAP writes.
See SAP architectureDemand, Supply, Finance and Sales can enter reconciliation with different assumptions. Time goes into rebuilding the disagreement, chasing evidence and preparing a decision brief before the owner can weigh the trade-offs.
Put issue facts, functional positions and unresolved conditions in one place. The aim is less manual preparation and repeated follow-up, with a clearer decision packet for the people accountable for the plan.
The overview makes the sample capacity constraint, revenue exposure and open decisions visible before functional review begins.
Bounded review rounds show the functional case and its missing evidence. Conditional alternatives feed a draft Executive Pack for the owner.
Documented static demonstration hosted on SAP BTP Cloud Foundry.
Application deployment foundation
Business Application Studio · subscribed tooling
Account services available · app integration unverified
Outside the current demonstration flow
BAS is development tooling. SAP AI Core and other SAP account services are provisioned, but app integration is unverified. Joule and live IBP integration remain future work. The demo performs no SAP write-back.
Assume monthly cycle effort falls from 120 to 96 hours, with 24 hours of human decision review unchanged. The 24 hours released per cycle total 288 hours a year, valued at $20,160 at an assumed $70/hour, before software and implementation costs.
Synthetic-data, deterministic demonstration. Alternatives remain candidates and the Executive Pack remains a draft. The efficiency figures are illustrative capacity value, not measured customer results or automatic cash savings. Released hours reduce cash costs only when they avoid actual spending.
These hypothetical examples show how an assessment or planning workflow could release team capacity. The assumptions are stated for discussion. They are not measured customer outcomes, guaranteed savings or estimates of calendar duration.
Assumed assessment effort: 600 person-hours. Modeled effort with the workflow, including human review: 300 person-hours. Modeled capacity released: 300 person-hours.
Scope: assessment and planning, not full migration execution. Software, setup and implementation costs are excluded.
Assumed assessment effort: 720 person-hours. Modeled effort with the workflow: 360 person-hours. Modeled capacity released: 360 person-hours.
Scope: readiness assessment. Human review remains required. Software, setup and implementation costs are excluded.
Assumed total cycle effort: 120 person-hours. Modeled total cycle effort: 96 person-hours. Decision-review effort stays unchanged. Modeled capacity released: 24 hours per cycle, or 288 hours across 12 monthly cycles.
At an assumed $70 per released hour, gross capacity value is $20,160 per year, before software and implementation costs. This is an illustrative value of released time, not cash savings.
A scoped evaluation should establish the actual baseline, review effort, data preparation and implementation costs before any return is estimated.
Review the representative landscape or planning inputs shown in the demonstration.
Examine gaps, proposed mappings or conditional alternatives with their supporting evidence.
Keep recommendations and draft plans subject to human review. The demonstrations do not execute production SAP actions.
A Cognto demonstration deployment is available on SAP BTP. The demos use representative or synthetic data and do not access a live customer SAP tenant or write to production SAP systems. Production integration requires separate technical validation and customer authorization. Joule integration is a future direction.
Discuss your planning questionTell us whether you want to explore APO-to-IBP assessment, HPA readiness or S&OP Consensus. A short, non-confidential description is enough. Please leave out credentials, tenant exports and customer data.
Cognto AI | Customer Solutions