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📽️ Check out a video demonstration for this use case, here. |
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Use Case Situation Description |
Improving spot margin performance through analytics KPIs in the process industry offers several advantages over margin/volume forecast methods. It enhances real-time decision-making precision, identifies profit opportunities, and minimizes revenue leakage. By leveraging data-driven insights, it optimizes production, reduces operational costs, and mitigates risks. This approach ensures proactive adjustments, maximizes profitability, and fosters competitive edge in a dynamic market landscape.
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Prescriptive Design Requirements |
Business Objective
Spot pricing is typically updated on a frequent basis (weekly, monthly, quarterly), or ad-hoc as market, competitive, and internal annual business plans require. The goal is to improve short-term spot pricing (non-contract customers) based on specific monthly margin, revenue, and volume goals (per the annual operating plan / forecast). They will do this using real-time pricing tools that allow for frequent pricing changes due to regular cost and market index changes, margin expansion goals, and other competitive forces.
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Not available at the moment. Will be communicated as soon as defined. |
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User Stories |
This is a list of all the usr stories associated with this use case.
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As a Pricing Manager/Pricing Administrator, I want to build the dashboard that uses my defined portlets. User Story Name - Cost data I want to: Load the existing cost data into a DM so I can: Use it in the dashboard to compare against actuals Acceptance Criteria: The cost data is available at the appropriate level of granularity to be used against history. User Story Name - Forecast data I want to: Load the existing forecast data into a DM so I can: Use it in the dashboard to calculate margins Acceptance Criteria: The forecast data is available at the appropriate level of granularity to be used against history. NB: If this data is not available, this dashboard should not be built at all as it would serve no purpose. User Story Name - Filters I want to: Define filters based on the dimensions available in the transaction history DM so I can: Use them to drill up and own into detail as needed Acceptance Criteria: All appropriate dimensions of the transaction DM are set as filters User Story Name - Margin calculation I want to: Calculate margins according to my standards, using the available cost data so I can: See in the dashboard margins which are consistent with my organisation’s definitions Acceptance Criteria: The dashboard margin totals reconcile to the other reports in my organisation User Story Name - YTD trends I want to: Confirm the standard formulas to calculate trends are appropriate so I can: See meaningful trends and take action as needed Acceptance Criteria: Standard formula: (YTD Current year – YTD Previous year) / YTD Previous year To be applied to revenue, volume, margin |
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Data Requirements |
NOTE: There have been no data requirements identified at this time
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Out-of-Scope |
NOTE: There have been no out-of-scope functions or features identified at this time
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Solution Design |
The solution aims to enhance spot margin performance in the process industry by leveraging analytics KPIs. Using data-driven insights, real-time decision-making precision can be improved, profit opportunities can be identified, and revenue leakage can be minimized while optimizing production, reducing operational costs, and mitigating risks. Pricing and sales teams in the chemical industry can achieve increased alignment and reduce the possibility of margin compression with the help of detailed visibility into spot revenue, margin, and volume performance over time, as well as trending details against the financial plan. Here is how this can be achieved in Pricefx.
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