137 件 ・ 関連度順
概要と使いどころ
Use when the user asks "what is coming next?", wants strategic forecasting, or is hunting weak signals of emerging threats before they materialise. Covers signal identification, trend analysis, and scenario development.
日本語の概要は準備中です。原文の説明を表示しています。
"Build three-statement financial models (Income Statement, Balance Sheet, Cash Flow) with revenue forecasting, assumption management, and scenario analysis. Use this skill when the user needs to project financials, build a fundraising model, create financial projections for a business plan, or evaluate M&A targets — even if they say 'build a financial model', 'project our revenue', 'how much money will we make next year', or 'model this acquisition'.".
日本語の概要は準備中です。原文の説明を表示しています。
"Build ARIMA models for time series forecasting with trend and seasonality decomposition. Use this skill when the user needs to forecast future values from historical sequential data, test for stationarity, or select ARIMA parameters — even if they say 'time series forecast', 'predict next month sales', or 'ARIMA model'.".
日本語の概要は準備中です。原文の説明を表示しています。
Analyze sales pipeline, historical revenue, conversion rates, and assumptions to produce forecast scenarios. Use for sales reviews, RevOps planning, and founder revenue forecasting.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a task needs the judgment of an Economist — estimating a demand elasticity or causal treatment effect from observational or experimental data, building a cost-benefit or welfare analysis for a policy or pricing decision, forecasting a macro or market aggregate under stated assumptions, or stress-testing whether a "the data shows X" claim survives a confounding-variable check.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a task needs the judgment of an Advertising Sales Agent — pricing an ad-inventory package against a client budget, building a media-kit pitch, protecting yield on scarce inventory while moving remnant, or forecasting close rate on a sales pipeline. Sell-side: this role sells a publisher's or station's own ad space/time to advertisers, the opposite side of the table from a buyer-side advertising-promotions-manager who purchases media on a client's behalf.
日本語の概要は準備中です。原文の説明を表示しています。
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.
日本語の概要は準備中です。原文の説明を表示しています。
Revenue Intelligence setup: activating the RI app and its CRM Analytics assets, Einstein deal insights, the opportunity-change waterfall, and forecast-accuracy analytics for sales leaders. NOT for configuring the Pipeline Inspection view, its metrics and review cadence - use admin/pipeline-review-design. NOT for forecast types, categories, rollups and quotas - use admin/collaborative-forecasts.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize and stress-test a logistics system end-to-end — chains route optimization, warehouse operations review, inventory demand forecasting, supply chain risk analysis, and peak-load testing. Use for delivery platforms, warehouse management systems, fleet routing, or supply chain software.
日本語の概要は準備中です。原文の説明を表示しています。
Audit workforce scheduling systems for labor optimization and compliance. Triggers: you need to evaluate labor demand forecasting accuracy, shift generation and optimization algorithms.
日本語の概要は準備中です。原文の説明を表示しています。
Audit a real estate analytics platform -- evaluate comparable sales and rental engines, automated valuation models (AVM), demographic and economic indicator pipelines, submarket scoring, gentrification detection, price forecasting accuracy, market cycle analysis, and risk modeling.
日本語の概要は準備中です。原文の説明を表示しています。
Audit public sector and government resource allocation systems for budget optimization algorithms (zero-based, incremental, performance-based), service demand forecasting (ARIMA, Prophet, regression), equity-based distribution scoring (CDC SVI, environmental justice indices.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze energy load forecasting systems including demand prediction models (ARIMA, Prophet, LSTM), weather API integration, peak shaving strategies, demand response program optimization, renewable intermittency handling, net load duck curve management.
日本語の概要は準備中です。原文の説明を表示しています。
Audit demand forecasting models and inventory optimization logic -- forecast accuracy (MAPE, bias), safety stock calculations, reorder point strategies (EOQ, ROP, min/max), ABC/XYZ classification, demand signal pipelines, and multi-location network optimization..
日本語の概要は準備中です。原文の説明を表示しています。
Analyze MRO parts inventory systems for field service optimization -- truck stock composition, first-time fix rate improvement, reorder point calculation, safety stock sizing, obsolescence detection, and demand forecasting..
日本語の概要は準備中です。原文の説明を表示しています。
Analyze food supply chain systems for waste reduction opportunities including shelf life prediction models, FIFO and FEFO inventory rotation enforcement, demand forecasting accuracy and bias, donation logistics workflows, cold chain temperature monitoring, and sustainability reporting against EPA Food Recovery Hierarchy and UN SDG 12.3 targets.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze fleet maintenance programs for preventive maintenance scheduling effectiveness, parts inventory forecasting, vehicle downtime minimization, total cost of ownership modeling, and telematics integration.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes apparel demand prediction systems for trend forecasting, size curve optimization, color and style analytics, sell-through rate tracking, and markdown optimization following CPFR collaborative planning and GTIN product identification standards..
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes asset lifecycle planning systems for capital expenditure forecasting, replacement scheduling, total cost of ownership modeling, depreciation tracking, and facility condition assessments using IFMA standards and Facility Condition Index scoring..
日本語の概要は準備中です。原文の説明を表示しています。
Automate AR workflows: aging analysis, collection prioritization, payment follow-ups, cash application, and bad debt forecasting.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze design trends and recommend appropriate styles, color palettes, and typography systems for your project based on current design movements. NOT for accessibility auditing or full design system creation.
日本語の概要は準備中です。原文の説明を表示しています。
Strategic analyst that maps competitive landscapes, identifies white space opportunities, and provides positioning recommendations. Use when users need competitive analysis, market positioning strategy, differentiation tactics, or "how do I stand out?" guidance across any domain (portfolios, products, services). NOT for market size estimation or financial forecasting.
日本語の概要は準備中です。原文の説明を表示しています。
Infectious disease modeling with SIR/SEIR models — R0, fitting, forecasting, and intervention scenarios.
日本語の概要は準備中です。原文の説明を表示しています。