Glossary: Financial Planning and Analysis

From A for Agent to W for What-if Analysis – here is a glossary of 27 words and expressions related to the field of budgeting, planning, financial forecasting👇

Click on a word to read its definition.

Agent Datawarehouse Operational planning
Allocation Dimensions Point of view
Budgeting ETL: Extract, Transform and Load Profitability analysis
Bottom-up budgeting Financial Planning Rolling forecast
Top-Down budgeting Financial Planning and Analysis Scenario-based planning
Business analytics Forecasting Scorecarding
Business drivers Goal seeking Sensitivity analysis
Business intelligence KPI Strategic planning
Data lake Machine learning What-if analysis

Agent

An agent is a background process in charge of notifying users of the application in case a specific condition is true. This functionality is generally used to provide notifications and alerts automatically to the users in case critical conditions, such as amounts which are above or below a threshold, are valid.

A practical example for this functionality could be to warn the Sales Controller if the sales in a specific region are deviating more than 10% from the budgeted amount.

Allocations

Allocation is the process of dividing a total amount in different parts. In FP&A, allocations are widely used to divide the amounts for the underlining dimension based on specific drivers. For example, when indirect direct costs, the driver could be the amount of revenues. When allocating an amount on a monthly basis we could use seasonality as a driver for the allocation.

Budgeting

The budgeting process enables the organisation to define a detailed short-term plan (1 year) on how the organisation allocates the resources and the organisation’s profitability. The assumptions of budget are often based on the actuals of the previous financial period and the objectives defined in the financial and strategic plan.

Bottom-up budgeting

With a bottom-up approach, the process starts in the individual departments where managers create a budget and then send it upwards for approval. That budget is either approved, revised or sent back for modifications, and a master budget is created from the various departmental creations.

Top-down budgeting

In corporate budgeting, a top-down approach involves the senior management team developing a high-level budget for the entire organization. Once these budgets are created, amounts are allocated to individual departments, and those departments must then take those numbers and build their own corresponding budgets within the confines of the executive-level-created budget.

Business analytics

Business Analytics is a set of best practices and processes which aim to achieve Predictive Analytics (“What could happen in the future?”) and Prescriptive Analytics (“Which should we do?”).

Predictive Analytics make use of technology to define future probable scenarios and their probability. This is performed by making use of statistical models, machine learning, AI and more specifically deep learning algorithms. By defining the future possible scenarios, the management can adjust the financial plan to reflect more accurately the scenarios.

Prescriptive analytics make use of technology to test several actions that an organisation could take and predict all the different outcomes. The aim of prescriptive analysis is to finally pick the action that predicted the best outcome to support the decision-making process.

Business drivers

Business drivers are the business factors that directly influence the performance of a business. As an example, the sales performance could be influenced by drivers such as demand, price, seasonality, competition, marketing investments. Identifying key drivers is an important process for a business to define the appropriate planning methodology.

Business Intelligence

Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information which helps executives, managers and other corporate end users make informed business decisions. BI encompasses a wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against that data and create reports, dashboards and data visualizations to make the analytical results available to corporate decision-makers, as well as operational workers.

Business intelligence is focused on descriptive analytics which aim to answer the question “What has happened?”

Data lake

A data lake is a storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured, and unstructured data. The data structure and requirements are not defined until the data is needed. Unlike the Datawarehouse where data is structured and normalised to enable analysis, in a data lake the data is kept unstructured and the machine creates structures on demand based on the analysis that need to perform.

Datawarehouse

Data Warehousing (DW) is a process for collecting and managing data from varied sources to provide meaningful business insights.

A datawarehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting.

Dimensions

Dimensions are a set of information that describe a business fact. For example a transaction could be described by providing exclusive information on the type of transaction (example: sale), region, customer, product, etc.

Information of the same type are grouped into a dimension. For examples all the regions are grouped into a dimension named Geographical Area.

ETL (Extract, Transform and Load)

In computing, extract, transform, load (ETL) is the general procedure of copying data from one or more sources into a destination system which represents the data differently from the source. During an ETL process the data is extracted from the data source, transformed to align with the destination system and then loaded in the destination system.

Financial Planning

The financial planning process is a financial translation of the strategic plan. The aim of a financial plan is to represent how the strategic objectives are achieved in financial terms.

A comprehensive financial plan consolidates into 3 statements: Income Statement, Balance Sheet, and cash-flow statement.

Financial Planning and Analysis (FP&A)

Financial planning and analysis (FP&A) is a fundamental function within an organization which enable businesses to assess their current financial situation and have a structured approach to predicting future financial performance.

FP&A is defined by a structured framework of measurements, data, processes and analytical reports, providing the organization with a primary decision-making tool.

Forecasting

The forecasting process is a business process in which an organisation estimates the future performance of the business based on the actual performance of the previous periods and the expected performance future periods. The forecasting process is usually driven by the definition of a specific forecasting model which fit the organisation business model (BUD+ACT, statistic, Machine Learning).

Forecasting is an important decision-making process because it enables organisations to act on time and take strategic business decisions. (strategic plan revision, financial plan revision, budget revision).

Goal seeking

Goal-seeking is a backward calculation which allows to discover the inputs from a desired output and specific input constrain (min and max value). In budgeting it can be used for example to find the optimal Price per Unit and Sales Volume given a desired amount of Revenues.

KPI

KPI stands for Key Performance Indicator and is a numeric measurement of a specific performance metric. KPIs are essentials in decision making processes as they enable the organisation to represent a wide range of financial performance indicators in readable and comparable measurements.

Financial KPI can be categorised in different groups:

  • Profitability Ratios
  • Profit Measures
  • Cash Flow Measures
  • Capital Market Ratios
  • Efficiency Ratios
  • Liquidity Ratios
  • Solvency Ratios

Machine learning

Machine Learning, also referred as Deep Learning or AI, is an analytical approach where multiple inputs are tested against the outputs and the model is returned as an output.
The advantage of Machine Learning compared to a model driven analysis is that the more input and outputs we have the more accurate the model becomes.
In business planning Machine Learning is becoming a major trend in forecasting because rather than having a fixed approach to forecasting, the self-learning capability of the AI improves the forecasting accuracy as more and more data are collected.

Operational planning

Operational planning is the process of defining a plan to achieve the strategic goals. An operational plan describes milestones, conditions for success, and explains how a strategic plan will be put into operation during a given operational period.

Point Of View (POV)

A point of view is an aggregation of the amounts in a specific dataset for a set of dimensions.

For example, if in our dataset we are recording the sales for each single store (located in different places), a point of view could be a view of the sales by region (aggregation of different stores).

Profitability analysis

Profitability analysis seeks to understand a company’s ability to generate profit. When companies report on sales and profitability data, analysts can then drill into that data by analysing drivers like customer, country, product, number of units, price etc., in order to identify which drivers are yielding profits and which drivers are leaking them.

Common drivers are:

  • business segment
  • product/service type
  • sales channel
  • geographical area
  • customer type
  • individual customer
  • stage in the production process

Each driver is analysed to determine segments that are most profitable and identify those which aren’t. For example: the most profitable customers vs. the least profitable customers. Thorough profitability analysis can provoke positive change within organizations, leading to action based on key insights, like fast responses to changing customer needs. It functions to maximize the effectiveness of the product mix and remedy areas of decreasing profit margins.

Rolling Forecast

The definition of a rolling forecast is a report that uses historical data to predict future numbers continuously over a period of time. Rolling forecasts are often used in financial reporting, supply chain management, planning, and budgeting across every department. The rolling forecast is an essential aid in making sound business decisions.

Rolling forecasts are more agile than static forecasts, which project numbers based on a single time frame, say January through December. Instead, rolling forecasts drop a month as it passes, forecasting the next month automatically. In other words, they allow you to plan continuously over a predetermined time horizon. This way, you are always looking into the future based on the most recent numbers and time frame.

Rolling forecasts are especially useful in today’s tumultuous, digital business environment, which is fast, fluid, and ever-changing. They enable a company to plan, respond, and refocus their efforts quickly and with less impact as market conditions change.

Scenario-based planning

A framework for FP&A processes to define strategic, operational and financial plans based on multiple possible scenarios with different level of probability. To implement a scenario planning, an approach to planning based on key factors / business drivers is required.

Scenario based planning can be represented with the following flowchart:

Scenario Based Planning Sketch

Firstly, the organisation identifies the key factors that drive the business. In a second instance the base scenario is identified (most likely to unfold). In addition, a series of relevant alternative scenarios are identified based on different assumptions. For each of the relevant additional scenarios, financial impacts and mitigating actions are identified in relation to the base scenario. The information generated from the different scenario plans will then support the organisation in the budgeting, forecasting and management reporting processes.

Scorecarding

Scorecarding is an analytical methodology that by using a mix of qualitative and quantitative information it provides a visual representation of corporate performance. The most common type of scorecard is the balanced scorecard.

A balanced scorecard is a strategic management performance metric used to identify and improve various internal business functions and their resulting external outcomes. Balanced scorecards are used to measure and provide feedback to organizations. Data collection is crucial to providing quantitative results as managers and executives gather and interpret the information and use it to make better decisions for the organization.

Sensitivity analysis

A sensitivity analysis is used to assess the impact of a small variation of a single variable (or business driver) over the financial model. For example, it can be used to assess the financial impact of oil change price or the impact of exchange rate on the company performance.

Strategic planning

Strategic planning is an organization’s process of defining its strategy, or direction, and making decisions on allocating its resources to pursue this strategy. The strategic plan outlines the long-term vision of an organization.

What-If Analysis

A what-if analysis is a technique that is used to determine how projected performance is affected by a particular action or event. What-if analysis is used to compare different the financial impact of different actions or set of actions as a decision-making tool to make sure that the decision is supported by a model.

 

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