Prescriptive Analytics - Impact on Finance
Finance Professionals have used forecasts and budgets to compare what is expected to occur vs what happened. The undertaking requires the application of sound judgment from information provided by business units within the organisation.
Understanding why an event happened can be as important as predicting what is expected to happen. Traditional budget and forecasting methods used may not have taken into account patterns based on internal and external factors.
The use of information technology has allowed information to be collected, cross-referenced, and categorised based on specific data-points. Information sources include the use of databases, statistical formulas, as well as Client Resource Management (CRM) in addition to traditional enterprise resource systems (ERP).
Ensuring Reliable Descriptive Analytics
For an organisation to undertake predictive and prescriptive analytics, it needs to provide that information in its descriptive analytics, that is analytics based on what has already occurred is reliable both regarding financial and non-financial information. Without a stable foundation, an organisation cannot build upon such insights for future data insights.
Consider various data-points such as financial, nonfinancial information including customer insights, and general market trends. Integrating information from different sources can be used to create dashboards that are unique, and can be tailored to the particular business unit to enhance the reporting Key Performance Indicators (KPI). If the underlying information which the KPIs is based is not reliable, timely, and relevant, the analytics will have less value.
Different Types of Analytics – Overview
There are three basic types of analytics commonly used. From a strategic standpoint, it is important to understand. Each class provides insight into the operations of the organisation.
Descriptive Analytics – is the traditional analytics undertaken by organisations.
• What has occurred? It allows organisations to understand what happened and why. It can provide a foundation for future potential outcomes.
• Benchmarking, and KPI analysis uses this information to measure the results of performance both in financial, and non-financial terms.
Predictive Analytics
• What may occur? Using statistical algorithms organisations predict what may happen in the future based on probabilities.
• It combines information from various sources such as from ERP, SCM, and POS systems to identify possible customer patterns to identify trends to forecast sales, determine required inventory levels, as well as assist in financial projections.
Prescriptive Analytics
• Quantifies the effect of decisions in the future to advise determine likely outcomes.
• It goes a step further than Predictive Analytics in that it focuses on why an event may occur.
• It uses a combination of historical analytics, combined with business insights, and statistical modelling to determine future outcomes including why it will happen.
Complexity of Predictive and Prescriptive Analytics
Predictive and Prescriptive Analytics are complex and require information from various data-points. It integrates information from both financial and non-financial, and historical, as well as the integration of real-time information. The use of statistical formulas, and perhaps the use of analytics software to manage the various sources of information can increase predictability.
Before Predictive or Prescriptive Analytics can be used it is important to ensure that Descriptive Analytics is functional, accurate, understood and used throughout the organisation. Introducing a new analytics system when not fully utilising foundational systems will not provide any tangible benefits to the organisation.
Ensuring the relevance, reliability, and timeliness of information is critical for a Finance Business Partner, it is also important when analysing value-added information. As with financial analysis ensuring the integrity of information from Predictive, and Prescriptive Analytics is important from the various sources including the CRM, ERP, and other sources used to mine information.
Transitioning from Descriptive Analytics to Prescriptive Analytics
Information collected in various systems such as ERP systems has provided an overview of what has occurred including explaining anomalies. Traditional descriptive analytics lays the foundation for future planning with predictive and prescriptive analytics. To do such information from various information touch points such customer taste, preferences, market segment information can be used provide forward-looking insight for an organisation to take a strategic course of action.
A traditional information system is based on what has already occurred and provides an understanding of customer tastes and preferences. It can also identify cause and effects for events that have had a financial impact. Multi-divisional Organizational can have complex decision-making decisions including multiple product lines, cross-selling, and up-selling initiatives that can be complex and unique requirements of the client.
Prescriptive Analytics Ability to Transform Financial Analytics
Prescriptive analytics can provide forward-looking information by making such as using what-if analysis and determining the impact on sales, and marketing, and operations.
It clarifies decision making to understand the trade-offs and consequences. Combining information from various touch-points allows for a better understanding of complex operations. Internal business units will increasingly need to collaborate not only regarding information analytics software but also discussions to understand the full impact of a decision throughout the organisation.
Prescriptive Analytics can improve the accuracy of decision-making by including the cause and impact of various decisions on other business units in the organisation. With robust information, organisations can better plan their sales and marketing, supply-chain management, other resource requirements, and determine the financial impact accordingly. Cross-collaboration with business units is required to ensure goal congruence towards the strategic aims of the organisation.
Prescriptive Analytics – Transforming decision making
Prescriptive analytics can be used to determine demand and optimise supply chain and logistic requirements thus allowing for proactive changes. Healthcare organisations can use such analytics to manage patient care including case costing decision support analysis. The potential impact goes beyond just marketing, sales, and finance.
The amount of data that is available for analytics will continue to increase as information system tools become sophisticated. The challenge faced is distinguishing useful information from outlying information that can distract from the core decisions. Initiatives may include the combination the use of statistics, forecasts, and marketing information to align information from the various organisation segments. As an example, Inventory levels are affected by sales and marketing initiatives; also, non-moving inventory has associated carrying costs. With the value-added information, the organisation can optimise operating cash-flow.
Addressing Financial Compliance
Prescriptive Analytics can allow an organisation to understand better customer patterns which can, for example, detect potential money laundering by monitoring unusual activity before it has a financial impact. It can also be used to ensure regulatory compliance within the industry and that of the government.
Impact on Various Business Units – Overview
Sales and Marketing – Prescriptive Analytics allows for an understanding of potential sales demand with greater certainty. With traditional analytics, organisations used best estimates to determine what application may occur and plan accordingly. As such at times organisations may have over or underestimated demand which affects not only sales forecasts, but inventory, and cash flow management accordingly.
Supply Chain Management – Organizations can plan the production and distribution of their products accordingly to reduce potential bottlenecks in production. Prescriptive analytics can potentially benefit organisations if the usage is extended beyond the sales and marketing department to include other areas if deployed strategically.
Logistics – Supply Chain may need to rebalance their distribution according to the demand of their products or based on the availability of a product. With an understanding of which products timing requirements organisations can route, or reroute shipments taking to account cost, demand, and optimal lead-time.
Finance – It is important for organisations to budget and forecast based on information that is as accurate as possible by partnering Finance Business Partner to use such analytics to project and analyse financial and operational information based on the organisational strategy. Prescriptive Analytics can provide the necessary tools to allow finance to collect, determine which information should be combined from other organisational business partners to ensure goal congruence with the strategic aims of the organisation.
Sources of Non-Financial Information
The Finance Business Partner will need to undertake value-added analytics that is strategic by partnering with business units in for prescriptive analytics. The challenge will be to obtaining such information from the business units.
Ensuring the accuracy of such information is important. Also, a clear understanding of the composition of the information, and the ability to removing any external information to remain focused in the decision-making process.
Budgeting and Forecasting
With the movement towards Zero Based Budgeting (ZBB) organisations are being challenged to manage their budgets and forecasts better. The challenge faced is to produce more accurate budgets that factor in sales demand, and other external factors. The use of rolling budgets requires up to date information will increasingly become important.
With such information, the Finance Business Partner can deliver decision-support analytics to the organisation that is more relevant, and meaningful based on the strategic information. As well through the use of rolling budgets and forecasts, it can be adjusted as the business environment changes.
Support Decision-Based What-If-Analysis
Finance is a vital link to providing decision-based what-if analysis. Combining information from various areas such as resource constraints, and opportunities an organisation can gain better align its operations. Cash flow projects through the use of forwarding-looking statements that better reflect the current, and future expectations.
The Finance Business Partner will need to get buy-in from the other business units. Communication and an open dialogue are necessary to ensure that existing descriptive analytics, as well as predictive, and prescriptive analytics is useful.
Conclusion
Finance and other business units should employ technology strategies that can qualify, and quantify the impacts of decisions to maximise shareholder value, or value-for-money in the case of government or not for profit organisations.
About the author:
Hanif Shamji, MBA, CPA, CGA is a Finance Business Partner / Sr. Financial Analyst with an information technology background, experienced in several industries.
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