Chief Executive Officer
I’m here to help you set your business strategy, identify your goals, and define your plan to achieve them.
Budgetary planning is about planning to understand the best way to spend resources. This is not a new concept, the earliest examples of budgeting practices date back as far as one hundred years, when large industrial organisations introduced the formal use of calculation tools to manage cash flows and costs. During the 1960s, budgetary planning was also used for incentive systems to guide and assess management performance.
Today, budgetary planning is a universally followed practice and has become a standard tool in organisations because of its importance in monitoring and maximising value, becoming a cornerstone of management control. Budgetary planning can therefore be a tool for benchmarking, communicating, monitoring and assessing your company’s performance.
Budgetary planning essentially involves building a spending plan, which can be used to make strategic business decisions and guide organisational changes across departments. With accurate budgetary planning, your company’s stakeholders can get a more solid idea of the organisation’s current and future financial position and needs.
Budgetary planning generally involves three steps:
Budgetary planning allocates economic resources through a decision-making process, so by making rational decisions, investment returns can be improved. Here, the role of artificial intelligence can be crucial, because its potential provides the opportunity to optimise allocation processes. Let’s find out how.
Let’s start with benchmarking, which can be improved by using text analysis techniques, i.e. the area of AI called natural language processing (NLP). By extracting information from text, structured data of any kind can be gleaned. Here is where algorithms can help your organisation better identify expectations and needs to support decision-making. On the basis of the information obtained, a comparison can be made to understand the relationships and assess the target setting for future decisions (predictive analysis).
A further opportunity offered by AI is the identification of cause-effect relationships in value chains. New insights can be uncovered that can support managers in marketing and finance to better measure return on investment. In addition, optimised spending patterns can be built. In practice, for example, this can mean being able to identify the ideal number of sales professionals or predict customers’ purchasing decisions.
Despite the obvious opportunities offered in budgeting processes, AI also poses challenges and limitations that need to be considered. Gartner identified and described three main obstacles:
These are all obstacles that can be overcome with appropriate measures. To overcome the first, Gartner recommends validating AI outputs in a broader group of different perspectives. For example, the IT team can help validate the artificial intelligence model’s ability to identify anomalies or exceptions that could deteriorate results.
To deal with bias, the advice is to ensure that data sets are diverse so that staff can perform correlations and comparative analyses and identify right and wrong answers when AI produces a prediction or predicts business performance, thereby reducing risk.
Finally, to counter employees’ fear of being replaced by artificial intelligence in their roles, you need to develop a digital culture in your company to integrate AI with human judgement. More digitally capable personnel better accept AI in the workplace and this improves decision-making and process efficiency through artificial intelligence itself.