In a constantly changing business environment, the ability to adapt to changing trends and implement new strategies quickly is of paramount importance today. Economic pressures, industry changes, regulatory pressures, supply uncertainties, and changes in consumer preference can all affect a business' ability to sell its products or services. Managing these business scenarios effectively will protect organizations from plummeting revenue and profits. According to a report by Business Continuity Institute, the consequences of unplanned events lead to significant loss of productivity, increased cost of working and loss of revenue. Dynamic business strategies help a business with responding appropriately to changes that may represent both potential opportunities and new threats to its operations.
Scenario analysis along with the ‘what-if’ simulation capability is one such strong management tool designed to deal with business uncertainties. Scenario analysis can be defined as a decision-making tool that is useful in assessing how a situation can turn out and how different actions will affect its outcome. Scenario analysis is the exercise of considering unexpected events, occurrences, and changes by asking the questions ‘what might happen?’ and ‘what could we do?’ Scenario analysis is an important part of the organization’s risk management strategy that involves understanding the plausible events that can affect the business and their effect on its strategy, operations, and financial health. This method helps decision makers make informed choices. It can help establish the best-case and worst-case scenarios, and sometimes expose those outcomes that may have been overlooked.
To sum up the above points, these are the main business drivers that make organizations to make use of the scenario analysis approach:
- Building a competitive advantage in terms of responsiveness and flexibility
- Better management of market and operational risks
- Structured and collaborative process of decision making
- Higher alignment between strategy and execution
- Enhanced understanding of the drivers and assumptions impacting the business and the relationship among these variables
Scenario analysis can be employed widely across the organization e.g. analyzing the impact of a disruption on the supply and identification of alternatives to meet the customer demand, safety stock – service level trade off scenarios, impact of macroeconomic conditions on the raw material spend, impact on revenue of the organization with the introduction of new product etc.
Let us deep dive into the example of supply disruption to understand how scenario modelling can help assess the suitability of the different alternatives.
Business Scenario: A company has invested in the capability to continuously monitor the performance data of the machines spread across various plants. Application of predictive analytics to that data predicts that one of the critical machines in plant 1 may breakdown in the next few months. The maintenance department will work on the machine for proactive maintenance so the machine will not be available for some time during the next month. On analysis, it was found out production of product A will be hit during that period. The company is evaluating different options to choose the best among these:
Scenario 1: Prebuild inventory of product A in the current month for next month in the plant 1
Scenario 2: Offload production of product A to another plant 2 for that month
Scenario 3: Source from a third party vendor
The supply plan is sourced from the planning system, budgeted forecasts from the business planning system, and the different costs such as per unit cost, fixed production, fixed overhead costs etc. from the production system are pulled for scenario planning. The analysis is shown below:
|Product A||Month (M)||M+1||M+2||M+3||M+4|
|Baseline Scenario||Unit Cost, Fixed production & Overhead cost||Supply(Plant 1)||1000||1500||2000||1500||1500|
|Scenario 1||Unit Cost, Fixed production, Overhead cost, Inventory holding cost||Supply(Plant 1)
|Scenario 2||Unit Cost, Fixed production & Overhead cost||Supply (Plant 2)||0||1500||0||0||0|
|Scenario 3||Unit Cost (higher than the unit cost if built in own plants)||Supply (3rd party Vendor)||0||1500||0||0||0|
The cost of the supply for each scenario is calculated and the profitability for each scenario is found out by subtracting costs from the revenue for the planning horizon. Profitability values are compared against each other and against the budgeted value. Planners can get a fair, data supported assessment of the different scenarios and choose the best alternative. Planners can also perform the ‘what-if’ analysis e.g. they can find the unit cost that makes the profitability of scenario 3 equal to that of the best scenario and can use this as the base value for negotiating further with that particular third party vendor or different vendors.
This methodology is a structured approach to leverage the data as an asset. However, there are certain challenges in making best use of this technique. Some of the key challenges are:
- Siloed processes and data inconsistencies leading to fragmented and unstructured decision making.
- Lack of collaboration among the stakeholders involved in decision-making.
- Limitations in the technical capabilities used to handle exponentially high volume of data and handle multiple scenarios having multiple dimensions on the fly.
- Lack of comprehensive representation of the results of scenario analysis available for the decision makers.
Organizations can overcome these challenges with having digital at the core. This ensures high collaboration and visibility across the manufacturing value chain leading to single version of data and well-integrated processes. The minimal data discrepancies results in more accurate decision-making scenarios. This helps with integrating the data from multiple enterprise systems and real time data coming from the IoT devices as well. This should be supported by the capability to dynamically build scenarios on the fly, a collaborative platform to allow multiple stakeholders work on the scenarios effectively and advanced analytics.
Users can create, edit, share, compare, and delete scenarios on this platform. The platform provides the ability to build models and plan across multiple dimensions such as time, hierarchies etc. The different scenarios are presented in a comprehensive way in the form of dashboard reports that are used for sharing insights with the different stakeholders.
A scenario dashboard allows users to modify levers associated with the business (costs, capacity, demand, products) as well as their objectives in terms of business strategy (e.g. maximize revenue, maximize net income, minimize inventory). This provides a summarized view of the scenario analysis and helps in faster decision making. This provides an edge to the organizations when it comes to the linking up of strategic and operational plans based on different possibilities. Finally, the platform should provide an ability to orchestrate chosen scenarios back into execution through proper integration with the relevant systems.
There can be arguments on “why do organizations need such platforms when the same ‘what-if’ scenarios can be modelled in spreadsheet tools?” The answer lies in the fact that spreadsheet-based modelling makes for an extremely tedious and lengthy process due to the complexity of calculations and the need to track and compare multiple scenarios. It is also prone to manual errors and can result in decreased accuracy of any analysis. According to The Wall Street Journal’s MarketWatch, nearly 90% of spreadsheets contain errors. As a result, such platforms can add a competitive advantage.
Thus, the ‘what-if’ scenario analysis adds to the capabilities of any organization. Every business decision involves a degree of risk, and managing that risk appropriately can help a business remain competitive and increase growth. By analyzing several “what-if” scenarios, companies can significantly reduce the potential risk of business decisions by gaining a deeper understanding of how each decision will affect the overall company financials. Having a Plan-B or a Plan-C helps in better managing contingencies. This approach protects against the groupthink problems as the group can now take decisions with clear objectivity.
Let us summarize the benefits of the what-if scenario analysis:
- Reduces the decision-making cycle time
- Makes organizations responsive and flexible
- Improved profitability
- Improved operational metrics
- Improved risk management