But what makes the difference between a successful effort at operational planning and optimization and a failed effort? To look at this, we’re going to define operational planning and explain how it differs from other forms of planning, such as strategic planning. We’ll also talk about six key factors that will help make operational planning and optimization an unmitigated success together with the role of prescriptive analytics.
What Is Operational Planning?
An operational plan is the plan for the current budget period. In business terms, its horizon is from the present to the end of the current financial year. Operational planning represents the concrete plans and actions required to implement the business plan, such as sales and production volumes, selling margins, turnover and profitability. It also includes the capital and investment required to maintain, upgrade and add to production and sales capabilities in terms of the organization’s strategic plan.
Definition of Operational Planning
Operational planning is the process used to determine the activities required of an organization as a whole as well as of individual functions or departments to implement the short-term business plan. While operational planning is a term that’s widely used, within businesses it is generally confined to represent those activities required to ensure the organization meets its current targets and budgets.
Isn’t That the Same as Strategic Planning?
No, it is not. When considering what the difference between strategic and operational planning is, the most important divergence is that operational planning is tangible and real, while strategic planning represents a theoretical view of the future. In a strategic plan, the organization sets out a vision for the future using various techniques such as a SWOT analysis (Strengths, Weaknesses, Opportunities and Threats) and determines the broad initiatives necessary to take the organization there.
While the strategic plan sets out the vision, the operation plan defines short-term steps that need to be taken in the next budget period to start implementing the strategic plan as well as those needed to manage day-to-day business activities.
Six Key Factors for Mastering Operational Planning
There are several factors that have been found to be beneficial in terms of effective operational planning. These include access to reliable data, holistic planning, developing context, evaluating organizational value, a common understanding of terms and measurable goals.
Reliable data
Worthwhile operational planning and optimization relies upon a rock-solid foundation of data. To determine appropriate initiatives, you need a software platform that can collect relevant data of activities that create or consume value. While much is available from ERP software, some isn’t. Data should be presented in an appropriate and usable format so it can facilitate operation planning.
Integrated planning
Effective operational planning demands an integrated approach that considers planning and optimization at every level of the company. Changes at the operational level ultimately affect tactics and strategies across the company. A failure to eliminate silos or to account for ripple effects can cripple optimization efforts, leading to minimal improvement or even losses.
Older methods of optimization — those dependent upon extrapolating from a single point — have historically underperformed; especially those that fail to consider inputs from all functional departments. By approaching optimization and planning holistically, as well as measuring everything in appropriate financial terms, rather than in units, it’s possible to achieve real, lasting gains.
Understanding context
When trying to understand what is operational planning, it’s not enough to look at internal changes only in terms of how they affect the organization. Nothing exists in a vacuum, and it’s important to understand how internal and external changes position your company in terms of your competition, markets and among the consumers who buy your products. Failure to account for this wider context in operational planning often results in short-sighted plans that are ineffective and optimization processes that achieve nothing. Taking context into account helps ensure operational planning holds up in the real world.
Evaluating value
To move forward with an operational plan, it’s essential to have a thorough understanding of the total value the different aspects of your operations hold. While it’s easy to evaluate the organization’s overall turnover, margin and profit, it’s another thing to measure these metrics at the functional and product level. In addition, value isn’t always measured in monetary terms; consider goodwill arising from your customer base as well as the importance of maintaining legacy solutions if they offer value and help retain customers.
It’s essential to use all such data using advanced analytics and to determine its value across your operations. Only then is it possible to really understand how changes and initiatives will strengthen or weaken your company’s position.
Use consistent definitions
Nailing down terminology and understanding the various systems, plans, tools and metrics associated with operations is crucial to the operational planning process. Inconsistencies in how different teams understand terms, how they’re defined within your tools and how you talk about them all contribute to inefficiencies and misunderstandings. To move forward with operational planning and optimization, your people and systems all need to communicate in the same language.
Have testable goals
Operational planning and optimization processes should aim to achieve specific and achievable goals. Vague goals that aren’t measurable are ultimately useless for the endeavor. To make optimization efforts succeed, goals should be defined in a manner you can measure and test for. These include specifying the financial targets, sales values and production achievements you want to hit. As you see the organization moving toward or away from these goals, you can make rational, reasoned decisions about how to progress.
Operational Planning Processes
There are numerous operational planning examples available, including those based entirely on manual processes and others that use advanced analytics to arrive at data-driven solutions. Asking the right questions is an important aspect of operational planning processes, and having an appropriate operational planning framework helps ensure all aspects are considered. This requirement applies to both manual- and software-driven processes. It’s essential to understand the organization’s goals and long-term plans before initiating the operational planning process.
Using Prescriptive Analytics to Optimize Operational Planning
While most C-level executives have a good understanding of where they want their organization to go, knowing how to do that is an entirely a different matter. All businesses are complex, and it’s difficult to analyze and weigh up multiple factors and constraints to arrive at rational operational planning decisions without support from advanced analytics software such as prescriptive analytics.
By basing operational planning and optimization on a foundation of prescriptive analytics, you’re building a reliable, consistent platform for improving your company. Such a platform allows you to accurately model the business, and the platform’s optimization capabilities help determine outcomes of operational planning decisions. By making data-driven decisions, you can determine how to enhance operational efficiency and avoid traditional pitfalls inherent in manual optimization processes. You won’t cling to waste, won’t hesitate to invest in useful tools and improvements and won’t make ill-advised “gut decisions.”
Benefits of Data-Driven Operational Planning Process
The six key factors above help organizations come to grips with the basics of operational planning processes. However, they don’t solve all problems, nor are they sufficient on their own. To really succeed with operational planning, it’s crucial to tap into the capabilities of advanced analytics to determine which, of several possible routes and decisions, is best.
