During one of your college economics or business classes, you may have heard the term “discussed opportunity cost”. What it means, essentially, is to create the “pros and cons” of a decision and weigh the outcomes in terms of short and long-term opportunities. What’s the cost of different opportunities? In college, you could apply this to theory quite easily…should I study for an exam or hang out with friends (I will leave this as a rhetorical question)?
As a business leader, applying opportunity cost is simple in theory yet extraordinarily complex in reality, especially when applied to making decisions that impact production and the supply chain. Today, to make smarter decisions in a more difficult business environment, we rely on advanced analytics software to calculate tremendous amounts of variables to have a fact or data-centric evaluation to define the opportunity cost.
Getting to this state of advanced analytics doesn’t happen overnight, and it requires organizations to embrace a culture of operating in a “lean” or “agile” manner when it comes to production and distribution. The data is present and available to analyze, but for some organizations, there’s simply too much information that’s often difficult to access. Today’s ERP systems can help make the transition from manual spreadsheets and log books to automated dashboards and reports, enabling teams to experience impressive ROI from sales histories, inventory, and supply chain and logistics.
To gauge how mature your organization ranks along the analytics spectrum, here are a few instances of enterprise operations that require a high level of analytical maturity.
Lean inventory is a practice that optimizes the levels of raw materials required in the production process so that materials arrive “just in time” to support the production of goods. Once produced, goods are distributed with minimal aging. Too much material and finished goods sitting in storage can limit other business opportunities by locking up liquid capital. Too little material stymies productivity. Achieving this “just in time” sweet spot not only optimizes the production process, but also increases the velocity of business. Inertial constraints of process are streamlined.
Lean Supply Chain
The supply chain is a great opportunity to use analytic tools to find efficiencies (or inefficiencies). A lean supply chain is the optimization of several systems and processes. At the center is an ERP system that gathers and analyzes data from a variety of sources, and through advanced predictive engines and artificial intelligence, provides the organization with a holistic look at data-supported business scenarios, or the opportunity cost. Data such as customer sales history, current demand, environmental trends and predictions and a host of others enable mature organizations to run “what if” scenarios to prepare plans to adjust capacity and productivity levels.
Disruption is inevitable and no industry is immune. It also comes in many forms and can be both internal, such as a merger or acquisition, and external, such as an act of nature. Unfortunately, organizations on the lower maturity end of the spectrum cannot overcome disruptive forces in the marketplace. Timing for products to in the marketplace is absolutely critical to the success of the business. If a production run takes too long, if a distributor loses drivers, if a storm snarls traffic or flight patterns for days…all of these things can present significant risks for low mature companies.
Lean or agile are trendy terms that are often associated with manufacturing or software development, but the philosophy can be applied universally. Highly mature organizations embrace a culture of being lean or agile. There is organizational aptitude to analyze systems and data and embrace the technical tools required to support data-centric cost decision-making. Today’s business leaders should embrace analytics to ensure tomorrow’s ROI.
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