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Operations management practice: between supply chain & value chain

Is there anything in a business that is not covered by operations management practice? By definition, all of an enterprise’s internal processes are included: supply chain for instance, already a complex subject in its own right, is just part of total operations management practice. One of the few items not ‘officially’ covered is demand forecasting; although even this, because of links to certain product-related variables, often makes its way into operations management discussions. But in such an approach of ‘everything under the sun’, how can analysis and modeling be done for useful, relevant results, instead of ending up with humongous models with no well-defined end points?

The original value chain model from Michael Porter Image source: commons.wikimedia.org

Overall cost-effectiveness and efficiency

Supply chains themselves are already balancing acts that try to achieve global optimization while recognizing that systematic individual optimization is not possible. Logically, operations management practice will therefore also suffer from the same constraint. This is perhaps the answer to how best to model a company’s overall operations – to build model modules for the different activities and departments that make up a business and to put them together to examine business interactions and trade-offs. Some overall models may allow compensatory actions between modules. Others, possibly ones that integrate additional environmental considerations, do not allow results in a certain area to be sacrificed in order to boost results elsewhere.

What is the end goal of operations management practice?

Each module in the collection of activities making up overall operations has its defined end goal. Production wants to make products at the least cost (and preferably with the least ecological impact), finance wants to maximize profit and revenue, and so on. Once again, we can look to the example of supply chain, already a multi-modular entity, for clues about operations in general. The end goals of supply chain are often taken to be customer satisfaction and overall (in the supply chain) profitability. For operations management, the end goal is sometimes defined in terms of customer satisfaction, but may also be taken to be the creation of value, defined in terms of measures of financial profit, market share, brand image and reputation.

The value chain

Incremental creation of value or the Value Chain is also defined by the trade consortium Value Chain Group in its Value Reference Model (VRM). The six business modules that make up this model are R&D, design of products, services, or processes, production, marketing and sales, and distribution.

OR tools for operations management practice

Judgment and experience both play a role in good operations management practice. On the other hand, the operations research field also provides a wide range of tools and techniques to model operations and suggest improvements. In production, processing and queues can be modeled naturally enough using queuing theory, while multi-attribute decision analysis and linear algebra often feature in management of stocks and profitability. As operations become more complex and uncertainty increases, decision support using simulation can help to bring modeling back to manageable proportions.

If you’d like to know how Analytica, the modeling software from Lumina, can help you make smarter, more relevant models for operations management practice, then try the  free edition of Analytica to see what it can do for you.

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Download the free edition of Analytica

The free version of Analytica lets you create and edit models with up to 101 variables, which is pretty substantial since each variable can be a multidimensional array. It also lets you run larger modes in ‘browse mode.’ Learn more about the free edition.

While Analytica doesn’t run on macOS, it does work with Parallels or VMWare through Windows.


    Analytica Cubes Pattern

    Download the free edition of Analytica

    The free version of Analytica lets you create and edit models with up to 101 variables, which is pretty substantial since each variable can be a multidimensional array. It also lets you run larger modes in ‘browse mode.’ Learn more about the free edition.

    While Analytica doesn’t run on macOS, it does work with Parallels or VMWare through Windows.


      Analytica Cubes Pattern