Supply chain optimization, following supply chain management (tracks the details) and supply chain planning (creates the execution), makes processes ‘smarter.’ However, optimization has traditionally had a narrower focus and with limited use. For companies that want to use supply chain optimization as an ongoing process to gain significant improvements, here are eight risks to avoid:
Risk #1: Not Integrating Optimization Methods and Tools in a Meaningful Way
Unlike supply chain tools that are continuously run to keep processes moving, optimization tools run separately. For example, optimized transportation logistics on occasion can’t address fast-changing events like the Midwest flooding (March 2019) which impacted driving routes. Without a way to continually optimize and integrate into ongoing processes, optimization is short-lived.
Risk #2: Ignoring Performance Management
Companies investing in optimization as an ongoing process risk achieving true optimization if performance management is missing. With performance management, optimization plans are integrated back into the system, so questions such as “How did the outcome align with the original plan?” or “What shifted and what was the variance?” can be evaluated. Ultimately, what companies want to know is if the optimal plan performed to expectations, and if not, why? With performance management processes in place, real-time insights into the variances allow for necessary adjustments to be made, and help companies achieve the optimal plan.
Risk #3: Keeping it Too Simple
Companies that focus on one segment of the supply chain to minimize costs and “keep it simple” miss out on maximum cost savings and increased profit potential. For example, reducing product costs at one plant with delivery to its intended distribution center fails to optimize the extended supply chain. By not considering differential costs like fluctuating raw material prices or seasonal demand, businesses experience missed opportunities, such as profit-generating opportunities to meet more of a particular demand.
Risk #4: Using an Inflexible Model
Many advanced analytics tools are rigid, requiring businesses to adapt to pre-existing, structured data templates. These types of tool designs can make the business model inaccurate because they conflict with the way the business operates. Creating a replica, or a digital twin, of the business provides a flexible model and simulates the company as it is so the what-if scenarios are feasible. The model should also be extendable by capturing what happens pre- and post-supply chain activities, such as warehousing or covering multiple time periods.
Risk #5: Delaying a Futuristic Mindset
Transformational change is not without growing pains. Humans are hardwired to follow routines that have been proven safe. In the world of advanced analytics, it’s safe thinking that business units identify problems handed to programmers to create algorithms to solve, optimizing the supply chain process. It’s safe thinking that Sales and Marketing will throw a plan with accurate forecasts over the virtual corporate wall to Manufacturing, which will, in turn, produce and meet demand.
Linear thinking is traditional, but the world is moving at a faster pace than ever before. When it comes to many industry verticals, like CPG, businesses run in omni-directions. Groceries may be shopped online, then scheduled for store pickup. With consumers demanding features like convenience and speed, a quick response to supply chain planning and optimization is necessary.
Risk #6: Ignoring Information as a Competitive Advantage
Historically, a product’s features were typically the point of differentiation in a competitive market. However, the $3 trillion digital economy has changed the dynamics since the introduction of the internet some 20-plus years ago.¹ Today, it’s the information velocity or knowledge velocity that provides a competitive advantage. An example of this would be a newly released medical report that promotes a superior ingredient. The company that takes this new information, incorporates it into the best plan and executes the fastest wins. Planning that previously took months can now be done in a day. However, this knowledge requires a new mindset to champion supply chain optimization and make smarter decisions faster.
Risk #7: Not Engaging Management Consulting Firms for Change Management
The best supply chain optimization tool can be diminished without effective change management expertise which often lay with large management consulting firms. The advantages these firms can provide include:
- Sample project plans showing the change management components
- Processes to help transform the existing business processes
- Practice runs to ensure new processes work
- Performance metrics to show outcomes and variances
- Ongoing monitoring to manage changes that go awry, understanding why and how to get them back on track
Note of caution: Firms providing change management should deliver a balanced approach to the change management discipline as not to lose sight on the tool’s capabilities, which leads us to the final risk about the human factor.
Risk #8: Forgetting the Human Factor
Human nature is a mainstay in supply chain optimization. From champion to laggard, people will almost always internalize “what’s in it for me?” at some point throughout the process.
A strong buy-in from the top keeps the momentum for optimization going. On the contrary, some stakeholders may experience their traditional roles become less defined, collaborating with other functions. Along with roles, compensation incentives can be wiped out with optimal plans of action. Like the organization, individuals will want to adapt to a new way of thinking. In return, supply chain practitioners will gain more confidence and intelligence; some will adapt and change, and others will go.
Complexity is increasing at a rapid rate, and poor decisions are the cost. No matter the number of risks, the rewards of supply chain optimization will drive smarter decisions faster.
¹The Digital Economy In 5 Minutes, June 16, 2016, Forbes.
