Plenty has been written on the right way to choose the supply chain management technology that best fits your company’s needs, much of it focusing on broad organizational points like defining specific needs and long term business goals. Coming into the IT procurement process with intra-operational buy-in and a well-founded idea of how new technology should integrate into your workflows and key performance indicators (KPIs) is, of course, crucial to finding the right solution, but that’s not the end of the discussion. Once you’ve assessed your specific needs and your short- and long-term goals, how do you evaluate the technology itself?
Although automotive manufacturers have been hearing for years that Big Data is the next big thing, studies often show that executives, not just in automotive but across many different industries, fear that their organizations aren’t ready to take advantage of the new advancements in analytics. Big Data analytics can and will be a huge value-added proposition for companies hoping to stay competitive in the world of Industry 4.0, but it’s true that reaping the benefits of new technological insights often requires significant changes in workflows and IT infrastructure. Luckily, these changes are often not as daunting as they first appear. Here are a few suggestions for getting the most out of your advanced analytics.
Imagine for a moment that you’re an employee at an automotive manufacturing company. Every year of two, the owners create and share a strategic vision for the long-term future with management. Managers, in turn, create shorter-term plans of several months to put the longer-term vision into practice with Sales and Operations Planning (S&OP). As an employee, you manage your day-to-day tasks in accordance with those plans, responding the small crises of the workday with whatever resources and insights are available to you. Perhaps in responding to these situations, you find yourself wishing that there was something to bridge the gap between S&OP and those day-to-day processes. Sales and Operations Execution (S&OE) is that bridge, and it represents the path to the most responsive possible supply chain.
Imagine for a moment that your company is in the businesses of manufacturing parts for both conventional and hybrid vehicles. Based on the demand from your customers over the past year or multiple years, you develop a plan for allocating resources and person-hours to produce the right proportion of hybrid parts to conventional parts based on expected demand. Unexpectedly, a sharp increase in worldwide oil prices triggers a shift in demand away from hybrids and toward conventional automobiles that rely on gasoline. How will your production plans cope with the sudden change? Will your factory floors continue to produce a surplus of hybrid parts while orders for conventional parts go un-filled, or do you have the necessary planning agility to shift production to align with new demand paradigms?
Hopefully, you are in a position to safely assume the latter. But for many complex businesses, rapidly adjusting to demand is a perilously involved tasked, requiring the ability to assess and respond to new circumstances virtually instantaneously. One of the keys to building this level of agility into production processes is the integration of real-time and production planning.
Imagine you’re playing musical chairs. The music starts and stops and your instinct is to rush to the nearest seat before your competitors beat to you to it—but instead of a circle or a row of chairs, the chairs are scattered and hidden around the building at random. No one knows how many chairs there are, and no one is sure how to reset them before the next round begins. Surely this would be a confusing way to play the game, just as it would be a confusing way to run a business. And yet, many companies do just that, keeping real resource allocation hidden within planning siloes and mission critical data obscured by layers of disconnected IT infrastructure. The result is that long term cross-operational planning becomes impossible, with planners stuck in a reactive loop of constantly responding to roadblocks without the ability to be proactive. Integrated planning has long been touted as cost saving solution for complex businesses, one that specifically addresses the break-fix mentality that mires companies in minute-to-minute logistical snafus, but what is it, exactly, and how does it work?
As the world of manufacturing becomes ever more competitive, many are trying to stay ahead of the competition by driving toward a lean supply chain. While this approach is no doubt a boon for identifying potential cost savings and supply chain optimizations, it can often leave companies more vulnerable to supply chain risk. As inefficiencies and redundancies are pared down, manufacturers can become less insulated against possible uncertainty and disruptions. As a result, supply chain managers are now more than ever searching for ways to combat risk and preserve the value-added improvements of their lean supply chains. Even in a market filled with unpredictable externalities, risk management can have a tremendous impact on the bottom line, but for variant-rich industries managing risk is often easier said than done. Let’s take a look at some of the biggest hurdles companies face in combating supply chain risk.
As the year draws to a close, we at flexis look forward to a new year's worth of innovation and insight as we renew our commitment to keeping readers informed on the new challenges and solutions that define the ever-changing world of supply chain management. 2018 promises to be even more exciting than its predecessor and we promise to help our readers stay up to date on the arising trends that may impact their businesses.
Modern day supply chain management is often about finding reductions in costs, expenditures, wasted resources, or misallocations in how raw materials are spread across complex manufacturing networks and value chains. But this worldview often neglects or places little value on the fact that supply chains in and of themselves can be a key driver in affecting growth, increasing revenue, creating business moments, and forging new partner networks or footprint expansion.
But, as with almost anything in modern SCM (supply chain management), such achievements are often more easily discussed than realized. However, that doesn’t mean manufacturing companies don’t have the tools necessary to transform their supply streams from merely a vessel of procurement and product distribution into an important vehicle for engineering long-term, sustainable growth and productivity. Forward-thinking planners and managers can, with relatively minor adjustments to their SCM strategy, create a supply stream with the power to not only drive growth and innovation, but also the capacity to generate real revenue for companies in an increasingly competitive marketplace.
Ask any manufacturing company planner or manager about the most valuable aspect in effective production planning processes and you’ll hear one thing over and over again: data and reporting. In today’s increasingly digitized supply stream, the ability for companies to quickly, accurately, and efficiently gather data and reporting about any number of production elements from material procurement to job allocation is paramount in helping companies manage a streamlined, productive value stream. As the cliche goes: The devil is in the details, and in modern manufacturing those details are the data and reporting.
This is where the development and proliferation of advanced analytics in the manufacturing landscape has given planners and managers a critical value proposition in making best practice decision-making based on the viability of quality reporting. Because advanced analytics relies in large part on the adoption of intelligent technologies or solutions like Industry 4.0, Big Data, and The Internet of Things (IOT), planners and managers have the ability to put large amounts of data and reporting to work to leverage lean manufacturing principles for greater derived value. The addition of Cloud technology and other centralized data storage platforms further makes advanced analytics a critical element of an integrated reporting solution.