Big Ass Fans Turns to Smart Software as Demand Heats Up

Big Ass Fans is the best-selling big fan manufacturer in the world, delivering comfort to spaces where comfort seems impossible.  BAF had a problem:  how to reliably plan production to meet demand.  BAF was experiencing a gap between bookings forecasts vs. shipments, and this was impacting revenue and customer satisfaction.  BAF turned to Smart Software for help.

BAF’s Supply Chain Manager took the lead to flesh out their planning needs and methodically address them.  In his words, “it came down to fundamentals. Our planning process needed to be data driven, collaborative, and continually improved by assessing and enhancing our monthly forecasting process.”

A big part of this was bringing the disparate planning processes together.  Product managers produce monthly demand forecasts, while the operations team forecasts shipments and associated material requirements.  BAF needed a tighter, data-driven process that combines advanced analytics with team collaboration.  This would need to address seasonality, a huge factor driving demand fluctuations, incorporate input from international as well as US markets, and capture the impact of market promotions.

BAF’s Customer Service Director and S&OP Team Lead explained what this means.  “Now we have one unified, global process, one shared business view that provides the framework for all of our cross-business planning.”  She likens it to having one source for the truth.  “Every month the entire team sees updated orders and shipments and can compare forecast against actual performance.  Individual managers view business through their required  business lens – by product line or service, region, international geography, channel, customer, you name it.”

“This is enabling technology that makes us better,” she continued.  “Smart IP&O is, among other things, the vehicle for our monthly SIOP process.  We review our own business segments then convene as a group, consider results to date, the impact of promotions, events and seasonality, and agree on our consensus plan going forward.  This is an invaluable process, enabling manufacturing to stay ahead of demand and deliver what our customers need, when they need it.”

BAF Case Study SIOP planning Inventory Warehouse

“Smart Inventory Planning & Optimization is the critical tool we use to manage our forecasts across a large and dynamic set of Products/Parts, multi-national sites, and complex supply chains,” added the Supply Chain Manager.  “The ability of the software to provide a statistical forecast as baseline, allow adjustments by various subject matter experts, each recorded as ‘snapshots’ for consensus building and later use in accuracy/improvement efforts, then ultimately feed the forecast data directly into our Material Requirements Planning software is central to our S&OP process.”

BAF has refined its monthly Sales, Inventory and Operations Planning process utilizing Smart Demand Planner, Smart’s collaborative forecasting and demand planning application. Smart’s API based bi-directional integration with BAF’s Epicor Kinetic ERP automatically captures all order and shipment data that in turn drives the creation of monthly statistical forecasts.  Through its monthly SIOP process, BAF product managers produce initial forecasts, share these with sales managers who can suggest adjustments, and bring together consensus plans across 25 product lines for monthly review, adjustment, and presentation to the executive team as the company’s rolling 12-month plan.

The team credits Smart Demand Planner with providing a thorough and accurate forecast of future demand that is central to BAF’s monthly SIOP process.  BAF extended Smart’s utilization to its international offices, where subject matter experts manage their own forecasts.  “Within Smart they can manage both demand forecasts that key on their shipments to local end users and supply forecasts based on their purchase history as key customers to BAF-US.  This significantly enhances our global demand view and has improved forecast accuracy.”

About Smart Software:

Founded in 1981, Smart Software, Inc. is a leader in providing businesses with enterprise-wide demand forecasting, planning, and inventory optimization solutions.  Smart Software’s demand forecasting and inventory optimization solutions have helped thousands of users worldwide, including customers such as Disney, Arizona Public Service, and Ameren. Smart’s Inventory Planning & Optimization Platform, Smart IP&O, provides demand planners the tools to handle sales seasonality, promotions, new and aging products, multi-dimensional hierarchies, and intermittently demanded service parts and capital goods items. It also provides inventory managers with accurate estimates of the optimal inventory and safety stock required to meet future orders and achieve desired service levels.  Smart Software is headquartered in Belmont, Massachusetts.  Learn more at www.smartcorp.com.

BAF Case Study SIOP planning manufacturing

About Big Ass Fans

At Big Ass Fans, we are driven by our mission to create safer, healthier, more productive environments worldwide. What started as a big idea in airflow became a revolution and is now best practice for designers, managers, and business owners across every imaginable industry and application. Today, our products are proudly spinning and serving more than 80 percent of the Fortune 500 in 175 countries. From factories to homes and everywhere in between, Big Ass Fans delivers comfort, style, and energy savings to make life more enjoyable. With more than 235 awards, 350 patents, an experiment on the International Space Station and the only HVLS Research & Design lab in the world, we go big every day.

Procon Pumps Uses Smart Demand Planner to Keep Business Flowing

Introduction:
Procon, an industry leading pump manufacturer, uses Smart IP&O’s demand planning and inventory optimization modules from Smart Software to make sure they have the products their customers need, when they need them.  You might not have heard of their products, but if you’ve ever eaten at McDonalds or sipped a coffee at Starbucks, you have been served by Procon.  Procon’s broad portfolio of over 7,000 SKUs is supplied to more than 70 countries worldwide through their direct sales channel and an extensive distributor network.  Procon operates manufacturing facilities in the US, Mexico, Ireland, and through a licensed manufacturing partner in Japan.  We spoke with Procon’s Shankar Suman, Director of Sales, and Emer Horan, Global Supply Chain Manager, to learn more.

The Challenge
If Procon cannot ship a required product, their customers cannot ship theirs.  Accurate forecasting is a key driver of supply chain success and customer satisfaction. Procon’s monthly planning establishes the consensus demand plan that drives procurement, production, and stocking policies.  But they found they had a gap between sales and procurement, which historically led to missed deliveries and excess inventory.  What Procon needed was a robust demand forecasting and inventory optimization tool that was easy to use, enabled collaborative planning with their sales team and partners, and integrated with their  ERP system to drive procurement and production planning.

The Solution:
They found this in Smart IP&O,  web-based platform for statistical forecasting, demand planning, and inventory optimization.

  • Shankar Suman cited a broad mix of capabilities that convinced them to utilize Smart. Chief among them were:
  •   Smart Demand Planner supports the easy, orchestrated flow of information that yields an accurate consensus plan.  Presenting performance history and statistical forecast by product, territory, and partner, SDP provide the sales team with perspective that they can complement – adjusting for expected opportunities or demand shifts.
  • Forecast accuracy. Smart is an industry leader in statistical analytics, leveraging innovations developed over its forty-plus year history.  This combined with robust forecast vs. actuals analysis helps Procon continually improve the quality of their forecasts.
  • Transparent connectivity with Procon’s enterprise software, Epicor Kinetic. Daily sales and shipment data are automatically pulled into the Smart platform, fueling Smart’s forecasting engine, and results are easily pushed back to the ERP (MRP) via an API based integration to drive ordering and production planning.

Results:
Emer Horan explained how this plays out over the course of each month.   Emer provides forecasts for each of their five sales managers, they meet to compare statistical and sales forecasts, and agree on a revised 12-month consensus plan.  The sales managers have a good sense for the top accounts that represent 80% of revenue, often including direct input from customers themselves, and the statistical forecast fills in the gaps.  Next month they use the forecast vs. actual analytics to help improve accuracy, then repeat the process.

“Our sales team is incentivized to maintain and improve sales forecast accuracy,” said Emer, “and we have the tools to help them succeed.  This not only ensures optimal inventory levels but also contributes to improved on-time delivery and higher customer satisfaction.”

“Our journey with Smart Software has been quite remarkable,” added Shankar. “We began with an initial idea of the functionality and interface, and it has continually evolved from there. The Smart team has shown tremendous support and patience with our scope changes, delivering the product exactly the way we needed and wanted it.  We have been using Smart for over three years now, and this journey is ongoing. We continue to receive excellent support from the Smart team and truly enjoy working with them.”

 

 

Demand Forecasting in a “Build to Order” Company

The Smart Forecaster

Pursuing best practices in demand planning,

forecasting and inventory optimization

We often come into contact with potential customers who claim that they cannot use a forecasting system since they are a “build-to-order” manufacturing operation. I find this a puzzling perspective, because whatever these organizations build requires lower level raw materials or intermediate goods. If those lower level inputs are not available when an order for the finished good is received, the order cannot be built. Consequently, the order could be canceled and the associated revenue lost.

I agree that in such an environment, forecasting the finished good is not always possible or particularly helpful. Sometimes it’s helpful, but not sufficient. In any case, it is critical to make sure that the underlying raw materials and intermediate goods that go into the finished good are available. Demand for these can certainly be forecasted.

The organization’s goal would be to maintain service level inventories for these intermediate goods that are high but not unaffordable. Planners will need to set optimal stocking levels for these materials, balancing service level requirements against available budget. Since a given intermediate good could serve as an input to more than one finished good, the volatility of the demand for the intermediate good would be less than the volatility of the demand for a specific finished good. Hence, the safety stocks necessary to keep high service level inventories of the intermediate goods would be relatively lean.

Three companies, all users of SmartForecasts, serve as interesting examples. The first is a chemical company, Bedoukian Research, which manufactures custom chemicals for various clients. Each of these “finished goods” is a unique combination of intermediate chemical compounds. Bedoukian begins its demand planning with a finished goods forecast, which drives the production schedule and allocation of essential production resources. This requires exercising considerable judgment, as finished goods demand changes dynamically.

Once these finished good forecasts are created, raw material requirements can be estimated via a bill of material disaggregation. Bedoukian combines these results with safety stock estimates, based on actual utilization rates and service level objectives to be achieved, to generate the complete, service level-driven forecast for raw materials. This has allowed Bedoukian meet its production requirements with significantly less inventory.

The second company manufactures the internal components for mobile phones, where finished goods are specialized combinations of these components. For example, an order may call for a certain number of phones with unique labels on the case. This is the finished good for this order. Everything that goes into that order, except for the label, is built out of standard components. Again, SmartForecasts will be used to keep lean, high service level inventories of the components. This company thought that the only way to manage component inventories was via bill of material aggregations. They are now looking at the actual utilization rate for the components and setting much leaner inventories while maintaining high component availability.

A third company, NKK Switches, which explored this topic in their recent webinar (see CFO Bud Schultz’ guest blog post), considered their products to be “unforecastable”. You can read more about it below, but overall NKK Switches was able to forecast components and meaningful aggregations of product families. By tracking forecast vs. actuals over several months, NKK was able to demonstrate the accuracy of its forecasts to its Asian factory suppliers, and convince them to shift from a “build-to-order” model to “build-to-forecast.” This change has resulted in dramatic reductions in lead times, in many cases cutting them in half, increasing customer satisfaction and the overall sales close rate.

The bottom line here is that there is a perfectly viable—I would say essential—method of demand forecasting for build-to-order businesses, setting high service levels for pivotal input resources. If you would like to know more, please drop me a note, at nelsonh at smartcorp dot com.

Nelson Hartunian, PhD, co-founded Smart Software, formerly served as President, and currently oversees it as Chairman of the Board. He has, at various times, headed software development, sales and customer service.

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      Handling Extreme Supply Chain Variability at Rev-A-Shelf

      The Smart Forecaster

      Pursuing best practices in demand planning,

      forecasting and inventory optimization

      Does your extended supply chain suffer from extreme seasonal variability? Does this situation challenge your ability to meet service level commitments to your customers? I have grappled with this at Rev-A-Shelf, addressing unusual conditions created by Chinese New Year and other global events, and would like to share the experience and a few things I learned along the way.

      First, let me explain our situation. We import 60% of the parts we use to build our kitchen and bath accessories from China and Europe. Most of the year we were able to plan our inventory needs using a spreadsheet-based min/max approach. But not during Chinese New Year, which drives the planet’s greatest annual population migration. Chinese New Year shuts down production for up to two months, creating significant supply risk as we strive to meet our three day order fulfillment commitment.

      We solved our problem, introducing statistical demand forecasting with the flexibility to extend lead times when necessary, the ability to reliably establish safety stocks that achieve our required service levels and a continuous reporting system that lets everyone know exactly where we stand. However, success required much more than a new piece of software. We needed to change the way we view future demand, supply risk and safety stock. Here are a few key things we did that made all the difference.

      Stakeholder education and buy-in

      Regardless of the project, it’s always best to enlist the buy-in of all stakeholders. We knew we had to do something to solve our problem, but there was bound to be resistance. Senior managers, for example, had developed a healthy distrust of software and wondered whether demand forecasting software could help. Our buyers had developed their own perspectives and procurement methods, and felt personally at risk as we considered new approaches.

      People came around as they developed a common understanding of the problem and how we would address it. Education was a big part of the solution. We explained how forecasting works and key factors we should all understand: how to analyze trends, how to use “what if” scenarios, impact of shifting lead times, how to relate service levels to supply risk and safety stock and key performance indicators like inventory turns. Going through this process together, we all became stakeholders in the solution.

      Use the Right software

      When you have lots of part numbers and any sort of supply or demand variability, you just cannot forecast effectively with a spreadsheet. With our min/max forecasting system, we were planning to an average, and it wasn’t working. Average usage has inherent flaws for planning purposes—it’s always looking backward!

      You need software that looks ahead, recognizes seasonal patterns and enables you to determine how much stock you’ll need to meet required service levels over varying lead times.

      Fine-tune processes

      When the old ways don’t work, you need to be open to adjusting your assumptions. Think less about where you’ve been, and more about where you want to be. Take a look at your lead times and plan to your desired service level. Last year’s history may not be the best predictor of this year’s demand. The same forecast horizon may not be appropriate for all products or certain time of the year.

      Make the Forecast Actionable

      It’s not enough to produce an accurate forecast and estimated inventory stocking levels. You’ve got to develop a way to make the information actionable for those tasked with using it. We developed a set of reports that enabled buyers to leverage better forecast and safety stock information. Now, at the end of every month, we produce a forecast report that provides a clear picture of current inventory, safety stock, past usage, forecasted usage, incoming deliveries (PO’s) and recommended order quantities.

      Validate Results

      You can, and we did, test our new methods against our own demand history. Still, an authoritative outsider can make acceptance easier. We commissioned a study by a professor at Louisville University’s College of Business who set one of her graduate students to the task. Through them we were able to reinforce what we saw happening from our results, and feel comfortable that we were on a good path.

      All of these factors helped Rev-A-Shelf transform its demand planning process, to great effect. Today we are exceeding our service level targets, and our fill rate, based on a three day ship cycle, is showing steady improvement, and trending up. Overall, units-in-stock have stayed flat while supporting a 13% increase in sales.

      John Engelhardt is currently Director of Purchasing and Asian Operations for Rev-a-Shelf, LLC in Louisville, KY. He has held a variety of management positions both in private business and public organizations. At Rev-A-Shelf he held the position of International Sales Manager and Director of Sales Support before assuming his current position. He can be reached at johne at rev-a-shelf dot com.

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          A CFO’s Perspective on Demand Planning – “More Strategic Than You Think”

          The Smart Forecaster

          Pursuing best practices in demand planning,

          forecasting and inventory optimization

          Bud Schultz, CPA, Vice President of Finance for NKK Switches, presented his company’s experience with demand planning during a recent webinar. The following is a brief summary of Bud’s key points; view the complete webinar by clicking here.

          Q: Tell us about NKK’s business and demand planning challenges.

          NKK Switches, based in Scottsdale, Arizona, is a leading manufacturer and supplier of electromechanical switches. The business involves many different switch types—toggles, push-button, rotary, even some programmable switch types. We are known for our high quality, and for our ability to meet an exceptionally broad range of customer requirements on a turnkey (custom configuration) basis. NKK Switches produces customized solutions from component parts sourced exclusively from manufacturing facilities in Japan and China.

          There are literally millions of possible switch configurations, and we never know what configured solutions our customers will order. This makes our demand highly intermittent and exceptionally difficult to forecast. In fact, until fairly recently we considered our demand unforecastable. We operated on a build-to-order basis, which meant that customer orders could not be fulfilled until their component parts were produced and then fashioned into finished goods by NKK. This resulted in long lead-times, painful for our customers and a competitive challenge for our sales organization.

          Q: What did you expect to get from improved product demand forecasting?

          When we began to investigate the value of demand forecasting software (SmartForecasts from Smart Software), we tried to view the decision from a Return on Investment (ROI) point of view. We did some capital budgeting, making assumptions about potential reductions in inventory levels, reduced inventory carrying costs and other potential savings. Although the capital budgets returned positive returns on investment, we nevertheless were unable to move forward based on that information. We lacked confidence in our assumptions, and we were worried that we wouldn’t be able to justify the safety stock and inventory levels that the software would suggest.

          What we didn’t expect was a challenge from our parent company. In light of the capabilities of a newly implemented ERP system, they would consider a new approach. If we could produce demonstrably reliable demand forecasts, they would consider procuring raw materials and producing switch components on a build-to-forecast rather than build-to-order basis. This opened the door to a much more profound impact. We tracked actuals against forecasts over a twelve-month period and found that our forecasts, particularly in aggregate, were exceptionally accurate: actual demand was within 3% of forecast. Once we were able to prove the validity of our forecasts, we were able to move forward with the parent company’s plan to manufacture product based on those forecasts.

          Q: How did accurate forecasts of product lines with intermittent demand data transform NKK’s operations?

          From the many different combinations we manufacture to order, individual switch parts can show very intermittent demand (long periods with zero orders and then seemingly random spikes), but we can identify more consistent patterns across switch series. All of the part numbers in a given series have common components and raw materials, such as plastic housing, brackets and other hardware, gold, silver and LEDs.

          Providing our manufacturing facilities with reliable forecasts ended up allowing us to make dramatic changes. Our manufacturing plants could start procuring raw materials that in the aggregate would eventually be used in production of different part numbers within that series, even if the specific part numbers to be produced were unknown at the time the forecasts were made. And in many instances, despite the irregular demand history data, it was even possible for the suppliers to manufacture specific part numbers based on the forecast.

          Once the program is fully implemented, we anticipate our leads times will be reduced to half the time or even less. Shorter lead times will result in lower reorder points, resulting in higher service levels while reducing our inventory requirements.

          Bud Schultz leads all finance and accounting functions at NKK. His background as a Certified Public Accountant, attorney, engineer and pilot for the US Air Force provide unique perspective on finances for engineering and manufacturing operations.

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          Why MRO Businesses Should Care About Excess Inventory

          Why MRO Businesses Should Care About Excess Inventory

          Do MRO companies genuinely prioritize reducing excess spare parts inventory? From an organizational standpoint, our experience suggests not necessarily. Boardroom discussions typically revolve around expanding fleets, acquiring new customers, meeting service level agreements (SLAs), modernizing infrastructure, and maximizing uptime. In industries where assets supported by spare parts cost hundreds of millions or generate significant revenue (e.g., mining or oil & gas), the value of the inventory just doesn’t raise any eyebrows, and organizations tend to overlook massive amounts of excessive inventory.

          Recent Posts

          • Overcoming Uncertainty with Service and Inventory Optimization TechnologyOvercoming Uncertainty with Service and Inventory Optimization Technology
            In this blog, we will discuss today's fast-paced and unpredictable market and the constant challenges businesses face in managing their inventory and service levels efficiently. The main subject of this discussion, rooted in the concept of "Probabilistic Inventory Optimization," focuses on how modern technology can be leveraged to achieve optimal service and inventory targets amidst uncertainty. This approach not only addresses traditional inventory management issues but also offers a strategic edge in navigating the complexities of demand fluctuations and supply chain disruptions. […]
          • Daily Demand Scenarios Smart 2Daily Demand Scenarios
            In this Videoblog, we will explain how time series forecasting has emerged as a pivotal tool, particularly at the daily level, which Smart Software has been pioneering since its inception over forty years ago. The evolution of business practices from annual to more refined temporal increments like monthly and now daily data analysis illustrates a significant shift in operational strategies. […]
          • The Cost of Doing nothing with your inventory Planning SystemsThe Cost of Spreadsheet Planning
            Companies that depend on spreadsheets for demand planning, forecasting, and inventory management are often constrained by the spreadsheet’s inherent limitations. This post examines the drawbacks of traditional inventory management approaches caused by spreadsheets and their associated costs, contrasting these with the significant benefits gained from embracing state-of-the-art planning technologies. […]
          • Learning from Inventory Models Software AILearning from Inventory Models
            In this video blog, the spotlight is on a critical aspect of inventory management: the analysis and interpretation of inventory data. The focus is specifically on a dataset from a public transit agency detailing spare parts for buses. […]
          • The methods of forecasting SoftwareThe Methods of Forecasting
            Demand planning and statistical forecasting software play a pivotal role in effective business management by incorporating features that significantly enhance forecasting accuracy. One key aspect involves the utilization of smoothing-based or extrapolative models, enabling businesses to quickly make predictions based solely on historical data. This foundation rooted in past performance is crucial for understanding trends and patterns, especially in variables like sales or product demand. Forecasting software goes beyond mere data analysis by allowing the blending of professional judgment with statistical forecasts, recognizing that forecasting is not a one-size-fits-all process. This flexibility enables businesses to incorporate human insights and industry knowledge into the forecasting model, ensuring a more nuanced and accurate prediction. […]

            Inventory Optimization for Manufacturers, Distributors, and MRO

            • Why MRO Businesses Need Add-on Service Parts Planning & Inventory SoftwareWhy MRO Businesses Need Add-on Service Parts Planning & Inventory Software
              MRO organizations exist in a wide range of industries, including public transit, electrical utilities, wastewater, hydro power, aviation, and mining. To get their work done, MRO professionals use Enterprise Asset Management (EAM) and Enterprise Resource Planning (ERP) systems. These systems are designed to do a lot of jobs. Given their features, cost, and extensive implementation requirements, there is an assumption that EAM and ERP systems can do it all. In this post, we summarize the need for add-on software that addresses specialized analytics for inventory optimization, forecasting, and service parts planning. […]
            • Spare-parts-demand-forecasting-a-different-perspective-for-planning-service-partsThe Forecast Matters, but Maybe Not the Way You Think
              True or false: The forecast doesn't matter to spare parts inventory management. At first glance, this statement seems obviously false. After all, forecasts are crucial for planning stock levels, right? It depends on what you mean by a “forecast”. If you mean an old-school single-number forecast (“demand for item CX218b will be 3 units next week and 6 units the week after”), then no. If you broaden the meaning of forecast to include a probability distribution taking account of uncertainties in both demand and supply, then yes. […]
            • Whyt MRO Businesses Should Care about Excess InventoryWhy MRO Businesses Should Care About Excess Inventory
              Do MRO companies genuinely prioritize reducing excess spare parts inventory? From an organizational standpoint, our experience suggests not necessarily. Boardroom discussions typically revolve around expanding fleets, acquiring new customers, meeting service level agreements (SLAs), modernizing infrastructure, and maximizing uptime. In industries where assets supported by spare parts cost hundreds of millions or generate significant revenue (e.g., mining or oil & gas), the value of the inventory just doesn’t raise any eyebrows, and organizations tend to overlook massive amounts of excessive inventory. […]
            • Top Differences between Inventory Planning for Finished Goods and for MRO and Spare PartsTop Differences Between Inventory Planning for Finished Goods and for MRO and Spare Parts
              In today’s competitive business landscape, companies are constantly seeking ways to improve their operational efficiency and drive increased revenue. Optimizing service parts management is an often-overlooked aspect that can have a significant financial impact. Companies can improve overall efficiency and generate significant financial returns by effectively managing spare parts inventory. This article will explore the economic implications of optimized service parts management and how investing in Inventory Optimization and Demand Planning Software can provide a competitive advantage. […]