Finding Your Spot on the Inventory Tradeoff Curve

This video blog holds essential insights for those working with the complexities of inventory management. The session focuses on striking the right balance within the inventory tradeoff curve, inviting viewers to understand the deep-seated importance of this equilibrium. If you’ve ever had to manage stock, you’ll know it feels like a bit of a tug-of-war. On one side, you’re pulling towards less inventory, which is great for saving money but can leave your customers high and dry. On the other, you’re considering more inventory, which keeps your customers happy but can be a pain for your budget. To make a smart choice in this ongoing tug-of-war, you need to understand where your current inventory decisions place you on this tradeoff curve. Are you at a point where you can handle the pressure, or do you need to shuffle along to a more comfortable spot?

If you can’t answer this question, it means that you still rely on outdated methods, risking the potential for surplus inventory or unmet customer needs. Watch the video so you can see exactly where you are on this curve and understand better about whether you want to stay put or move to a more optimal position.

 

And if you decide to move, we’ve got the tools to guide you. Smart IP&O’s advanced “what-if” analysis enables businesses to precisely evaluate the impact of different inventory strategies, such as adjustments to safety stock levels or changes in reorder points, on their balance between holding costs and service levels. By simulating demand scenarios and inventory policies, Smart IP&O provides a clear visualization of potential financial outcomes and service level implications, allowing for data-driven strategic decisions. This powerful tool ensures businesses can achieve an optimal balance, minimizing excess inventory and related costs while maintaining high service levels to meet customer demand efficiently.  

 

 

Why 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.

For example, at a recent Maximo Utilities Working Group event, several prospects stated that “Our EAM will do that” when asked about requirements for forecasting usage, netting out supply plans, and optimizing inventory policies. They were surprised to learn it did not and wanted to know more.

In this post, we summarize the need for add-on software that addresses specialized analytics for inventory optimization, forecasting, and service parts planning.   

EAM Systems

EAM systems can’t ingest forecasts of future usage – these systems simply aren’t designed to conduct supply planning and many don’t even have a place to hold forecasts. So, when an MRO business needs to net out known requirements for planned production or capital projects, an add-on application like Smart IP&O is needed.

Inventory Optimization software with features that support planning known future demand will take project-based data not maintained in the EAM system (including project start dates, duration, and when each part is expected to be needed) and compute a period-by-period forecast over any planning horizon. That “planned” forecast can be projected alongside statistical forecasts of “unplanned” demand arising from normal wear and tear. At that point, parts planning software can net out the supply and identify gaps between supply and demand. This ensures that these gaps won’t go unnoticed and result in shortages that would otherwise delay the completion of the projects. It also minimizes excess stock that would otherwise be ordered too soon and needlessly consumes cash and warehouse space. Again, MRO businesses sometimes mistakenly assume that these capabilities are addressed by their EAM package.

ERP Systems

ERP systems, on the other hand, typically do include an MRP module that is designed to ingest a forecast and net out material requirements. Processing will consider current on hand inventory, open sales orders, scheduled jobs, incoming purchase orders, any bill of materials, and items in transit while transferring between sites. It will compare those current state values to the replenishment policy fields plus any monthly or weekly forecasts to determine when to suggest replenishment (a date) and how much to replenish (a quantity).

So, why not use the ERP system alone to net out the supply plan to prevent shortages and excess? First, while ERP systems have a placeholder for a forecast and some systems can net out supply using their MRP modules, they don’t make it easy to reconcile planned demand requirements associated with capital projects. Most of the time, the data on when planned projects will occur is maintained outside of the ERP, especially the project’s bill of materials detailing what parts will be needed to support the project. Second, many ERP systems don’t offer anything effective when it comes to predictive capabilities, relying instead on simple math that just won’t work for service parts due to the high prevalence of intermittent demand. Finally, ERP systems don’t have flexible user-friendly interfaces that support interacting with the forecasts and supply plan.

Reorder Point Logic

Both ERP and EAM have placeholders for reorder point replenishment methods such as Min/Max levels. You can use inventory optimization software to populate these fields with the risk-adjusted reorder point policies. Then within the ERP or EAM systems, orders are triggered whenever actual (not forecasted) demand drives on-hand stock below the Min. This type of policy doesn’t use a traditional forecast that projects demand week-over-week or month-over-month and is often referred to as “demand driven replenishment” (since orders only occur when actual demand drives stock below a user defined threshold).

But just because it isn’t using a period-over-period forecast doesn’t mean it isn’t being predictive. Reorder point policies should be based on a prediction of demand over a replenishment lead time plus a buffer to protect against demand and supply variability. MRO businesses need to know the stockout risk they are incurring with any given stocking policy. After all, inventory management is risk management – especially in MRO businesses when the cost of stockout is so high. Yet, ERP and EAM do not offer any capabilities to risk-adjust stocking policies. They force users to manually generate these policies externally or to use basic rule of thumb math that doesn’t detail the risks associated with the choice of policy.

Summary

Supply chain planning functionality such as inventory optimization isn’t the core focus of EAM  and ERP. You should leverage add-on planning platforms, like Smart IP&O, that support statistical forecasting, planned project management, and inventory optimization. Smart IP&O will develop forecasts and stocking policies that can be input to an EAM or ERP system to drive daily ordering.

 

 

Spare Parts Planning Software solutions

Smart IP&O’s service parts forecasting software uses a unique empirical probabilistic forecasting approach that is engineered for intermittent demand. For consumable spare parts, our patented and APICS award winning method rapidly generates tens of thousands of demand scenarios without relying on the assumptions about the nature of demand distributions implicit in traditional forecasting methods. The result is highly accurate estimates of safety stock, reorder points, and service levels, which leads to higher service levels and lower inventory costs. For repairable spare parts, Smart’s Repair and Return Module accurately simulates the processes of part breakdown and repair. It predicts downtime, service levels, and inventory costs associated with the current rotating spare parts pool. Planners will know how many spares to stock to achieve short- and long-term service level requirements and, in operational settings, whether to wait for repairs to be completed and returned to service or to purchase additional service spares from suppliers, avoiding unnecessary buying and equipment downtime.

Contact us to learn more how this functionality has helped our customers in the MRO, Field Service, Utility, Mining, and Public Transportation sectors to optimize their inventory. You can also download the Whitepaper here.

 

 

White Paper: What you Need to know about Forecasting and Planning Service Parts

 

This paper describes Smart Software’s patented methodology for forecasting demand, safety stocks, and reorder points on items such as service parts and components with intermittent demand, and provides several examples of customer success.

 

    The Three Types of Supply Chain Analytics

    ​In this video blog, we explore the critical roles of Descriptive, Predictive, and Prescriptive Analytics in inventory management, highlighting their essential contributions to driving supply chain optimization through strategic foresight and insightful data analysis.

     

    ​These analytics foster a dynamic, responsive, and efficient inventory management ecosystem by enabling inventory managers to monitor current operations, anticipate future developments, and formulate optimal responses. We’ll walk you through how Descriptive Analytics keeps you informed about current operations, Predictive Analytics helps you anticipate future demands, and Prescriptive Analytics guides your strategic decisions for maximum efficiency and cost-effectiveness.

    By the end of the video, you’ll have a solid understanding of how to leverage these analytics to enhance your inventory management strategies. These are not just tools but a new way of thinking about and approaching inventory optimization with the support of modern software.

     

     

    The Objectives in Forecasting

    A forecast is a prediction about the value of a time series variable at some time in the future. For instance, one might want to estimate next month’s sales or demand for a product item. A time series is a sequence of numbers recorded at equally spaced time intervals; for example, unit sales recorded every month.

    The objectives you pursue when you forecast depend on the nature of your job and your business. Every forecast is uncertain; in fact, there is a range of possible values for any variable you forecast. Values near the middle of this range have a higher likelihood of actually occurring, while values at the extremes of the range are less likely to occur. The following figure illustrates a typical distribution of forecast values.

    forecast distribution of forecast values

    Illustrating a forecast distribution of forecast values

     

    Point forecasts

    The most common use of forecasts is to estimate a sequence of numbers representing the most likely future values of the variable of interest. For instance, suppose you are developing a sales and marketing plan for your company. You may need to fill in 12 cells in a financial spreadsheet with estimates of your company’s total revenues over the next 12 months. Such estimates are called point forecasts because you want a single number (data point) for each forecast period. Smart Demand Planner’ Automatic forecasting feature provides you with these point forecasts automatically.

    Interval forecasts

    Although point forecasts are convenient, you will often benefit more from interval forecasts. Interval forecasts show the most likely range (interval) of values that might arise in the future. These are usually more useful than point forecasts because they convey the amount of uncertainty or risk involved in a forecast. The forecast interval percentage can be specified in the various forecasting dialog boxes in the Demand Planning SoftwareEach of the many forecasting methods (automatic, moving average, exponential smoothing and so on) available in Smart Demand Planner allow you to set a forecast interval.

    The default configuration in Smart Demand Planner provides 90% forecast intervals. Interpret these intervals as the range within which the actual values will fall 90% of the time. If the intervals are wide, then there is a great deal of uncertainty associated with the point forecasts. If the intervals are narrow, you can be more confident. If you are performing a planning function and want best case and worst case values for the variables of interest at several times in the future, you can use the upper and lower limits of the forecast intervals for that purpose, with the single point estimate providing the most likely value. In the previous figure, the 90% forecast interval extends from 3.36 to 6.64.

    Upper percentiles

    In inventory control, your goal may be to make good estimates of a high percentile of the demand for a product item. These estimates help you cope with the tradeoff between, on the one hand, minimizing the costs of holding and ordering stock, and, on the other hand, minimizing the number of lost or back-ordered sales due to a stock out. For this reason, you may wish to know the 99th percentile or service level of demand, since the chance of exceeding that level is only 1%.

    When forecasting individual variables with features like Automatic forecasting, note that the upper limit of a 90% forecast interval represents the 95th percentile of the predicted distribution of the demand for that variable. (Subtracting the 5th percentile from the 95th percentile leaves an interval containing 95%-5% = 90% of the possible values.) This means you can estimate upper percentiles by changing the value of the forecast interval. In the figure, “Illustrating a forecast distribution”, the 95th percentile is 6.64.

    To optimize stocking policies at the desired service level or to let the system recommend which stocking policy and service level generates the best return, consider using Smart Inventory Optimization.   It is designed to support what-if scenarios that show predicted tradeoffs of varying inventory polices including different service level targets.

    Lower percentiles

    Sometimes you may be concerned with the lower end of the predicted distribution for a variable. Such cases often arise in financial applications, where a low percentile of a revenue estimate represents a contingency requiring financial reserves. You can use Smart Demand Planner in this case in a way analogous to the case of forecasting upper percentiles. In the figure, “Illustrating a forecast distribution” , the 5th percentile is 3.36.

    In conclusion, forecasting involves predicting future values, with point forecasts offering single estimates and interval forecasts providing likely value ranges. Smart Demand Planner automates point forecasts and allows users to set intervals, aiding in uncertainty assessment. For inventory control, the tool facilitates understanding upper (e.g., 99th percentile) and lower (e.g., 5th percentile) percentiles. To optimize stocking policies and service levels, Smart Inventory Optimization supports what-if scenarios, ensuring effective decision-making on how much to stock given the risk of stock out you are willing to accept.

     

     

     

    Smart Software Announces Strategic Partnership with Sage for Inventory Optimization and Demand Forecasting

    Belmont, MA, February  2024 –Smart Software, a global provider of next-generation cloud-based inventory optimization, demand planning, and forecasting solutions, announces today their strategic partnership with Sage.

    This collaboration brings Smart IP&O (Inventory Planning and Optimization) into the latest cloud and on-premises versions of Sage X3, Sage 300, and Sage 100. By seamlessly integrating strategic planning with operational execution, users can eliminate reactive inventory planning and forecast guesswork by accurately calibrating risks, tradeoffs, and consequences at scale with Smart IP&O.

    Sage is the leader in accounting, financial, HR and payroll technology for small and mid-sized businesses (SMBs). Customers trust Sage’s comprehensive suite of finance, HR, and Supply Chain software to streamline processes and simplify operational tasks. This integrated approach to solving business challenges ensures seamless interactions and delivers valuable insights to SMBs, reinforcing Sage’s position as a leader in the industry.

    “Smart Software helps our customers by delivering insightful business analytics for inventory modeling and forecasting that drive ordering and replenishment in the latest version of Sage. With Smart IP&O, our customers gain a means to shape inventory strategy to align with the business objectives while empowering their planning teams to reduce inventory and improve service,” says   Regina Crowshaw, Director of ISV Strategy, Sales, and Programs at Sage.

    “Sage drives innovation and fosters business growth by delivering insightful solutions designed to enable organizations to scale and succeed. By leveraging the capabilities of Smart’s field-proven demand forecasting and inventory planning solutions, Sage is poised to supply the necessary expertise to assess needs, establish objectives, and craft the underlying business strategies key for ensuring widespread adoption and deriving maximum benefit.  We look ahead to what we can accomplish together, and we look forward to our joint success”, says Greg Hartunian, President and CEO at Smart Software.

    About Smart Software, Inc.

    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, and our website is www.smartcorp.com.

    About Sage Corporation

    Sage exists to knock down barriers so everyone can thrive, starting with the millions of Small and Mid-Sized Businesses served by us, our partners, and accountants. Customers trust our finance, HR, and payroll software to make work and money flow. By digitizing business processes and relationships with customers, suppliers, employees, banks, and governments, our digital network connects SMBs, removing friction and delivering insights. Knocking down barriers also means we use our time, technology, and experience to tackle digital inequality, economic inequality and the climate crisis.


    For more information, please contact Smart Software, Inc., Four Hill Road, Belmont, MA 02478.
    Phone: 1-800-SMART-99 (800-762-7899); FAX: 1-617-489-2748; E-mail: info@smartcorp.com