Smart Software Launches Smart Inventory Optimization and Demand Planning for Prophet 21

Smart Software, a leader in enterprise demand planning, consensus forecasting, and inventory optimization solutions announces the release of Smart Inventory Planning and Optimization (Smart IP&O) for Prophet 21 (P21).  The company will demonstrate the solution at the Connect 2022, P21’s Annual User Group Conference August 29th – August 31st.  With Smart IP&O, Prophet 21 users will now be able to:

 

  • Conduct Global What if Scenarios across thousands of parts that compare Smart prescribed, user defined, and P21 calculated stocking policies across Key Performance Predictions of Service Levels, Fill Rates, Shortage Costs, Inventory Value, and more.

 

  • Leverage Smart’s prescribed stocking policies and service level recommendations that will optimally yield the most profitable outcomes for each part considering predicted holding costs, ordering costs, and shortage costs.

 

  • Accurately forecast all demand patterns including intermittent demand that is highly prevalent with distribution businesses. Smart’s patented probabilistic modeling engine generates thousands of future demand scenarios that more accurately predict demand and stocking policies.

 

  • Develop consensus forecasts comparing statistical, P21 generated forecasts, sales, and customer forecasts. Smart’s Demand Planning workbench enables graphical and tabular visualizations of all forecasts considered and supports automated consensus forecasting and accuracy measurement.

 

  • Leverage Smart IP&O’s bi-directional integration to P21 that continually updates Smart’s common data model with planning data and writes back forecasts and stocking policies on demand.

 

“Smart IP&O extends an already feature rich P21 with difference making forecasting and inventory optimization technology. Our joint customers will now be able to more effectively wield inventory to build a competitive moat around their business, maximize sales, and outperform the competition,” said Greg Hartunian, Smart Software CEO.  “Today’s supply chains need far better capabilities to contend with the extreme demand and supply variability businesses are facing today.  We look forward to equipping our Epicor P21 customers with the tools to do this effectively, accurately, and at scale.”

 

About Smart Software, Inc.

Founded in 1981, Smart Software, Inc. is an Epicor Platinum Partner and leading provider of demand planning, forecasting, inventory optimization, and analytics solutions. Our web platform, Smart IP&O, leverages probabilistic forecast modeling, machine learning, and collaborative demand planning to optimize inventory levels and increase forecast accuracy.  Smart Software is headquartered in Belmont, Massachusetts.  To learn more, visit www.smartcorp.com.

 

Smart Software to Present at Epicor Insights 2022

Smart Software President and CEO to present Epicor Insights 2022 Sessions on Creating Competitive Advantage with Smart Inventory Planning and Optimization

 

Belmont, MA, May, 2022 – Smart Software, Inc., provider of industry-leading demand forecasting, planning, and inventory optimization solutions, today announced that it will present at Epicor Insights 2022.

Greg Hartunian, CEO of Smart Software, will present two sessions and will explain Epicor Smart Inventory Planning and Optimization at this year’s Epicor Insights event in Nashville, TN. Greg will show how to empower planning teams to reduce inventory, improve service levels, and increase operational efficiency.

  • The Prophet 21 presentation is scheduled for Wed May 25th, 11:30 am -12:15 pm  (CST) 

Prophet 21 Smart Software to present at Epicor Insights 2022

Smart Software Kinetic 21 Session Greg CEO

  • The Kinetic presentation is scheduled for Wed May 25th, 2:30 pm – 3:20 pm (CST) 

Kinetic Smart Software to present at Epicor Insights 2022

 

If you plan to attend this year, please join us at either session below and learn more about Smart Inventory Planning and Optimization as we highlight valuable features in our solutions. Epicor Insights 2022 will bring together more than 2,000 users of Epicor’s industry-specific ERP solutions for the manufacturing, distribution, and service industries.  To learn more, visit INSIGHTS 2022.

Insights Team at work

Smart Software is an Epicor Platinum Partner and leading provider of demand planning, forecasting, inventory optimization, and analytics solutions. Our web platform, Smart IP&O, leverages probabilistic forecast modeling, machine learning, and collaborative demand planning to optimize inventory levels and increase forecast accuracy. You’ll use Smart IP&O to create accurate forecasts and optimal stocking policies that drive automated ordering in Epicor. The platform includes bi-directional integrations to both Epicor ERP and Prophet 21.

 

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 at mid-market enterprises and Fortune 500 companies, such as Otis Elevator, Mitsubishi, Siemens, Disney, FedEx, MARS, and The Home Depot.  Smart Inventory Planning & Optimization gives 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 can be found on the World Wide Web at www.smartcorp.com.

 


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

 

 

An Example of Simulation-Based Multiechelon Inventory Optimization

Managing the inventory in a single facility is difficult enough, but the problem becomes much more complex when there are multiple facilities arrayed in multiple echelons. The complexity arises from the interactions among the echelons, with demands at the lower levels bubbling up and any shortages at the higher levels cascading down.

If each of the facilities were to be managed in isolation, standard methods could be used, without regard to interactions, to set inventory control parameters such as reorder points and order quantities. However, ignoring the interactions between levels can lead to catastrophic failures. Experience and trial and error allow the design of stable systems, but that stability can be shattered by changes in demand patterns or lead times or by the addition of new facilities. Coping with such changes is greatly aided by advanced supply chain analytics, which provide a safe “sandbox” within which to test out proposed system changes before deploying them. This blog illustrates that point.

 

The Scenario

To have some hope of discussing this problem usefully, this blog will simplify the problem by considering the two-level hierarchy pictured in Figure 1. Imagine the facilities at the lower level to be warehouses (WHs) from which customer demands are meant to be satisfied, and that the inventory items at each WH are service parts sold to a wide range of external customers.

 

Fact and Fantasy in Multiechelon Inventory Optimization

Figure 1: General structure of one type of two-level inventory system

Imagine the higher level to consist of a single distribution center (DC) which does not service customers directly but does replenish the WHs. For simplicity, assume the DC itself is replenished from a Source that always has (or makes) sufficient stock to immediately ship parts to the DC, though with some delay. (Alternatively, we could consider the system to have retail stores supplied by one warehouse).

Each level can be described in terms of demand levels (treated as random), lead times (random), inventory control parameters (here, Min and Max values) and shortage policy (here, backorders allowed).

 

The Method of Analysis

The academic literature has made progress on this problem, though usually at the cost of simplifications necessary to facilitate a purely mathematical solution. Our approach here is more accessible and flexible: Monte Carlo simulation. That is, we build a computer program that incorporates the logic of the system operation. The program “creates” random demand at the WH level, processes the demand according to the logic of a chosen inventory policy, and creates demand for the DC by pooling the random requests for replenishment made by the WHs. This approach lets us observe many simulated days of system operation while watching for significant events like stockouts at either level.

 

An Example

To illustrate an analysis, we simulated a system consisting of four WHs and one DC. Average demand varied across the WHs. Replenishment from the DC to any WH took from 4 to 7 days, averaging 5.15 days. Replenishment of the DC from the Source took either 7, 14, 21 or 28 days, but 90% of the time it was either 21 or 28 days, making the average 21 days. Each facility had Min and Max values set by analyst judgement after some rough calculations.

Figure 2 shows the results of one year of simulated daily operation of this system. The first row in the figure shows the daily demand for the item at each WH, which was assumed to be “purely random”, meaning it had a Poisson distribution. The second row shows the on-hand inventory at the end of each day, with Min and Max values indicated by blue lines. The third row describes operations at the DC.  Contrary to the assumption of much theory, the demand into the DC was not close to being Poisson, nor was the demand out of the DC to the Source. In this scenario, Min and Max values were sufficient to keep item availability was high at each WH and at the DC, with no stockouts observed at any of the five facilities.

 

Click here to enlarge the image

Figure 2 - Simulated year of operation of a system with four WHs and one DC.

Figure 2 – Simulated year of operation of a system with four WHs and one DC.

 

Now let’s vary the scenario. When stockouts are extremely rare, as in Figure 2, there is often excess inventory in the system. Suppose somebody suggests that the inventory level at the DC looks a bit fat and thinks it would be good idea to save money there. Their suggestion for reducing the stock at the DC is to reduce the value of the Min at the DC from 100 to 50. What happens? You could guess, or you could simulate.

Figure 3 shows the simulation – the result is not pretty. The system runs fine for much of the year, then the DC runs out of stock and cannot catch up despite sending successively larger replenishment orders to the Source. Three of the four WHs descend into death spirals by the end of the year (and WH1 follows thereafter). The simulation has highlighted a sensitivity that cannot be ignored and has flagged a bad decision.

 

Click here to enlarge image

Figure 3 - Simulated effects of reducing the Min at the DC.

Figure 3 – Simulated effects of reducing the Min at the DC.

 

Now the inventory managers can go back to the drawing board and test out other possible ways to reduce the investment in inventory at the DC level. One move that always helps, if you and your supplier can jointly make it happen, is to create a more agile system by reducing replenishment lead time. Working with the Source to insure that the DC always gets its replenishments in either 7 or 14 days stabilizes the system, as shown in Figure 4.

 

Click here to enlarge image

Figure 4 - Simulated effects of reducing the lead time for replenishing the DC.

Figure 4 – Simulated effects of reducing the lead time for replenishing the DC.

 

Unfortunately, the intent of reducing the inventory at the DC has not been achieved. The original daily inventory count was about 80 units and remains about 80 units after reducing the DC’s Min and drastically improving the Source-to-DC lead time. But with the simulation model, the planning team can try out other ideas until they arrive at a satisfactory redesign. Or, given that Figure 4 shows the DC inventory starting to flirt with zero, they might think it prudent to accept the need for an average of about 80 units at the DC and look for ways to trim inventory investment at the WHs instead.

 

The Takeaways

  1. Multiechelon inventory optimization (MEIO) is complex. Many factors interact to produce system behaviors that can be surprising in even simple two-level systems.
  2. Monte Carlo simulation is a useful tool for planners who need to design new systems or tweak existing systems.

 

 

 

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Smart Software to Present at Epicor Insights 2021

Smart Software President and CEO to present Epicor Insights 2021 Breakout Session on Creating Competitive Advantage with Smart Inventory Planning and Optimization

 

Belmont, MA, June, 2021 – Smart Software, Inc., provider of industry-leading demand forecasting, planning, and inventory optimization solutions, today announced that it will present at Epicor Insights 2021.

Greg Hartunian, CEO of Smart Software, will present “Creating Competitive Advantage with Smart Inventory Planning and Optimization.” Greg will explain how to empower planning teams to reduce inventory, improve service levels, and increase operational efficiency. Most inventory planning teams rely upon traditional forecasting approaches, rule of thumb methods, and sales feedback on demand. Our Breakout Session at Epicor Insights discusses these approaches, why they often fail, and how new probabilistic forecasting and optimization methods can make a big difference to your bottom line.

  • The presentation is scheduled for Wed July 14th 10:25 -11:15 AM  (PST) 

1 Epicor Inventory Mangement Platinum Partner

Epicor Insights 2021 will bring together more than 2,000 users of Epicor’s industry-specific ERP solutions for the manufacturing, distribution, and service industries.  To learn more, visit INSIGHTS 2021.

 Join us at Mandalay Bay in Las Vegas, at the Solution Pavilion,  Booth #1.

3 Epicor Inventory Mangement Platinum Partner

 

2 Epicor Inventory Mangement Platinum Partner

 

Smart Software is an Epicor Platinum Partner and leading provider of demand planning, forecasting, inventory optimization, and analytics solutions. Our web platform, Smart IP&O, leverages probabilistic forecast modeling, machine learning, and collaborative demand planning to optimize inventory levels and increase forecast accuracy. You’ll use Smart IP&O to create accurate forecasts and optimal stocking policies that drive automated ordering in Epicor. The platform includes bi-directional integrations to both Epicor ERP and Prophet 21.

 

 

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 at mid-market enterprises and Fortune 500 companies, such as Otis Elevator, Mitsubishi, Siemens, Disney, FedEx, MARS, and The Home Depot.  Smart Inventory Planning & Optimization gives 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 can be found on the World Wide Web at www.smartcorp.com.

 


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

 

 

What you Need to know about Inventory Forecasting and Planning

Q&A with Smart Software: Forecasting solutions and the business benefits of inventory optimization

Belmont, Mass., October, 2020 – Smart Software, Inc., provider of industry-leading demand forecasting, inventory planning, and inventory optimization solutions, announced today that SourceForge Online Magazine will feature an interview with Smart Software CEO, Greg Hartunian.  In the interview, Mr. Hartunian shares background on Smart Software’s 35 years in the planning software business, the business benefits of improving inventory planning and forecasting processes, and offers practical advice to help enterprises reduce standing inventory and increase service levels.
To read the article please visit https://sourceforge.net/articles/

 

Summit Group America 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 at mid-market enterprises and Fortune 500 companies, such as Otis Elevator, Mitsubishi, FedEx, MARS,  The Home Depot, Siemens and Disney, . Smart Inventory Planning & Optimization gives 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 can be found on the World Wide Web at www.smartcorp.com.

SmartForecasts and Smart IP&O are registered trademarks of Smart Software, Inc.  All other trademarks are the property of their respective owners.


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