Smart Software and ArcherPoint Team Up to Launch Smart IP&O for NAV

Collaboration Provides Smart Inventory Planning, Forecasting, & Optimization for Microsoft NAV

Boston MA., June 5, 2018 – Smart Software, Inc. is excited to announce the successful integration of its cloud-based Inventory Planning and Optimization software with Microsoft Dynamics NAV to create Smart IP&O for NAV.  Smart Software partnered with ArcherPoint Inc., a Microsoft Dynamics ERP Gold Partner and full-service provider for Dynamics NAV and Dynamics 365 to build the connector.

Smart Software is a global provider of next generation 100% web-based demand planning, forecasting, and inventory optimization solutions. ArcherPoint created the connector to integrate Smart Software’s tools with Microsoft Dynamics NAV. The new integration brings the cloud-based Smart IP&O (Inventory Planning and Optimization) into the latest version of Microsoft’s ERP solution. By seamlessly integrating strategic planning in Smart IP&O with operational execution in Dynamics NAV, business users can continuously predict, respond, and plan more effectively in today’s uncertain business environment.

Jim Benson, sales executive from ArcherPoint says, 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 Microsoft NAV. 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. In today’s supply chain, it is no longer enough to simply manage inventory. It must be optimized.”

The Smart/NAV integration makes all transactional data in NAV, such as shipments, sales orders, receipts, inventory on hand, and more, available in Smart IP&O’s data model. Smart IP&O brings this data to life leveraging field-proven analytics and forecasting methods. This enables executives and their planning team to identify operational inefficiencies, accurately forecast demand, model the financial and customer impact of current and proposed inventory policies, and return optimal planning parameters and forecasts to drive replenishment.

Greg Hartunian, CEO of Smart Software stated, “Businesses that leverage inventory optimization and forecasting technology are able to better understand their operations, lower costs, improve customer service, and outperform the competition. We look forward to working closely with ArcherPoint to help our joint customers achieve these key benefits.”

To learn more about the Smart IP&O for NAV and how it can help your business, please join us for a free webinar, Wednesday, June 27 at 2pm ET. We will provide a demo on the software, uses, and benefits of the product.  To register for the webinar please visit: https://www.archerpoint.com/events/lunch-and-learn-archerpoint-smart-inventory-planning-and-optimization

About Smart Software
Smart Software, a leading innovator in demand planning and inventory optimization software, offers Smart IP&O, an integrated suite of web-based demand planning, inventory optimization and supply chain analytics applications.  Smart Software has collaborated with ArcherPoint to develop an automated integration with Microsoft Dynamics NAV, enabling the transparent flow of data and results to drive Sales, Inventory and Operations Planning.  Founded in 1984, Smart serves a wide range of manufacturing, distribution, and transportation organizations including The Home Depot, FedEx, SCIEX, DisneyLand Resorts, MARS, BC Transit, Metro-North Railroad and many more.  Learn more at www.smartcorp.com.

About ArcherPoint
ArcherPoint has built a business around adaptive innovation. Regardless of industry, companies look to ArcherPoint as a business solution provider and partner they can depend on to deliver results. Our history with Microsoft Dynamics NAV dates back to the product’s beginnings. Today, our team includes experts all over the world, not only in Dynamics NAV solution designdevelopment, 24/7 support, and upgrades, but also in accounting, manufacturingretaildistribution, and other key areas of business. With a commitment to quality service, ArcherPoint is dedicated to helping companies realize true business value by giving them access to world-class ERP solutions that will grow with them to meet their needs now and in their future.


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

The Real Culprits of Stockouts and Excess

The Smart Forecaster

Pursuing best practices in demand planning, forecasting and inventory optimization

What is to blame for having too much of the stuff you don’t need and not enough of the stuff you do need?  Demand and supply variability are often blamed.  These problems are significant and seems impossible to overcome leaving many organizations to simply accept misallocated stock as a cost of doing business.  However, the real problem it isn’t simply late supplier deliveries and unpredictable demand.  These are supply chain planning “facts of life” and it’s how your company addresses them that counts.  Watch Greg Hartunian’s vlog to hear his thoughts and what you can do about it.

 

 

Smart Inventory Planning and Optimization automatically calculates the stocking policy that yields the best return for your business considering holding costs, ordering costs, and stock outs.  To see it in action, register below to watch a 12 minute demonstration.

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The 3 levels of forecasting: Point forecasts, Interval forecasts, Probability forecasts

The 3 levels of forecasting: Point forecasts, Interval forecasts, Probability forecasts

There are three possible types of forecasts that can be used in demand and inventory planning processes. Point forecasting, interval forecasting, and probabilistic forecasting. Each type of forecast offers progressively more information to inventory managers that will enhance the planning process. In this video blog, Dr. Thomas Willemain explains the differences and highlights the advantages that probabilistic forecasting offers. In summary, knowing more is always better than knowing less and the probability forecast provides additional information that is crucial for inventory planning.

Undershoot is Sabotaging your Service Level!

Undershoot is Sabotaging your Service Level!

Undershoot means that the lead time begins not at the reorder point but below it. Undershoot happens every time the demand that breached the reorder point took the stock down below (not down to) the reorder point. Undershoot picks your pocket before you even begin to roll the dice. It deludes the inventory professional into thinking his or her reorder points are sufficient to achieve their targets, whereas actual performance will not make the grade.

The Real Culprits of Stockouts and Excess

The Real Culprits of Stockouts and Excess

Service level and fill rate are two important metrics for measuring how effectively customer demand is satisfied. These terms are often confused and understanding the differences can help improve your inventory planning process. This video blog (Vlog) helps illustrate the difference with a simple example using Excel

Service Level vs Fill Rate

The Smart Forecaster

Pursuing best practices in demand planning, forecasting and inventory optimization

We are often asked what the difference is between these two important performance metrics for inventory planning. While they are both important for measuring how successful a business is in meeting demand, their meaning is very different.  If not understood and incorporated into the strategic inventory planning process, inventory will be inefficiently allocated resulting in lower customer service and higher carrying costs.  We’ve illustrated the difference in this 4 minute recording using Microsoft Excel.

 

 

 

Smart Operational Analytics automatically calculates historical service levels & fill rates across any item.  To see how you calculate these and other operational metrics including inventory turns, supplier performance, and more register below to watch a five minute demonstration.  The demo will show how our cloud platform continuously calculates and reports these metrics across thousands of items helping you identify opportunities for service level improvement and inventory reduction.

 

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Company Name *

Work Email *

Work Phone


 

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Related Posts

The 3 levels of forecasting: Point forecasts, Interval forecasts, Probability forecasts

The 3 levels of forecasting: Point forecasts, Interval forecasts, Probability forecasts

There are three possible types of forecasts that can be used in demand and inventory planning processes. Point forecasting, interval forecasting, and probabilistic forecasting. Each type of forecast offers progressively more information to inventory managers that will enhance the planning process. In this video blog, Dr. Thomas Willemain explains the differences and highlights the advantages that probabilistic forecasting offers. In summary, knowing more is always better than knowing less and the probability forecast provides additional information that is crucial for inventory planning.

Undershoot is Sabotaging your Service Level!

Undershoot is Sabotaging your Service Level!

Undershoot means that the lead time begins not at the reorder point but below it. Undershoot happens every time the demand that breached the reorder point took the stock down below (not down to) the reorder point. Undershoot picks your pocket before you even begin to roll the dice. It deludes the inventory professional into thinking his or her reorder points are sufficient to achieve their targets, whereas actual performance will not make the grade.

The Real Culprits of Stockouts and Excess

The Real Culprits of Stockouts and Excess

Service level and fill rate are two important metrics for measuring how effectively customer demand is satisfied. These terms are often confused and understanding the differences can help improve your inventory planning process. This video blog (Vlog) helps illustrate the difference with a simple example using Excel

The Advantages of Probability Forecasting
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The Smart Forecaster

Pursuing best practices in demand planning, forecasting and inventory optimization

Most demand forecasts are partial or incomplete: They provide only one single number: the most likely value of future demand. This is called a point forecast. Usually, the point forecast estimates the average value of future demand.

Much more useful is a forecast of full probability distribution of demand at any future time. This is more commonly referred to as probability forecasting and is much more useful.

The Average is Not the Answer

 

The one advantage of a point forecast is its simplicity. If your ERP system is also simple, the point forecast fills in the one number needed by the ERP system to do workforce scheduling or raw material purchases.

The disadvantage of a point forecast is that it is too simple. It ignores additional information in an item’s demand history that can give you a more complete picture of how demand might unfold: a probability forecast.

Going Beyond the Average: Probability Forecasting

 

While the point forecast provides limited information, e.g., “The most likely demand next month is 15 units”, the probability forecast adds crucial information, e.g., “There is a 20% chance that demand will exceed 28 units and a 10% chance that it will be less than 5 units”.

This information lets you do risk assessment and contingency planning. Contingency planning is necessary because the point forecast usually has only a small chance of actually being correct. A probability forecast may also say “The chance of demand being 15 units is only 10%, even though it is the single most likely value.” In other words, there is a 90% chance that the point forecast is wrong. This kind of error is not a mistake in the forecasting calculations: it is the reality of dealing with demand volatility. It might better be called an “uncertainty” than an “error”.

An operations manager can use the extra information in a probability forecast in both informal and formal ways. Informally, even if an ERP system requires a single-number forecast as input, a wise manager will want to have some clue about the risks associated with that point forecast, i.e., its margin of error. So a forecast of 15 ± 1 unit is a lot safer than a forecast of 15 ± 10. The ± part is a compression of a probabilistic forecast. Figure 1 below shows an item’s demand history (red line), point forecasts for the next 12 months (green line) and their margins of error (cyan lines). The lowest forecast of about 3,300 units occurs in June, but the actual demand might be as much as 800 units higher or lower.

Bonus: Application to Inventory Management

 

Inventory management requires that you balance item availability against the inventory cost. It turns out that knowing the full probability distribution of demand over a replenishment lead time is essential for setting reorder points (also called mins) on a rational, scientific basis. Figure 2 shows a probability forecast of total demand during the 33 week replenishment lead time for a certain spare part. While the average lead time demand is 3 units, the most likely demand is zero, and a reorder point of 14 is needed to insure that the chance of stocking out is only 1%. Once again, the average is not the answer.

Knowing more is always better than knowing less and the probability forecast provides that extra bit of crucial information. Software has been able to supply a point forecast for over 40 years, but modern software can do better and provide the whole picture.

 

 

Figure 1: The red line shows the demand history of a finished good. The green line shows the point forecasts for the next 12 months. The blue lines indicate the margins of error in the 12 point forecasts.

 

 

Figure 2: A probabilistic forecast of demand for a spare part over a 33 week replenishment lead time. The most likely demand is zero, the average demand is 3, but a reorder point of 14 units is required to have only a 1% chance of stock out.

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Undershoot is Sabotaging your Service Level!

Undershoot is Sabotaging your Service Level!

Undershoot means that the lead time begins not at the reorder point but below it. Undershoot happens every time the demand that breached the reorder point took the stock down below (not down to) the reorder point. Undershoot picks your pocket before you even begin to roll the dice. It deludes the inventory professional into thinking his or her reorder points are sufficient to achieve their targets, whereas actual performance will not make the grade.

How to Choose a Target Service Level

How to Choose a Target Service Level

When setting a target service level, make sure to take into account factors like current service levels, replenishment lead times, cost constraints, the pain inflicted by shortages on you and your customers, and your competitive position.

5 Demand Planning Tips for Calculating Forecast Uncertainty

5 Demand Planning Tips for Calculating Forecast Uncertainty

Those who produce forecasts owe it to those who consume forecasts, and to themselves, to be aware of the uncertainty in their forecasts. This note is about how to estimate forecast uncertainty and use the estimates in your demand planning process. We focus on forecasts made in support of demand planning as well as forecasts inherent in optimizing inventory policies involving reorder points, safety stocks, and min/max levels.

Too Much or Too Little Inventory?

The Smart Forecaster

Pursuing best practices in demand planning, forecasting and inventory optimization

Do you know which items have too much or too little inventory? What if you knew? How would you go about cutting overstocks while still ensuring a competitive service level? Would you be able to reduce stockouts without incurring a prohibitively expensive inventory increase? How would these changes impact service levels, costs and turns—for individual items, groups of items and overall?

Most companies know they have too much or too little inventory but lack a key ingredient for optimizing inventory: Service Level-Driven Demand Planning. To take action, you must know how much inventory is needed to satisfy the service level you require. More fundamentally, you need to know the specific service level that will result from your current inventory policies, the gap to be addressed and its financial implications.

Many organizations, especially those with intermittent demand, find this to be an exceptionally challenging trial and error process.

Moving to a service level-driven approach will overcome this challenge and ensure that rebalancing inventory improves service level performance at a lower cost. Start with the most accurate demand forecast possible, calibrate for forecast risk and then determine your optimal inventory position. In a recent webinar, I demonstrated Service Level-Driven Demand Planning and how SmartForecasts can be used to drive this process:

1. Measure the service levels that will be achieved at current inventory levels and with your current inventory policy.
2. Identify items that will achieve high service levels (98%+) but at prohibitively high cost.
3. Identify items that are at high risk of stockout (service levels < 75%).
4. Run multiple what-if scenarios based on a different prioritization of service levels by item or item groups. Choose the scenario that optimizes financial constraints with service objectives.
5. Quantify cash savings from reducing overstocks and the costs to increase inventory when service levels are unacceptably low.
6. Take action to establish new service level-driven reorder points, order quantities and inventory levels to meet your service targets and budget.

To view the webinar replay, please click here and complete the registration request.

Gregory Hartunian serves as President of Smart Software and as a member of the Board of Directors. A graduate of The F.W. Olin School for Business at Babson College, he formerly served as Vice President, Sales and Operations.

Leave a Comment

Related Posts

Undershoot is Sabotaging your Service Level!

Undershoot is Sabotaging your Service Level!

Undershoot means that the lead time begins not at the reorder point but below it. Undershoot happens every time the demand that breached the reorder point took the stock down below (not down to) the reorder point. Undershoot picks your pocket before you even begin to roll the dice. It deludes the inventory professional into thinking his or her reorder points are sufficient to achieve their targets, whereas actual performance will not make the grade.

How to Choose a Target Service Level

How to Choose a Target Service Level

When setting a target service level, make sure to take into account factors like current service levels, replenishment lead times, cost constraints, the pain inflicted by shortages on you and your customers, and your competitive position.

5 Demand Planning Tips for Calculating Forecast Uncertainty

5 Demand Planning Tips for Calculating Forecast Uncertainty

Those who produce forecasts owe it to those who consume forecasts, and to themselves, to be aware of the uncertainty in their forecasts. This note is about how to estimate forecast uncertainty and use the estimates in your demand planning process. We focus on forecasts made in support of demand planning as well as forecasts inherent in optimizing inventory policies involving reorder points, safety stocks, and min/max levels.