Lokad news - Integrated business forecasting

The video produced by Kirix about Lokad was a great source of inspiration for us. We realized that videos were a pretty efficient way to communicate on software. Thus, we decided to produce a couple of video tutorials for Lokad.

Our first tutorial is about Lokad Safety Stock Calculator. Check out how to start optimizing your inventory with Lokad within minutes.

(English subtitles are available, just click the CC button)

In this video, you will learn how get started with Lokad Safety Stock Calculator, how to import your sales data and how to generate your first report. We will also explain how the report works and what are the key figures to look at.

You can also download the Windows Media Player file of the video. Special thanks to Rex Teodosio for helping us producing this video.

Lokad Safety Stock Calculator v1.3 has been released. This new version fixes many subtle, yet annoying, defects of the previous versions.

Those fixes are based on questions sent to the Lokad support. Following the two ways fix approach, we do our best, first to address customer questions, and second the fix the underlying issues which caused questions to be raised in the first place.

Among the various improvements, it is now possible to

• to cancel an operation in progress.
• to minimize the application to the system tray when waiting for the forecasts.
• to clear a report (i.e. erasing all existing data while keeping the settings).
• to import data from Excel (check the tutorial).
• to browse for the right file when the connection string is a file path.

Plus, we have improved a couple of error messages and behaviors to make them less obscure to those who did not happen to actually design the application.

Lokad Safety Stock Calculator v1.1 has been released. This release comes with 6 newly supported applications

• QuickBooks
• Shop-Script
• CS-Cart
• Avactis
• LiveCart
• SoftSlate

A few bugs have also been fixed. If your favorite application is still missing from the list, just contact us.

Lokad Safety Stock Calculator v1.0 has been released. Beside having a new product icon (compared to the beta), this release supports many 3rd party applications, including JFire, Sage, Magento, X-Cart, PrestaShop, ViArt, WebERP that were previously unsupported. If your favorite application is still missing from the list, just contact us.

We have just released the first beta of Lokad Safety Stock Calculator (LSSC). This application is best suited for retailers and manufacturers who need to optimize their inventory levels. As announced previously, LSSC provides report points optimization and stock coverage analysis.

Compared to Lokad Desktop Sales Forecasting, LSSC comes as significant upgrade

• True business-oriented report that includes stocks on hand, suppliers, lead times, service levels ... in addition to the raw sales forecasts.
• Incremental inventory data retrieval and incremental sales data upload toward Lokad. Performances get greatly improved for recurrent usage.
• Build-in customization framework. LSSC comes bundled with LSSC Editor, a GUI tool that let you design custom inventory connectors for LSSC.

As LSSC gets out of beta, Lokad Desktop Sales Forecasting will be put in maintenance mode, since this application brings no additional benefits compared to LSSC.

Due to popular demand, we have started to work on Lokad Safety Stock Calculator an analytics application that will be dedicated to inventory optimization.

Soon after the initial release of Lokad Desktop Sales Forecasting, it did become clear that both retailers and manufacturers were needing a deeper analysis than just sales forecasts. In particular, safety stocks that optimize the desired levels of service were among the most frequently requested feature.

Our initial specification for the "safety stocks" application includes a report that displays, for every product (or every SKU if there are multiple storage locations),

• Past sales (grabbed from a 3rd party software).
• Future sales (forecasted by Lokad).
• Stock level (grabbed from a 3rd party software).
• Stock coverage (computed), the time to reach the stock out if no reorder is made.
• Supplier (manually entered), just to be able to sort the products against their respective suppliers.
• Lead time (manually entered).
• Service factor (manually entered), the desired probably to get a stock-out.
• Reorder point (computed), the suggested amount of inventory that should trigger a reorder.
• Delta stock (computed as stock at hand minus reorder point), it tells you how much over-stock you have.

Like we did already, this application will be released as open source under SourceForge. If you think we should include more features, do not hesitate to contact us or to directly submit a feature request.

Lately, a few users have been asking how does Lokad handle an exceptional sales that won't be happening again anytime soon? This issue is usually known as outliers management: how to deal with data points that are completely off compared to the other points.

Lokad is only looking at historical data, and since we don't know that the exceptional sales aren't going to happen again (expert knowledge), this event is going to be interpreted as "real" sales, leading to potentially over-estimated sales forecasts. This situation is a typical case of demand forecasts vs. sales forecasts.

At this point, the natural solution would be to give the user the possibility to adjust the historical data to truly reflects the demand. We are currently working on a solution dedicated to safety stock calculations that would handle this sort of situations. Stay tuned.

Accurate forecasts are critical because each extra-percent of forecast error comes with a steep price, literally. Indeed, when the costs associated to forecast errors are usually supra-linear, or put more simply, the costs associated to forecast errors increase much faster than the error itself.

As a simple example, a greater forecast error increases the need for safety stocks and thus working capital requirements. But if the working capital goes too high, bank interests start to rise, leading to even more expensive safety stocks.

But there are also more subtle negative consequences: past forecast errors may lower future accuracy. Indeed, historical demand itself is rarely known, instead, we usually rely on the historical sales data as an efficient approximation of the demand. Yet, this approximation is not perfect. For example, a stock-out prevents any sale to be made for a particular product. Yet, in case of a stock-out, zero sale does not equate zero demand.

For statistical forecasting algorithms, that relies on time-series analysis, it can be quite hard, using the sole sales data, to distinguish a zero sale caused by a stock-out from a zero demand. As a result, a lot of stock-outs (as they lead to lower sales) can be statistically interpreted as a lower demand; which, eventually, generates even more stock-outs.

Increasing your forecast accuracy now is one of the key to increase the forecast accuracy tomorrow. Accurate forecasting is not the destination but the journey.

In retail, the ultimate goal of sales forecasting is usually to calculate optimal safety stocks. Unfortunately, most online resources do give much detail about the explicit algorithms that should be used for safety stocks.

In order to facilitate the task for customers and partners (and competitors :-), I have just published an extensive guide Calculate safety stocks with sales forecasting. The guide is illustrated with a Microsoft Excel spreadsheet.

The intent of this guide is to be a valuable piece of information for practitioners. I have pushed some efforts in order to make it independent from the Lokad forecasting technology (thus, you can grab your favorite forecasting tool, and re-use the formulas as such).