Free Delivery For Online Retailers

New models for online businesses are emerging. Products are being priced low with free delivery, but the lead time is much longer. Pricing low means orders will come in and businesses will have the economies of scale to pay for delivery. What is more customer information and orders can be analyzed to encourage loyalty. The whole works of customer acquisition, engagement, conversion and loyalty with Google Analytics can definitely come into play here.

Advance Prediction And Classification Techniques

Below is a list of resources to understand advance prediction and classification techniques. Enjoy! :)

Neural network - http://www.data-miners.com/companion/Chapter7.ppt

Decision trees and Random Forest - http://www.cs.cmu.edu/~ggordon/10601/recitations/rec08/Rec08_Oct21.ppt

Principal Conponent Analysis (PCA) and Factor Analysis (FA) - http://sociology.about.com/od/Statistics/a/Factor-Analysis.htm

Gradient boosting method (GBM), same as regression! - http://en.m.wikipedia.org/wiki/Gradient_boosting#section_1

K nearest neighbor (KNN) - http://www.scholarpedia.org/article/K-nearest_neighbor

Least squares regression to lasso, ridge and elastic nets - http://www.stanford.edu/~hastie/Papers/B67.2%20(2005)%20301-320%20Zou%20&%20Hastie.pdf

Generalized additive model (GAM) - http://www.d.umn.edu/math/Technical%20Reports/Technical%20Reports%202007-/TR%202007-2008/TR_2008_8.pdf

Support vector machine (SVM) - http://docs.opencv.org/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.htm

Improving Hotel Room Turnaround Productivity

Are hotels still relying on average times to make good a room to plan for resource?

How about forecasting time to clean rooms with different messiness levels? Different messiness levels can then be associated with whether customers are business or family, whether there is room service or not, length of stay, etc...

These forecast will then help managers plan resources more accurately. What's more, they can also assign cleaning/chambermaid resources base on profiles of customers to facilitate subsequent cleaning.

A/B Testing To Increase Sales and Synchronize with your Supply Chains

The digital gurus of the Obama campaign had given us tremendous insight into how we can increase participation, opinion and funding through big data crunching (http://www.motherjones.com/politics/2012/10/obama-campaign-tech-staff).

From a supply chain point of view, we should no longer see demand as something to be modelled from historical data, but just one piece of information to complement continuous sensing and improvement to increase sales, especially online sales. So how do we increase online sales? We heard of how simple A/B testing has helped pull in the bucks (http://blog.optimizely.com/2010/11/29/how-obama-raised-60-million-by-running-a-simple-experiment/).

For many online retailers, many of them continuously refine their websites through experiments to increases sales, cross-sell, upsell and bundling opportunities. This demand creation approach is really quite different from the traditional historical sales analysis coupled with sales promotions and new product launches. 

Demand creation is very interesting as we creating a pull of end products from raw materials. At the very least, it complements traditional forecasting/sales promotion/product launches by reducing the bullwhip effect along the supply chain. So how do we do it, it seems quite straight-forward with google analytics (http://support.google.com/analytics/bin/answer.py?hl=en&answer=1745210&topic=1745207&ctx=topic)

Google Analytics as Forecast for online businesses

Someone said that Google Analytics (GA) is for sales and marketing, it is tool much of a stretch use if for supply chain management.

I certainly don't think so. Good marketing and sales capability means good forecast and synchronization with operations.

The proliferation of online commerce and use of analytics tools like GA has not only help to grow sales for operations synchronization, but ahead also developed better forecasts to minimize obsolete inventory. In fact, I think GA is about accurate forecasts and growing demand.

It will be interesting to develop a whole business to help companies reduce markdowns and write offs by adjusting prices and GA.

List Of Free Supply Chain Web Applications

Some of you have asked me to post a summary of what my web applications to.

Below is it. Had sequenced the applications and brief write-up here so that you and your company can build capabilities on top of one another for end to end supply chain capability development.

1. Serialization and Leveraging Off Serialization Standards:
www.transhipmentflow.appspot.com
- It allows users to scan their GS1 128 standard bar codes for decoding by my web application. Many companies ate using 128 standards as it is globally recognized, and it can take production dates, expiry dates, weight, batch, etc.. Thereafter it converts the bar code to a QR code and tells the user how many characters is left. There is no decoder right now, and I think as a transhipment hub, Singapore SMEs will want to decode original bar code information and add to it. QR code is free and can take the most characters.

2. Track and Trace by Associating Product/Carton Serialized Bar/QR code With Location (e.g. online warehouse management system):
http://trackandtraceanalytics.appspot.com/
- This is a simple location and product tracking system where you can scan any and product bar code to a location bar code, find the location of your product when you have the product bar code requirement, then scan out from the location when you pick to free up the location bar code space.

3. Streamlining Route by Visualizing Current Route with Space Filling Curve Routing Algorithm
http://compareroute.appspot.com/
- This web application helps users compare their current delivery travel distance with the distance my web application is showing using an algorithm. Base on the average speed and time it leaves your company and return, you can probably estimate the travel distance of your delivery trucks compared to what this web application is predicting. For companies wishing to reduce fuel cost when they suspect certain routes are a lot longer than they should be.

4. Know possible customers along their delivery route for more business with transportation marginal cost
http://nearmyroute.appspot.com/
- Is an advance version of compareroute where I know what is around your delivery points. Helps you identify potential customers

5. Associating picture documents with deliveries for further analysis (e.g. picture of signed DO)
www.transhipmentocr.appspot.com
– web application to convert jpg, bmp, png and gif image files into text for further processing customization. You just need to browse the file and upload to the server and my program will process it.

Matching Available Delivery Resources With Those That Need It

In the spirit of prototyping, I had just put together a free website for companies to post available delivery resources so that those who need it can find it. Feedback and comments are most welcomed! :)

https://sites.google.com/site/foodconcerige/

Quick-Change High-Mix, Low-Volume Approach For Transhipment Hubs

I have talked about the use of marginal contribution approach to calculate stocking levels base on overstocking and under stocking cost in the transhipment analytics approach earlier, and compare it with the safety stock and variability propagation calculations.

What I had not talked about is about developing quick change, high-mix, low-volume value added services for a
transhipment hub like Singapore. Value added services like labelling, repacking, QC, light assembling and customization are carried out in such centralized locations. It is thus key for these companies to grab opportunities to reduce changeover time by better scheduling and value stream mapping approaches. What is also important is to know when we need to buffer with inventory, time and capacity. This is where Factory Physics approach comes in.

Value added, storage, logistics, manufacturing and even raw materials balancing and adjustments can then be done with coming item level serialization.

Consider Multi-Echelon Inventory With Centralized Hubbing to Pool Inventory and Risk

One common way to pool risk and reduce overall inventory is to use a hub with good air and sea connectivity like Singapore.

However, this considers just variability of demand and lead time from a central location to meet customer demand and service level at customer market locations. The cost of under stocking and not meeting customer demand may be more than what we think. Similarly, the cost of overage may be higher and lower. Taking both the cost of overage as underage into account will tell us the stock levels we need to maintain. This is the news vendor approach.

Better still, we can extend the news vendor approach to multi-echelon (or multi-site) inventory allocation problem for stochastic demand and lead time variability. This is especially interesting for Asia where you have manufacturers and transhipment hubs located close to each other. You can measure the service level from cost of under and overage along to set coordinated service levels along supply chains.

Calculating from risk and inventory pooling and multi-echelon approach will help you reinforce the right inventory levels for your supply chain. What's more, you can also use your model to identify areas of capacity, lead time variability and even manufacturing weakness to prioritize improvement.

Approach To Supporting Business Growth With Big Data Analytics

1. Business strategy with congruent and reinforcing operational capability for the targeted market segment is always key to its success. This should always be the first step. This guides the allocation of capital for focus and accepting trade-offs. Companies may decide to focus on providing the most relevant designs to their customers to entice them to buy, or be able to provide customers with wide range of products to meet their needs.

2. Develop a theory of cause and effect to assess presumed drivers of the business strategy. This requires someone who is close to business, and understand common financial and non-financial drivers to the business. Sales, costs and investments are typical financial drivers. Return on capital invested, earnings growth and cad flow growth are some more specific financial measures. Non financial measures include customer loyalty, latency, recency, frequency, monetary and product quality measures. Measure these drivers for statistical correlations to see if one's cause and effect theory is correct. There should be experiments on examining theories that will fail. Worse is if one doesn't try at all.

3. Identify activities that employees and customers can do to achieve business goals. If customer satisfaction drives business value, then find reliable drivers of customer satisfaction. If is about speed of processing? Or performance of the funds invested? Perform statistical analysis on these specific measures to ascertain causal effect. Base on this, a company can focus on such measures within control
Of departments and employees to ensure process is quick and effective.

4. Don't forget to re-evaluate your statistics to adapt to changing needs. Customer may need to be engaged in the social network with now compared to before. A bank teller becomes less important than the online experience.

Drying Medela Breast Pump Air Tubes

This has got nothing to do with supply chain, but I found a good way to dry Medela breast pump air tubes that has water or milk seeped inside :) First, put a thread through a needle, the type that you use to sew clothes. Stretch your tubes to let the needle (and thread) travel all the way down using gravity. You have insert and take out to a new times if the tube is wet. Finally, let the needle come out from one end and twirl the thread around tube this way to dry the tubes :)

Customer Analytics for Online Retailer and Blogshops

It is easiest to set up data collection to do customer analytics if you run an online business.

Require your customers to create their account and track the when they log on, duration, pages that they look at, products that they click and of course what they buy.

From the data, you can carry out Latency analysis by checking if customers are taking a long time between consecutive purchases. For example, by having a column of 1st to 2nd purchase, 2nd to 3rd, 3rd to 4th purchases etc, and another column showing the days of the next purchase, one can find trends that the days of next purchase may significantly lengthen after the 4th or 5th purchase, then you can target promotions at this group of customers.

Another analysis is of course Recency, Frequency and Monetary (RFM) analysis. Develop an index to compare R, F and M measures for a sample size and focus on your top, and customers groups you can convert to top customers. Remember to validate your expected profit with a control group. Costs of a promotion also includes inventory capital and storage costs. Per product price and shipping cost may decrease because you ate ordering more.

Oh, and please look at changes in time trends for action base on RFM, perhaps using statistical quality control?

It may be worthwhile looking at variation for your latency and RFM besides averages too for for targeted marketing. Remember to overlay demographic data with location associated with IP addresses too, for better targeting like changing prices and language for different customers.

Responsive & Resilient Food Supply Chain And Logistics

Similar to what Cisco has done to recreate a resilient global supply chain, can we create a responsive and resilient food supply chain through Singapore?

Singapore as a transhipment hub thrives on breaking bulk and creating a wide variety of assortments for the region. It is critical that the inflow to Singapore be resilient to minimize cost over huge economies of scale.

How do we create resilient inflows? For food supply chain, one way is to be able to respond quickly to changes in food harvesting conditions. One practical way of going about this is to overlay food harvest locations over the world and and current supplies on the world map. One will then see where supplies are from currently and where are the alternative supplies. Overlay this data with sea/airfreight lead times. This will allow importers to adjust their reorder points quickly in bad weather affecting harvests. Overlay real time weather data for buyers/purchasers to assess impact to inflows and quickly identify alternate sources.

Algricultural produce regions and volume can be found at US agriculture records. Freight lead times can be gotten from maritime data sources. Weather as natural disasters now come in geoRSS feeds. Experienced buyers will be able to provide ratings weather events as a risk factor that one can multiple volume with to assess potential impact. If potential impact is large, the buyer can consider alternative supplies.

With historical data, one can also do a regression on weather patterns and food harvest yields and prices. For more accurate risk factor value.

Responsive Online Retail Using Google Insights and Trends

For online retailers wishing to quickly capture search trends and insights to decide which designs to develop and promote can certainly use Google Insights and Google Trends.

Below is a tabulation of rising searchings in Google Insights for 7, 30 and 90 days. For example, gangnam style is 60% times searched more in the past 7 days than 7 days before. Breakout means that it is searched more than 5000% times more than the previous period. One can easily download, or even poll Google Insights data to track rising trends. For example, if gangnam style suddenly becomes very popular in the past 7 days, you can have your own gangam style product design to capture impulse buys.

Similarly, I tried to use Google Trends to search for supply chain and logistics. Clearly, logistics as a search term is more popular. Someone is South Africa, Singapore, India, UAE, HongKong will likely see my posting if I use "logistics" in my post. There are also trending issues too, to complement Google Insights. In fact, you do not have to key in anything in the field to see what are the top overall searchs on the web.

Overlay this with Twitter posts for even better trendspotting? anyone? :)

Serializing Products - Aligning Proprietary Serialization with Global Open Standards

Many companies are not familiar with how to use the Global Trade Item Number (GTIN). Even for smaller companies who have their own serialization practices, it is still good to know how GTIN does it so that proprietary serialization approaches can be subsequently matched onto GTINs when business grows.

Always try to get the company prefix with the lowest number of numbers possible. It can range from 4 to 6 digits. As GTIN (whether EAN 13 or UPC 12) has limited digits, try to use just 4 digits for company prefix so that you can have the rest for your product type, colour, size, etc.. identification. You can use '1' or '2' to differentiate between products or '10' and '20', just in case you have new in-between products.

Your GTIN can be for the smallest packing possible, and subsequent packing (or SKU) to use another GTIN.

The GTIN can be associated with various product characteristics in your database.














Consider layering the ITF-14 Data Structure if you can't embedded it in GTIN. Add 1 to 8 in front of GTIN to differentiate packaging and aggregation (item, case, carton, pallet) layers.

Approach to adding in packaging levels in front of GTIN using ITF-14 standard.

Examples of application of ITF-14 on different packaging units below.

Spcficiations for bar code type, size, placement and quality all depends on where the bar code will be scanned. it could be at Retail point-of-sale, distribution, marking and repackaging locations.

Below is an approach to selecting the right serialization and bar code standard.

Remember to update GS1 your production sites too, so that they can relate the Global Location Number (GLN) to your GTINs for traceability.

Now that you have your GTINs (or even GLN, ITF-14s) in place, you can then track these products along your supply chain. Tracking and tracing allows you to measure and improve your supply chain performance.

Responsive Supply Chains For Blogshops

From selling fast fashion, many blogshops are offering customized products tailored to individual taste. Does that mean that each product has to be individually manufactured?

Certainly not. From the principles of Design for Logistics, some blogshops apply the principle of economic packaging and transportation for buying in bulk (sometimes by themselves and carrying it as hand luggage).

For some blogshop that customize products though, there are opportunities to batch produce, and standardize products as much as possible in a manufacturing process, and differentiate only at the end. For example, do you sew a bag first or print customized design on it first? your manufacturing process time is certainly shorter if you sew the bag first. The end result? the customer will be delighted that you are sending the customized product faster than they thought. You can also track and encourage customers to tag the company on Facebook or Twitter, and providing a bar or QR code for them to scan to retrieve the specifications easily. This helps promote the product, source new product ideas, and serialize products to track and trace the manufacturing specifications (e.g. zipper configuration or velcro, size? kind of stitching, etc...) for warranty purposes.

Additionally, one can also use concurrent and parallel processing principles to shorten production lead time. For example, can you print on both sizes of a pouch at the same time then sew it together rather than one side at time?

With Twitter and Facebook API we can even try to capture the popular text and designs to push possible designs to customers.

Machine Utilization For High-Mix, Low-Volume Operations

We understand that Queue Time, Flow Variability and Process Times affect process flow variability. Always remember to add up the utilization of the same machine base on the products using it. Except for utilization = arrival rate x effective processing times for mutiple products for the first machine, you always have to consider queue time, process times and the flow variability of previous departing flow for subsequent machines. Use the correct CTq equation for single or multi-machine scenarios too. Then compare the results with Best Case, Practical Worst Case or Worst Case.

The below pictures gives a good approach to reviewing operations if the results are close to worst case.

Digitizing Shipping Documents For Speedier Supply Chain Information Flow

Want to relate incoming invoices and other shipping documents with internal production and outgoing shipping information?

The fastest way is definitely EDI or some form of electronic information exchange. However, many companies, especially smaller ones, still prefer to issue hardcopy documents. So what do you do?

There are many OCR softwares available in the market, but none can help users OCR their documents easily and quickly associate with new data, like say on a 128 bar code or QR code.

I have created www.transhipmentocr.appspot.com to help users OCR their jpg, bmp, png and gif pictures. The application can be easily customized to pick up specific information in multiple documents, and associated with other product/shipping information from my barcode 128 decoder at www.transhipmentflow.appspot.com to do it.

Continuous Improvement In Delivery Performance & Product Freshness

As long as you give me a good price, I can accept deliveries within a time window. This holds true for many companies.

To minimize cost, deliveries are planned to maximize capacity and minimize cost. As such, delivery coordinators will look at say, the number of pallets for customers and assigned the larges trucks to the customers taking the most number of pallets first. The space available is noted for small number of pallet deliveries to the same area. By considering both capacity maximization and route, these deliveries then minimizes cost. Companies usually have limited cold trucks and manpower, so cold trucks are usually assigned to the biggest customer, and/or customers that are most particular. When it is hard for one person to unload products, an assistant is usually assigned. It is also hard to accommodate to specific timing requirements unless the volume and pricing is right.

There are still usually many loose cartons for city deliveries. This is when you can cluster by capacity or location again using small trucks, as it is hard to turn using bigger trucks. In city deliveries

So how do one ensure that delivery schedules are continuously planned to minimize cost? There are 2 ways, one is to set up KPIs for delivery coordinator/driver measure their cartons/delivery cost, break down their delivery cost into fixed and variable transportation cost components. Second, collect travel, product handover times and products that are sent to these customers for continuous improvement.

One way to do this is to associate invoices/delivery orders with delivery personnel and trucks. You can use any GPS system to then collect travel and product handover times by deliver personnel and trucks. This way, any fixed and variable transportation cost can be assigned to specific trucks and even delivery personnel. Measure capacity utilization and overall route timing. Investigate exceptionally long handover times.

What is more associating invoices with delivery personnel and truck is the first step for enhanced track and trace. Invoice information are linked to product sources. Time stamp for delivery start and reach times can be measured to ensure product freshness and traceability.

City Deliveries Approach

City delivery planning is affected by truck requirements (e.g cold or open trucks), customer timing, unloading bay, customer location waiting time (to handover goods), customer location and truck capacity constraints.

A few checks on current routing and capacity of your delivery trucks should yield some opportunities:

1. Check utilization rates of the trucks. Due to historical reasons, some drivers/delivery assistants may focus on delivering to some customers. You can certainly use underutilized trucks to deliver more in one trip. Delivery reach time constraints? Use an assistant and/or do not promise a specific arrival time for customer.

2. Do same trucks go to the same location that can be served by a bigger truck, or better still, do the same trucks have ample capacity that can deliver for all locations. Delivery reach time constraint? Use an assistant and/or do not promise a specific arrival time for customer.

3. Dynamic deliveries due to not being able to control orders? Make sure that these customers are high margin customers. If not, better set cut off times for orders and processing to be done so that delivery routes can be planned to be as economically as possible.

4. Even for highly utilized trucks, are there established procedures for delivery coordinator quickly check available capacity on trucks and consolidate deliveries for days when delivery volumes reduce?


An independent approach to systematically overcome these constraints are as below:
1. Tackle truck requirements, customer timing, unloading bay size, and waiting time to handover goods first. Cluster all your customer timing delivery and unloading bay size constraint points. Use the biggest trucks possible to serve these points. Use next biggest truck of you are not able to serve the locations after factoring time to move to location and waiting time to handover goods. Base on the space available after delivering to timing stores, use space filling curve algorithm to send to the next nearest store.

2. If you cannot meet delivery times after doing #1, use smaller trucks for those delivery points with long waiting times for handover of goods to customer. These smaller trucks may allow you to go straight into carparks and deliver from there rather than from congested loading bays that contribute to long handover time for goods. Alternatively, consider using additional staff. Due to unloading bay constraints, time to handover goods may be significantly shorter with 2 staff.

3. Tackle customers with no delivery timing constraints. For rest of the stores with no timing constraints, use the biggest trucks and space filling curve to route to customers with similar loading bay constraints. Then the next sized trucks.

This approach assumes that it is marginally cheaper to serve another customer at a different delivery point using the same truck, than using the smallest truck possible to do many to and for deliveries from a distribution centre.

Of course, there are also considerations like driving another truck to take back the cold truck at a customer premises and routing from truck capacity limitations.

Selling More To Upstream and Downstream Supply Chain Partners

It is common to see companies supplying to both upstream and downstream supply chain partners.

For your bigger customers, it is worth mapping out what kinds of products upstream and downstream partners along a supply chain are taking from you, especially for those customers are serving end customer group.

The very least you can get out of this mapping is you will know what partners nearer to end customers are cooking themselves and not taking from upstream suppliers, and who are buying products just to build on or customize products developed by upstream suppliers.

For supply chain partners developing end products by themselves and not taking from suppliers, you can then run it by your bill of materials (BOM) receipe database to suggest what new products that they can develop. In that way, you can broaden the product range ordered from your company.

For supply chain partners customizing/finishing up on earlier partners' products, you can again run your BOM receipe database to look at what products can be customized nearer to end customers to sell to upstream and downstream supply chain partners. Especially BOM receipes that involves minimal processing and are fast.

Both this strategies help to broaden the SKUs and increase its volume for your customers. It also deepens the relationship between you and your customers along the supply chain.

To enable this, one will have to build up their BOM receipes and link it to their SKUs. It can be done industry knowledge and by trawling the Internet.

Practical Re-order Level Setting

When lead-time and demand variability is variable, it is hard to define a re-order point, even when the cycle service level is clear.

As such, a practical way to set reorder points is to tap on the experience of the warehouse staff to identify out of stock (OOS) SKUs, and to go through the demand variability, lead time, cycle service level to set new reorder points and monitor OOS. The staff may tell you that they previously order the minimum order quantity, or there are highly variable demand or lead times? With experience, you can also set higher safety stock, and hence a higher reorder point for seasonal products.

How do you free up space for higher reorder points? Well, the same experienced staff will be able to ye you what SKUs could be over stocked. You can then calculate a lower reorder point to free up space.

Transhipment Supply Chain Bar-Coding For Track & Trace and Supply Chain Performance

Knowing how we could incorporate possible transhipment points in your suppy chain network calculations to speed up, pool risk to lower inventory cost and postponing customization isn't enough.

There growing need for track and track for sub-components of a finished project for patient/food/consumer safety. As such, there is an increasing need to add in more information on top of current product bar codes.

Besides tracking and tracing, the additional plant and production/expiry date/time information of sub-components can also be used to measure supply chain velocity, quality and costs.

So the question is, how do we add in more information from say, a transshipment hub like Singapore?

How about using EAN 128, or GS1 128 bar codes? It has SSCC, GTIN, Country Of Origin, Best Before etc... even optional fields you can define. It's open standards ensures interoperability worried about the length of bar codes to scan? You can use a QR code to store much more information in a smaller space. QR code specification is free and there are tonnes of free QR code generators around, including a Google API for QR. Multiple products on 1 QR code? No problem, we just need to configure the reader to consider it as separate product if 00,01 and 02 application identifiers are read, as these application identifiers will have unique company prefix.

You can use my web application at www.transhipmentflow.appspot.com to decode your EAN 128 or GS1 128 bar codes into its application identifiers and know how much more information you can add if you convert to using QR codes.

Consumer Analytics To Complement Marketing and Sales Strategies

Regression to identify significant drivers of sales, forming hypothesis with significant factors, then using naive bayesian classifier to test hypothesis is quick and reasonably good approach. Especially so for hub and spoke operations in Singapore where forecasting regional needs are challenging. It can also be used to compare performance between stores and where new stores should be opened.

Naive Bayesian classifier has been found to perform well against decision trees and neural network classifiers. A good example of naive Bayesian classifier, including Laplacian Correction, can be found at http://cis.poly.edu/~mleung/FRE7851/f07/naiveBayesianClassifier.pdf

Marketing budgets may be allocated base on rate of change of probabilities with time, so the above approach helps companies to obtain quantitative comparisons weekly or every 2 weeks. Even for probability in the first pass, the difference in null and alternate hypothesis already helps to clarify the strength of the null or alternate hypothesis.

Transshipment Flow Analytics Approach

Adding in a transshipment point to transportation problem is a common approach. Then the transshipment point will allow equal capacity volumes 'in' and 'out' of the transshipment point from different sources to different demand (sink) points.

Base on profit margin (marginal contribution) approach, the demand at sink points can also be modified in the model.

Of course, safety stock will be reduced with reduced lead time and propagation of variability. The cost of pooling variability in a transshipment point like Singapore can be compared to cost of holding more stocks regionally.

Slot & Pick By Ascending Sizes Along The Height Of Rackings

For retail products like apparel and bags, it makes sense to slot it by common sizes, or even commonly sold colors horizontally. For example, in the case of shoes, the smallest sizes can be at the bottom-most racks, common sizes at the middle (easy to pick) racks, and larger sizes at the upper racks.

In this way, put-away and picking is not difficult as sizes go up with racks. This also allows more SKUs to be placed along easy to pick level of shelvings/rackings.

Pick List with Bar Codes to facilitate picking

Many companies still generate paper pick lists. It is cheap - there is no need to lug a handheld around or wear a headset.

If you have the product bar code on the pick list, it is probably faster to scan product bar code on pick list than on actual products. As location is usually on the pick list itself, picking errors is unlikely anyway.

It is quite easy to generate the equivalent bar code on the pick list, especially of the pick list can be saved as an excel sheet. You can customize the bar codes you need too.

Online Product Sales Prediction

Good forecasts reduces excess inventory that would require markdowns and disposal. There are also cost of space and time/system used to monitor inventory. The savings are significant when you have a huge number of SKUs and/or carry lots of inventory.

One approach I had developed for an global data science competition is as below. It gives pretty good results. It is easily understandable (keep it simple approach), one can compare the accuracy using root mean square error (RMSE) with your current forecast, and most interesting, evolve your own algorithm to give weightage or overrides base on how sales evolves. I achieve an RMSE of about 1.5 :)

Step 1 - First review all the SKUs its date, quantitative or category variables to decide which variables(columns) to ignore, and which outcome(rows) to delete. With a huge number of SKUs, you certainly can't focus on all of them, so you can apply the Pareto rule. If you only have one or a few SKUs, you can skip this step.

Step 2 - Apply regression on each monthly/weekly/daily sales for each SKU as outcomes using the remaining variables as inputs. Remove non-significant factors and run the regression again to get the adjusted coefficients. If you have more than 16 variables, use minitab, SPSS, SAS or r.

Step 3 - Apply regression equation to only the significant factors to come out with outcomes on monthly/weekly/daily basis. Look at your significant factors with time. Does it make sense and did you get new insights in how your sales are affected by different variables.

Step 4 - Use RMSE to compare this new forecast with your older forecast. If the forecast is not better, adjust using your knowledge of the market using weightage, omitting factors, averages or comparison to multiple of averages.

Step 5 - Add in marginal contribution and time series analysis if you want to factor in profit margins and time trends.

Step 6 - Implement changes proposed significant factors identified from the analysis done the the above steps for continuous, self-adjusting capability.

Step 7 - Synchronize sales with operations and capacity planning.

Write to me if you need more help! :)

Facilitate Picking Using Invoices with ERP systems

Rather than using pick lists, some companies pick products using one ply of invoices. For a distribution operations dealing with a huge variety of SKUs, it is likely that SKU number would be classified according to product groups like (dry goods, chilled or frozen products). To facilitate picking, it may be better for the SKU number on invoices to be shorted alpha-numerically.

For example, in Microsoft GP, sorting by SKU number on invoice is
MS Dynamic GP> Tool > Customise > Report Writer > Reports > Invoice History & New Invoice > Sort > Choose Item number column > Descending

Quick Wins Using Google Forms For Order Processing

Customers can easily use google forms to order, and data to be stored in a format so that its CSV version can be easily ported to another system for invoice generation.

Email alerts can be easily generated when an order is placed. One can also manipulate the item number order to facilitate picking, similar to how you can generate invoices whose item numbers can be shorted for picking straightaway.

Practical Approach To Improve Inventory Inaccuracy

It is common for companies to have inaccurate physical inventory compared to what is reflected in their systems, especially in a high variety, small UOM retail distribution operations in a transhipment flow hub like Singapore.

This leads to:

- time delay on confirm inventory availability as there is a need to check physical stock, rather than generating more sales

- lost sales, lost customers and worst of all, false promises that inventory is available

- higher inventory to ensure that product is available, leading to higher obsolescence

- higher cost of checking with operations and always needing to expedite

A logical approach is to measure cost of these consequence and invest in efforts to dig deep into the reasons for inaccurate inventory and tackle them systematically. This approach to improve inventory accuracy however, is challenging in real-world situations. Firstly, the cost of stock loss is hard to measure as customer demand for each SKU with time/season/promotions. Secondly, most perishable consumer goods distributors allow sales to talk to warehouse operations directly to 'reserve/pick' stocks before pick list is generated. Thirdly, it is accepted that there is a delay in inventory updates. Fourthly, purchasing cost is reduced as certain SKUs are bought in container or pallet loads (reinforcing the acceptability for delay in inventory updates, as there will be enough stock). Fifthly, the multitude of SKUs with different stock loss characteristics makes it challenging for companies to dig deeper into various reasons and collate the cost of different mitigation measures. For example, products that are high value and small by be subjected to pilferage. Products with different packaging sizes may cause inaccuracies from mistakes in picking. Lastly, different inventory accuracy improvement measures escalate cost too.

Rather than collating stock loss and lost sales information, a practical approach to improve stock accuracy is to:

1. Work towards reducing lead time to update inventory. This will encourage operations and sales staff to rely more on system inventory to place orders, and trust that actual inventory is true, or at least closer to the truth. Implement this by trying to get receiving staff to update inventory directly upon receiving. Reserve stock when sales place an order and post out when it is picked. Cutting time to update inventory usually reduces manpower cost to pass inventory forms around too. This will be a quick win that should be enforced as an SOP.

2. With point 1 above done, measure the time reduction in updating inventory and the reduction in calls and paper scribbles operations and sales use to keep track actual inventory, especially for sales in smaller quantities, especially for stable demand items. As this process improvement is instituted for all SKUs, some products may not see improvement due to highly variable customer demands. If the SKU has a long shelf life, bulk purchasing can be implemented to buffer for highly variable customer demands. If it is already done, see of you can send products at high frequencies, tagging along your daily deliveries to pool variability.

3. Try to consolidate orders, rather than allowing daily orders, especially for products with stable demand, pass some savings to customers to encourage bulk ordering rather than piece meal ordering. Reducing transactions this way will reduce mistakes that contribute to inventory inaccuracy. Skip this step if your customers want to order everyday and/or if your business is about customer service through daily deliveries.

4. Then, track system inventory and actual inventory for products with relatively stable demand next. Flat horizontal lines for actual inventory at 0 means there are potential loss sales. Get your sales to note down the quantity in these situations to quantify stock loss/lost sales cost. It may be time to review your safety stock base on variability of demand and delivery lead time.

The above mentioned approach tries to prevent inventory inaccuracies from happening by incorporating focused process improvement and measuring improvements on specific SKUs to see benefits or more accurate inventory. Process improvement is a continuous process, and can also include reducing transactions too. Base on the financial impact of inaccurate inventory, it may be more worthwhile for companies to implement corrective measures like cycle counting (to count faster moving products more often too) and/or have more physical inventory.

If inventory in accuracy is only for a few SKUs, we would want to drill into the source of inaccuracy. Often, there is a combination of reasons for inaccurate inventory. Commonly observed reasons for inventory inaccuracy are pilferage (or shrinkage), transaction error, substitute inventory due to inaccessibility of actual inventory

Pilferage can be known or unknown. Companies can quickly clarify unknown pilferages with spot checks and CCTVs nowadays, and update inventory accordingly.

Transaction error includes:

a. Incoming transaction error - Inventory on electronic packing list is different from what is actual sent, and not corrected in system during receiving

b. Outbound transaction error – Picking/Scanning/Checking wrong SKU

Substitute inventory – The lack of storage space also encourage products to be stored along aisle or spaces meant for movement. This allows pickers to over-ride system directed pick locations. The lack of first-in-first-out flows can easily cause inventory inaccuracy.

The above mentioned reasons for inventory inaccuracy are mainly process related. We also need to layer this with volume related errors for mitigating measures.

Analyzing Application Identifiers (AI) For More Efficient Transshipment Flows

Since bar code is scanned so often, it makes sense to also analyze the many other information that is found on bar codes. I am talking more than just the country code, GTIN and so on.

I am talking about expiry dates, pricing information, batch and other information that can be found on say, a GS1 Databar. It is scanned to track product and location anyway. Analytics on remaining stock on warehouse can highlight expiring items, a cheaper priced product remaining, or what weight of product is not sold. The supply chain partner can then react quickly to the information to reduce mark-downs and expired products.

A list of AIs can be found at http://www.databar-barcode.info/application-identifiers/

Active analysis of bar code information and action will help transshipment hubs like Singapore add value to our partners.

Using Data Mining Measure of Lift To Prioritize Layout Elements

We all know layout of products in a retail store is important. It draws customers into the store, guides them to paths and hope they buy more.

How do we plan a layout to maximize sales? It is usually a mixture of art and science. Some use gut feel base on historical sales of complementary products, some also rely on planograms to develop higher sales from pick-faces. While these are good for smaller layouts and specific shelves, options and opinions may be divided when it comes to positions of different category of products and their relative location to each other. This is where a combination of lift (a measure used in data mining) and relationship chart can come in.

Lift takes into account support and confidence measures in data mining. Support is the probability of a final outcome from all transactions. Confidence is the chance of an outcome given a supporting outcome. Categories with higher lift will take the highest Total Closeness Rating (TCR) used in relationship chart for layout. Presto! You can know locate the category with the highest TCR value first! :)

By locating products close together, trans-shipment flows through Singapore will certainly be faster.

Simple Track & Trace Web Application using App Engine

I have created a simple track and trace web application to anyone to :

a. Associate bar code to a location (http://trackandtraceanalytics.appspot.com/)

b. Check location (http://trackandtraceanalytics.appspot.com/find)

c. Retrieve carton from location to free up location (http://trackandtraceanalytics.appspot.com/scanout)

The text fields “jumps” and “submits” data to webserver automatically, so you do not need to press submit at all. There are also checks on whether there is a location associated with the bar code or not.

I am thinking of adding a page that lets you configure the bar code text fields, and visualize location capacity using bar charts from Google Chart API. Think that it should be more of a track and trace than another warehouse managament system

Let me know what you think?! J

Extending Value Stream Maps For Software Implementation Opportunities

How can a company looking to scale up operations and prepare for the future know if WMS or/Order Management System and order management system is more useful for them than ERP?

All systems should facilitate process flow, and one's process should reinforce business strategy. A balance of speed, quality and cost makes one's process unique. One's performance improvement approach, like using value stream map, should take these elements in account beyond process improvement however, how can a value stream map highlight gaps in information flow that makes software implementation imperative?

One way is to use process boxes to measure process times, quality, manpower for information flows as well. That is, rather than having process boxes at the bottom of a value stream map, have similar process boxes near information flow lines in a value stream map as well. In this way, you can use a single value stream map to pioritize software or the usually process improvement opportunities. More importantly, being clear of your current information flow process times allow you to measure new process times.

Of course, if you have a good sense of what you want, you can go ahead to implement whatever software you think is useful, it is nevertheless still very useful to have your process documented and measured for benchmark, adding new customers and development of new services. Expand your value stream to cover financial flow and sales as well so that you know clearly the trade-offs between functions.

How about cheaper alternatives to softwares? There are plenty of cheaper alternatives around, using handphones as bar code scanners, and customizing excel are some examples. Cheaper, customizable softwares is attractive in its own way compared to established systems with lots of company references.

Frequency Of Ordering By Store versus Out-of-Stock at Distribution Centre (DC)

We know that ordering and receiving products often reduces safety stock at the store and at DC because the lead time is shorter at store, assuming lead time to DC is unchanged.

What about the cost of ordering and picking? Wouldn't it be more expensive to order and pick the same product again at the DC? Especially picking when the picker will now pick in smaller quantities.

Well, it depends on what you view as sunk cost, no cost and what is of higher cost.

If there are deliveries are twice or three times a week, and you are ordering once, you want to consider ordering your highly variable and easy to pick products, like cartons of can drinks, twice or three times a week. This is because we can consider deliveries as sunk cost. The store needs to order other products for the 2nd or 3rd delivery anyway so it is marginal cost to order one more product. Picking 2 cartons is about twice the work of picking one carton, so it doesn't matter if the picker at warehouse picks is in one day or in 2 days. That leaves cost out of stock at store to be usually higher, when you factor in loss of goodwill and customer satisfaction.

Besides inventory savings in safety stock, one will also have a higher resolution of demand variation data (2 data points a week rather than 1)to calculate safety stock by pooling variation. More variation data means more confidence in variability and consequently, the safety stock available at DC to meet demand variability from all stores.

Distribution Allocation & Routing Approach For City Deliveries/Pick-Ups

Challenge: How to review delivery operations with multiple trips to minimize vehicles used

Data needed: time trends of pickup/delivery volumes (weight, if truck weigh out instead of cube out).

Step 1: Applying http://www.compareroute.appspot.com/ to find the shortest distance to route all the points for each trip. Base on the route sequence, maximize load before using another vehicle to come up with new routes with possibility lower number of vehicles.

Step 2: Repeat stage one, but do it for consolidated volumes (sum up volume from multiple trips to the same point in a day) from to try and achieve one collection at each collection point in a day (consolidate for the day before). This will try to reduce collection to once a dayrather than 2 to 3 collections daily. Only when vehicle capacity, time, or next process is a bottleneck then we allow more vehicles for 2^nd/3^rd collections.

Step 3: We will probably have a good idea (by using pareto) of which route and collection points constraints the vehicle by capacity, or if time is the constraint. If capacity is a usually a constraint, we can try the low variability collection points collected by one vehicle, and high variability collected by another. If time is the constraint, we can have some vehicles to pick up and hub to max capacity and meet time constraints

Step 4: Run through the vehicle-route assignment from stage 1, 2 and 3 with the volume trends to suggest a responsive approach to review delivery operations with time


Let me know if you have a better idea to solve the same challenge

Point-Of-Sales (POS) For Responsive Supply Chains

Most POS still send data after midnight to a warehouse or distribution centre so that pick list can be generated for the next day. Same products can be picked for different outlets can be picked together this way.

In a competitive retail environment, and dense delivery locations like Singapore, it makes alot of sense to capture sales when it is made and update the warehouse/distribution centre when per-set parameters are breached, like sales per hour for a certain or group of SKUs. Transfer from lower sales outlets can also be activated this way.

Collecting this data also allows variability and consequently, safety stock to be more accurately calculated, compared to just consolidating sales once per day.

Greater granularity of sales information also helps on relate to staffing and other costs more closely. Steps can then be taken to vary cost more closely to sales.

With data collection getting cheaper. I imagine most POS machines should have time stamps on every transaction. Companies can choose to look at daily POS data first to see how their operations can cope. Going forward, looking at more granular data is the way to go.

Paper Orders, Delivery Orders and other documents

Many small SMEs still use paper documents for transactions. Ordering on forms to pass to the salesman and wait for him to bring it to the warehouse is common. Small companies may still find it expensive and inconvenient to bring iPads and tablets to take orders, especially when some customers insist on ordering by forms. In such cases, why don't you use OCR like image to text app on iPhone (http://itunes.apple.com/us/app/image-to-text-ocr/id431757093?mt=8)? Just take a image and send it to the warehouse for pickers to act asap. Records can also be easily kept for subsequent analysis. You don't waste space and effort filing paper records too. OCR is useful for SMEs because orders and requests comes in many different forms. Since it is difficult to standardize orders, might as well standardize how information is captured and archived.

Similarly a signed DO can be OCR-Ed for billing and analysis. In this case, a picture capturing the signature may also be useful.

Let me know if you have other use of OCRs too.

Reviewing Delivery/Pickup Operations

As transportation routing is a NP hard problem, heuristics is usually used to give reasonable answers.

Many heuristics nowadays still ride on lots of codes and inputs. Additionally, companies usually divide delivery by zones and am unsure how they can review their entire delivery/pickup operations.

This is where compareroute.appspot.com will be useful. I had developed this simple application to allow companies to compare their current route with another routing heuristic. The only data needed in this web application is the delivery/pickup address. It works for unlimited points and is scalable globally.

To review all routes within a state or country. Put down all your delivery points in random in the text field. Press submit and let the heuristic tell you the route sequence. Validate it using the map that is displayed in the application visually. Then take your first vehicle to go from point A to B and so forth, until capacity is reached, then you use your 2nd vehicle.

In dense cities like Singapore, clockwise and anticlockwise sequence make a significant difference in routing. In addition, it also makes sense to consider load variability into routes.

Try my other web applications like routeanalytics.appspot.com and nearmyroute.appspot.com

Using iPhone as bar code scanners

Wondering if you can use your smartphone as bar code scanners in warehouse? After all, warehouse management systems is all about associating location bar code with product/carton/pallet bar code. Now, do we need ruggardized, industrial grade scanners and software? Maybe yes, but maybe not, depending on scale of operations and product one is handling.

Try Kinoni or Tapforms.

Kinoni is available in all smartphone platforms and connect via wifi to a desktop or laptop. I should try how it works on 3G.

Tapforms is very interesting too as it allows one to save bar code scans into local smartphone memory for sync-ing later.

Of course, there are refinements like autoline feed capabilities you can use with Kinoni. For example, you can to receive my scanning two bar codes - product/carton/pallet bar code and location bar code, whereas for picking, you want to be directly to pick and scan the product/carton/pallet bar code to deduct inventory.

Best of all, these 2 apps are free! So this option is at least worth a look for most small and medium sized enterprises.

Quick Wins in Process Improvement

I have shared how overworked SMEs can improve their internal operations by incentivizing ordering from customers and changing ordering quantity, frequency and consolidating deliveries suppliers earlier.

We all know ideal, technology driven solutions for companies, but it is the quick wins for companies that helps them get buy in for longer term supply chain performance improvements. Below are some common quick wins:

In terms of internal operations, many improvements can be gotten from imposing cut off times or ordering so that picking can be done in a consolidated manner.

Cost of picking if the cut-off time is not adhered to is additional time the picker goes to pick. Company can measure the additional cost of picking with the profits they are making so make sure that it makes business sense. Of impose additional charge of late orders.

Related improvement with cut-off time would be to reduce many points of contact with just one or two. In this way, there will be less need for communication between many parties over the same processes. Communication between too many parties wastes time and increase opportunities for misunderstanding.

Multiple entries of the same data is also another quick win. Setting up email ordering template and most often ordered items (with empty rows below for ad-hoc items) reduces multiple entries by encouraging right information from the source itself. It can also be sent to suppliers for their reference and record.

Another quick win would be to try to have quality control at source instead of at the end. We all know costs are high for low quality product to end customer. Quality control at source encourages staff in line to check and be responsible for their work. Very often, getting staff to sign on their work or sheet for a product helps improve quality. Any complaints later on can be traced to the staff in the related process for improvement instead of the end QV staff who probably do not know better what to improve.

Lastly, information flows can usually be streamlined. Whether it is duplicate forms to make it clearer for operations, writing or attaching needless information, time saved from quick wins can usually be gotten.

Applying Propagation of Variability for City Deliveries/Pickups

So far, all transportation routing algorithm and heuristics assumes that delivery/pickup performance is the same whether one traverses the route in a clockwise or anti-clockwise fashion.

In a city like Singapore with lots of buildings, time spent at a delivery point can be much longer than point-to-point. If time spent at delivery points are more variable going from clock wise to anti clockwise using propagation of variability approach, then one can decide if the clockwise or anti-clocke wise routing is superior.

jQuery to create superior Excel-like tables on webpage

There is a project need to create an excel like spreadsheet on a webpage but with superior predictive capabilities. Like typing postal codes to retrieve company names.

jQuery can do just that.

We just need to maintain a separate table of the company name with the corresponding address and postal code. So that when someone types in the company name, we can use the jquery's ajax capabilities to pick up the corresponding postal code and show it in the next column. Street name and unit number will show in the next two columns.

If the company name is not found, then the user have to type in the postal code, street name and unit number for the first time.

Information on creating an simple excel table using javascript jquery can be found below:
http://stackoverflow.com/questions/2185636/excel-like-application-in-javascript

Mail Supply Chains

It is a widely known fact that the postal service is value-for-money, relatively fast and is reliable.

With the emphasis on one-piece flow to balance supply with demand, my companies and small businesses can use our global mail infrastructure to reduce their own cost. Packaged foods, clothes, sauces to iPhones and iPads can all be delivered with bubble wrap protection in mail.

Companies might want to split their deliveries to use mail and share savings with their customers. Delivery space in their trucks will be freed up to do more businesses.

Vacuum sealing machines for items containing mostly air could be worthwhile investment, especially for relatively more expensive clothes, pillows and beauty products.

Google OCR API for Small & Medium Enterprises

Paper documents still often generated for deliveries and sales. For example, a small hawker or provision shop placing orders still prefers a hard-copy purchase order that he can refer to when goods arrive. Similarly, many receiving staff or QC still wants the handy printed delivery order and/or purchase order to check physical accuracy of goods, then chop and sign to return to delivery person.

Though we foresee that notepads and electronic papers will be available in the future, it will take some time for habits and preferences to change. Just think about how we still ask to check a physical copy of receipt when we buy stuff, then checking using SMS or
Email.

Couple this with the many invoices and delivery orders a company gets from its suppliers to staff purchases, there could be a good case to look into Google OCR API. Companies can generate insights from photographs taken from signed delivery orders to generate invoice straightaway, or orders written on paper.

OCR is not new, and is already used by companies to capture truck number plates.

Perhaps having a order form for customers to order. Then take a picture for OCR processing for supply chain efficiency is a good compromise between usual practice and changing technology overnight, especially for the long tail of customers and suppliers small businesses serve.

An article on how demo of Google API for OCR is as below:
http://googlesystem.blogspot.com/2009/09/google-docs-ocr.html

Design Intellectual Property Protection Along The Supply Chain

For many in product design, there is a need to the product to generate sales and reduce per unit cost. At the same time, this raises the risk of someone copying the idea and design. So how does one reduce the risk of copying as they share the product to generate sales?

There are various options to reduce the risk of someone copying and selling. One obvious way is to patent the design. Another way is build a good volume in a lower cost location, so that the lower cost will deter potential counterfeiters.

Besides patents and industry knowledge on whether it is easy to create the same product, we can, and in most cases, should add product performance specifications, quality guarantee and serialization layers to deter copying.

By performance specs, you could clearly spell out the weight, rate of work, and size clearly. It is hard to create something with the same combination of performance. This is even more difficult if it is a product that can withstand harsh weather and drop environments.

In terms of quality guarantee, providing a 5 year 100% parts warranty will also be another layer of deterrent to potential counterfeiters. Providing the guarantee also allows one to learn about how your product can be improved. I think the cost of carrying additional parts in your house is minimal compared to the added assurance to beat counterfeiters.

One can also couple quality assurance with serialization of product to link to each buyer from the onset. One can verify each request of parts exchange (from your product warranty) by checking that the buyer details matches with the serialization given to it. The buyer can sign up for the warranty online (you can create this quite easily on a website) after he receives the product, and you can give the customer another code to authenticate with the product serial number that you kept, that is reference to this customer originally. One can also check specific details of the buyer when they file a part warranty claim.

Marginal Contribution For Bundled Products and Planogram Analysis

Marginal contribution approach for retailers to decide what to stock with limited space also applies to bundled products as well. One just have to consider the cost, selling price, salvage/mark-downs, demand and demand variation of the bundled products.

One can also consider other "products" that makes up the assortment. One just have to include the same details in the calculation. Cost of renovation to deliver a certain ambience can also be included.

If you have a large retail store with wide assortment. You may want to complement this approach with planogram analysis, as planogram analysis can give you better combinations of product layout to achieve higher margins contribution.

Use Slip-sheets To Load Instead Of Manual Loading

If you are still using manual labour to load goods on trucks, do consider using slip-sheets.

Slip-sheet is relatively cheap compared to labor, especially when you can load pallet-full of goods at one time compared to manual loading.

You can also get your suppliers to load using slip-sheets too. Savings can be shared.

A quick win for productivity.

JIT/Vendor Managed Inventory vs Customer Ordering

Your retail outlet ordering too much and your other retailers order more just to buffer? Then products become expired or obsolete with time?

A clear approach to reduce waste and capitalize on inventory pooling is to do Just-In-Time (JIT) inventory.

A practical approach to do this is to focus on products that have stable demand first. Do a parallel run to compare what the retailer is ordering vs what JIT will propose by safety and cycle stock analysis. Consider inventory cost saved throgh pooling at a central warehouse, ordering cost, production synchronization cost and space saved. How the space freed at retailer can be used for products that can generate more revenue.

Approach to Price Online Sales in Buckets

Problem - What is the basic price per volume that a logistics company with online sales can charge to cover delivery cost?

Approach

Step 1: The logistics company with online sales need to share their 2 or more most common box sizes. There will be a smaller box (let’s call it volume x) and bigger box (volume y)

Step 2: The logistics company with online sales can also tell us the volume (as in all the length, breadth, and height) of their deliveries for online sales every day. We can then find out the volume for each product that is delivered.

Step 3: For each delivery volume every day, sort by volume. Using the sorted data, we can then check how many of this volume fit in smaller boxes (with volume x each), the rest will be by bigger box (volume y). Another bigger box is used for the next product if the volume of the previous product occupies more than half the bigger box previously.

Step 4: We can do it for say a few months to get a statistically significant data and identify trends

Step 5: Show trend data and discuss with the logistics company with online sales projected in shipments to confirm the future number of smaller boxes and larger boxes.

Step 6: Base on either future projected combination of smaller and larger boxes, find the volume.

Step 7: Compare the volume found in step 6 with the lowest volume found in Step 4. Decide on the volume to use to calculate the minimum price per unit volume with the logistics company with online sales

Step 8: Get the cost of each delivery from The logistics company with online sales, factor in projected fuel increases, etc… and divide it by the volume decided in Step 7. Base on this cost per unit volume, the online store can charge in 2 step sizes or more. Presto, we have the minimum to charge using per unit, per small box or large box J

We are essentially putting in more space (volume) with 2 or more common box sizes for the logistics company with online sales to price it more easy in a step rate, and yet still cover cost, or even profit from it by leveraging on online consumers’ purchasing mentally.

A parallel run of this approach is needed to ensure that the number of small and big boxes used are accurate enough.

Note: If more than 2 box sizes, we can approximate the number of each boxes using relative volume of each box

QR CODES FOR ONLINE AND OFFLINE USE

1. We can use the same QR code to contain information without accessing the internet, and access the internet by containing basic information without using internet access in a URL

2. In this way, we can already retrieve the information without accessing the internet. Depending on the size of the QR code, it can store from 300 to 4296 alphanumeric characters.

3. When we use the URL to access the internet, it can point us to google forms. I have created my own google form page with customized text of “stockceck” with the link https://docs.google.com/spreadsheet/viewform?formkey=dHNLY2FUX0FSLVJJbXlNNjcxVXZ2ZGc6MQ&entry_1=stockceck , the corresponding QR code is below

4. In fact, we can create our own QR code for free using google charts. I just created one with text “YouRulesforever: with the link http://chart.apis.google.com/chart?chs=150x150&cht=qr&chl=YouRulesforever&choe=ISO-8859-1

5. Being able to create QR code with a url means we can develop applications using QR codes with some simple programming.

6. This capability can also complement existing GS1 bar code standards.

7. QR code information and application examples can be found at http://www.denso-wave.com/qrcode/qrfeature-e.html

Changing Supplies Delivery and Customer Orders to Relieve Staff of Workload

Met companies that shared that their own internal staff is very stretched from internal improvements and current work. How do they get suppliers to deliver and how customers order such that they relieve their staff of workload?

Some ideas of relieving internal staff from workload is to incentivize change in behaviour by suppliers and customers through savings. The savings from internal staff processes can be passed to suppliers and customers so that your internal staff can do higher value added work. The two main approaches and savings are described below

1. Get suppliers to deliver to me such that I relieve workload from staff

- Pickup/delivery consolidation from various suppliers such that you receive one load that facilitates receiving and put-away

- Bulk order from suppliers, especially those fast moving but small enough

- Get suppliers to bundle products that will help me fill orders more quickly

2. How customers order such that I relieve my staff of workload

-Encourage customers to order in bulk through delivery savings

-Help customers order in bulk by giving them a discount through delivery savings

-Give customers a discount by looking at their ordering pattern and stocking up for them

Seamless Mobile Payment & Fulfillment Capability

1. Develop your own website with PayPal payment option - Add in pictures to photobucket or flickr.com to get url

2. Create your free QR code for free with numerous free QR code websites out there.

3.Pay using credit card or PayPal account

4. Operations will receive an email after order confirmation to pick and complete the fulfillment

5. You can also see the order and keep record of your business in your paypal account