Excel, Purchasing, Supply Chain Management

In all likelihood, your first encounter with a balanced scorecard would have been your report card, where individual school projects, tests and exams were given a certain weight in accordance to their level of importance. In purchasing, this tool is put to practice in supplier selection and supplier evaluation. It is used to avoid risk, reduce costs, mitigate rogue or maverick purchasing and ultimately aid in the selection of the most qualified good or service provider. Performance metrics are listed in columns and are then scored using a standard numerical value range often being 0% to 100% or 1 through 10. Each individual score is then multiplied by the weight determined by their level of importance and are summed at the bottom, often converted into a percentage format. This is part 2 of a 2 article series that will provide the reader with tips and best practices for the creation of supplier evaluation balanced scorecards.


Now that you have selected your supplier(s) using the points outlined in part 1 of this article, titled Creating a Supplier Selection Balanced Scorecard in Excel, your supplier evaluation responsibilities are far from complete. Suppliers must be regularly tracked to ensure that KPIs including price, quality and reliability, or whatever metrics are important to your organization, are available for evaluation. Your Supplier Evaluation Scorecard will be broken down into two separate tables: your Supplier Evaluation Scorecard and your Historical Tracking Scorecard.


Supplier Evaluation Scorecard


The Supplier evaluation table will include columns possessing the following titles:

  • KPI Groups (optional)
  • Key Performance Indicators (KPIs)
  • Performance Target (optional)
  • Measurement
  • Acceptable Score
  • Score This Month
  • Variance from Acceptable Score


KPI Groups (optional) and Key Performance Indicators (KPIs)

KPIs include a description of the metrics used to evaluate the success of the good or service provider. The KPIs can be grouped into a KPI Area (optional) column that proceeds it using KPI groups such as Customer Service, Cost, Quality, etc.


Performance Target (optional)

The optional Performance Target column includes the quantifiable goal you wish for the KPI row to achieve. While it is nice to be specific in producing your supplier evaluation balanced scorecard, the point is to spend your time evaluating, as opposed to producing the most detailed document. So use the Performance Target column with caution.



The Measurement column describes precisely how you will quantify the score associated with each KPI.


Acceptable Score

The following column titles are self-explanatory. The Acceptable Score is the score that you would accept. This is the passing score, not necessarily a perfect score.


Score This Month

The Score This Month column is where you do the actual scoring. The time interval does not have to be monthly. Use the evaluation time interval that is appropriate for your situation. It is important to remain constant in your scoring for the purpose of incorporating this data with the Historical Tracking Scorecard that we will get to in a minute.


Variance from Acceptable Score

A simple =Score This Month cell – Acceptable Score cell formula will deliver your Variance from Acceptable Score for each KPI. The resulting value is what will be used in your Historical Tracking Scorecard.


Historical Tracking Scorecard


The Historical Tracking Scorecard is where your historical scores are recorded and evaluated. This table can either be placed on the same tab, or on its own separate tab. The table is a stripped-down version of the Supplier Evaluation Scorecard including the optional KPI Area column if you added one, an identical KPI column, and your time interval columns. As this example uses months, we will add 12-time intervals to evaluate. Of course, you can evaluate weekly, quarterly, yearly, etc. Each time interval, copy the score from the Variance from Acceptable Score column in the Supplier Evaluation Balanced Scorecard and paste those figures into the time interval column that corresponds with it in the Historical Tracking Scorecard.

To make the Historical Tracking Scorecard more visual: turn it into a  line chart by selecting the entire table’s containments and clicking on the Insert Tab ==> Chart ==> Line

Right click inside the chart and click Select Data. In the Select Data Source menu, for each Legend entry, highlight the name field and click the KPI cell (start with the first KPI). Then highlight the Y values field and select the entire time interval ROW that are associated with that KPI, all 12 months in our example. Do not include your KPI name. Repeat this step for every KPI. For the Horizontal (Category) Axis Label field, highlight the row cells that indicate your time intervals (month numbers/names, quarter names, etc.) You now have a beautiful chart that will help visualize your historical scores for each KPI. Customize the chart according to your preferences.

Now that you have completed your Supplier Evaluation and Historical Tracking Scorecards, it is vital to spend the time to fill them out within the specified time interval (weekly, monthly, quarterly, etc.). If for whatever reason you miss a time period or neglect to analyze the evaluation data you spent time making clear and easy to interpret, you will have wasted the time you spent producing the scorecards. It is also crucial that you remain constant in your scoring standards. Otherwise your supplier’s performance data will be distorted over time.



Excel, Purchasing, Supply Chain Management

In all likelihood, your first encounter with a balanced scorecard would have been your report card, where individual school projects, tests and exams were given a certain weight in accordance to their level of importance. In purchasing, this tool is put to use in supplier selection and in supplier evaluation. It is used to avoid risk, reduce costs, mitigate rogue or maverick purchasing and ultimately aid in the selection of the most qualified good or service provider. Performance metrics are listed in columns and are then scored using a standard numerical value range often being 0% to 100% or 1 through 10. Each individual score is then multiplied by the weight determined by their level of importance and are summed at the bottom, often converted into a percentage format. This is part 1 of a 2 article series that will provide the reader with tips and best practices for the creation of supplier selection and supplier evaluation balanced scorecards.




You will want to create your balanced scorecard in Excel. While you could print a basic table in Word or even draw one out by hand and calculate the scores manually, you will be missing out on the analytical opportunities outlined in these two articles,and the digital sharing functionality with your colleagues, while increasing the possibility of human error. Your Excel scorecard will essentially be a dashboard, with colour notifications by way of conditional formatting and historical tracking with automated graphs if you want to get fancy. If creating dashboards in Excel is not for you and this all sounds intimidating, you’re in luck! I have created the following Purchasing Coordinator evaluation scorecard for your use in hiring someone to build one for you. See how useful balanced scorecards can be?



Creating a Supplier Selection Balanced Scorecard


To build a scorecard to help in the selection of a supplier, you will want to begin by identifying the metrics considered to be of importance to your organization relating to the good or service the potential supplier is to provide. This is often associated with the business problem they are to solve. A more complex product or service will likely require more performance matrices than one that is less complex, but don’t get carried away. You do not want to waste your time creating and evaluating metrics, so 5 to 8 should do. List them vertically, assigning each metric to its designated cell in the performance metric column. You will input your potential suppliers’ names in the top row of your table. This should be a relatively short list as well, as the scorecard is designed to identify the most qualified provider according to the needs of your organization.


Each metric now has a designated row. The cells of that row under each candidate name is where the score that particular candidate achieves for that metric will be input. This will generally be in the form of a range or a binary Yes/No input. It is important to remain consistent in the range you use to evaluate each row throughout your scorecard. A score of 1-10 is a good idea. For a Yes/No selection, you have a few options:

  • Input 10 to equal Yes and 0 to equal No
  • Indicate “Yes” to equal Yes and “No” to equal No
  • Insert a check box or radio button.


Consider incorporating conditional formatting to bring attention to a particular score range. For example: make the score cell turn green if the cell’s score >= 8, yellow if >=4 and <8, red if <4. For Yes/No or checkbox/radio button cells you can use conditional formatting to make the cell turn green if Yes or if the box is ticked and red if No or if the box is not ticked.


The bottom row is where the total score is calculated for each candidate good or service provider. This is where your SUM formula will go. Sum each candidate’s column, while assigning a percentage or decimal point to each performance metric, giving the more important ones more weight. Note that if you ranked your metrics using a scale of 1 to 10 as recommended in this article, you will want to divide it by 10 before multiplying the cell by the percentage weight. For example:

=SUM(B2/10)*whatever weight you would like it to be worth)+your next equation


If you opted to use “Yes”/”No” text, checkboxes or radio button for your binary metrics, you will have to incorporate an IF Statement into your formula for each one. For example:


=if(E5=”Yes”,whatever weight you would like it to be worth,0) for the “Yes”/”No” text

=if(E5=TRUE,whatever weight you would like it to be worth,0) for a Checkbox or radio button

Each of your column’s SUM formulas should look something like this:



As the supplier selection scorecard is an internal document, the final perfect score does not have to equal a clean 100%, however it will be more comprehensive if it is equal to a common sense rounded number. Now that you have the tools to evaluate your suppliers, the next step in your supplier evaluation adventure is to crete Supplier Performance Evaluation Scorecards.



The purchasing department is in a strong position to leverage cost savings into profit. The profit leverage effect dictates that reducing operating expenses is more efficient than increasing sales. Situated at the beginning of the production process of a product or service, the procurement stage is in an excellent position to reduce overall costs, especially in the short term. This is why companies often resort to reducing headcount when they run into financial difficulties. Reducing operating costs is the fastest way to produce a short-term impact on the bottom line.


With this in mind, let’s talk about purchasing’s profit leverage effect. The following example will display how every dollar saved in purchasing goes directly to the bottom line, and it does so in a way that is more efficient that it would be through increased sales.


Your sales are $120,000 and your cost of goods sold (COGS) are $60,000. Within your COGS is your cost of purchased goods, which is 75% of your COGS ($45,000). Let’s say you reduce your cost of purchased goods through a combination of supplier relations and negotiations by 10%, you would save $4,500. Your cost of purchased goods is now $40,500. Your COGS are now $55,500.

Reducing costs of goods sold decreases your COGS from 50% to 46.25% of sales. Your operating income (net profit) therefor increases by the same amount. Let’s say operating income was $25,000 or 21% of sales, after the 10% of purchasing cost savings, net profit increased by 18% to $$29,736. That’s pretty good!


Now let’s look at what the sales department would have to do to achieve a comparable increase in net profit. To calculate how many more sales dollars would have to be generated we divide the needed additional profits ($4,500) by the operating profit margin (21%). The sales department will therefore have to sell an additional $21,428.57 worth of your product or service, which is the equivalent of increasing sales by 15%. And that does not factor in the marketing costs associated with increasing sales.

Which is easier? Decreasing the cost of purchasing by 10% or increasing sales by 15%? For most companies, that large of an increase in sales with no increase in advertising spend would be an incredible challenge, especially in the short run. On the other hand, reducing the cost of purchases by 10% is very attainable for organizations who have not traditionally managed purchasing as a strategic function.


Key Takeaway: every dollar saved through purchasing goes straight to the bottom line. By contrast, only 21% of sales goes to the bottom line, the remainder is consumed by the costs associated with doing business.



Purchasing, Supply Chain Management

Purchasing supply chain management software is challenging as just like the supply chain, it includes a number of moving parts, departments and changing regions. When you migrate to a new software platform, all your stakeholders are affected. Why do we buy software in the first place? The purchasing decision is not really about the software itself. It’s about the issue that the software will solve, or at least, you hope it will solve.  In the context of a complex supply chain, here are some common goals which those in the position to purchase software wish to achieve:


  • Increased efficiency through the automation of a pre-existing manual business process
  • Offer new functionality, helping you do more or increase your organization’s quality of service
  • Compliment current software platform, so that well-functioning pre-existing systems can live-on
  • Futureproofing, ensuring the software spend down the line is minimized


Traditional supply chain ERP software is corporate organization outward focussed with a high emphasis on stakeholder integration and collaboration. You need to consider a product that will not only integrate into your organization’s business processes, but also those of your suppliers, vendors and other partners which you interact with on a regular basis. Some important considerations for a potential ERP implementation include:


  • How employees within your organization will use the software
  • How they do those activities and processes today
  • How your partners including vendors and logistics service providers interact with you today and if it will change their process. Will they have the desire to / do they possess the ability to interact with the software you are looking to procure.


Some organizations look at purchasing software from a procurement perspective. Their procurement teams might create an RFP and will have particular requirements. They will research potential providers and consult with different departments in a cross functional approach. Ultimately, a document will be created, outlining what they are looking for in a vendor, potentially in the form of a balanced scorecard. From there they will shop around for that software.


Another option is for the supply chain organization within the company to own the software purchasing decision. The organization is familiar with how they get products from purchasing to logistics to customer service to planning: all of those departments will be considered in some way. This organizational focus is in a better position to represent the specific needs of the various business functions. While the procurement approach is often more concerned with making the most feasible financial decision. Of course, the best approach to a major supply chain software procurement decision would be a combination of the two methodologies.


Inventory Management, Purchasing

          Bankruptcy forced the DeLorean Motor Company (DMC) to shut down its Belfast, Northern Ireland production facility in 1982, with an inventory of over 1,700 brand new cars and millions of parts. During liquidation, Consolidated International acquired all of DMC’s remaining inventory. Meanwhile, Steven Wynne, a British mechanic specializing in DeLorean maintenance and restoration since 1982, opened a 40,000 square foot warehouse in Houston, Texas, meant to act as a centralized distribution centre for used DMC parts. In 1997, Wynne acquired all DMC inventory from Consolidated International, in addition to the DeLorean Motor Company name and logo.

          Initially, the acquisition was aimed to support Wayne’s maintenance, restoration and parts sales operations. He and his team have serviced a consistent stock of 35-45 DeLoreans belonging to owners from all around the world since 1987. They also sell parts to DeLorean owners and restorers. As those operations were still not considerably cutting into the new DMC’s parts stock, they began assembling brand new DeLoreans themselves.

         A DeLorean requires roughly 2,700 individual parts of which DMC has over 99%, with no opportunities for traditional inventory replenishment. To fill the holes in their inventory, the remaining less than 1% are rather easily reproduced, rebuilt or procured as used parts. As all original DMC technical specifications and drawings were also acquired, they are often able to reproduce parts using the original specs with CAD/CAM and 3D modeling. This, in combination with their current inventory, allows the modern DeLorean Motor Company to produce a maximum of 500 cars, while continuing its additional pursuit to be the most prominent facility for DeLorean service, parts and restoration.


        Since 2016, the new DMC has employed Acctivate as its inventory management software. Acctivate is utilized for inventory adjustments when parts are received in the distribution centre, whether reproduced or acquired as used parts. Those adjustments are then automatically integrated into DMC’s web store. Acctivate supports and is used to create assemblies (one part containing multiple parts) in addition to sales order management including open and closed sales order monitoring, the creation of pick tickets and sales order printing. Some service orders, such as full frame-off restorations, require 200-300 line items for labor codes and part codes.

We’re able to build a service order pretty quickly with Acctivate, especially with some of these big restorations– Sarah Heasty, Service Manager, DeLorean Motor Company.

         DMC uses Acctivate’s Business Activity Service Billing module to create service order quotes, where separate subtotals can be created for a customer’s engine, transmission, suspension, etc., providing increased transparency. The Business Activity Scheduling module is employed to track labour hours and parts used for each service order. Labour hour tracking helps with DMC’s capacity planning as parts are pulled prior to service, increasing efficiency.


Excel, Inventory Management, Purchasing, Supply Chain Management

Quantitative forecasts are as in-demand as ever. This post provides four solid forecasting options in Microsoft Excel that can be used to predict sales, operating costs, performance and more. The forecasting methods explained include: moving average, the Excel FORECAST function, trendline and regression using the Analysis ToolPak.

Moving Average

A moving average predicts the future value of a time period through averaging past time period values. That forecast can then be used in further forecasting down the line, averaging it with other time period values. The risk in Moving Average forecasting is that it can lag behind a trend.

  1. Select the Data tab, then Data Analysis command button. In the Data Analysis dialog box, select the Moving Average item from the list and then click OK.
  2. Identify the data you want to use to calculate the moving average. Click in the Input Range text box of the Moving Average dialog box. Then identify the input range, either by typing a worksheet range address or by selecting the worksheet range. Your range reference should use absolute cell addresses ($A$1:$A$5 as opposed to A1:A5).
  3. Indicate how many values are to be included in the moving average calculation in the Interval text box. By default, Excel uses the most recent three values to calculate the moving average (i.e 3 month moving average, 3 year moving average, etc.). To specify that another number of values are to be used to calculate the moving average, enter that value into the Interval text box.
  4. Use the Output Range text box to establish the worksheet range into which you want to place the moving average data.

The FORECAST Function

The FORECAST Function predicts a future value using existing values. The predicted value is a y value for a given x value. The known values are existing x values and y values, and the new value is predicted by using linear regression. You can use this function to predict future sales, inventory requirements, or consumer trends.

FORECAST (x, known_y’s, known_x’s)

example =FORECAST(100,A2:A10,B2:B10)

  • X is the data point for which you want to predict a value.

  • Known Ys are the dependent range of data.

  • Known Xs are the independent range of data.


A Trendline is simple way to analyse the trend within a collection of data points within a graph, smoothing out the data oscillations in the process. The trend within the data is then used to forecast future performance.
  1. Create a graph with your existing data.
  2. Right click on any of the data oints within the graph and select Add Trendline.
  3. In the Format Trendline window select whether you would like to forecast/analyse using: exponential, linear, logarithmic, polynomial, power or moving average. Linear is most common. If the data appears to trend towards compounding, try exponential
  4. Click on close.

Regression Using the Analysis Toolpak (ATP)

  1. Ensure Analysis Toolpack is installed (Tools tab, select Excel Add-ins, select Analysis Toolpak)
  2. Select the Tools tab
  3. Select Data Analysis
  4. In the Data Analysis window select regression.
  5. The Input Y range represents what you want to estimate (likely sales)
  6. The Input X range represents the data that can explain your Y (likely unit cost or price)
  7. Click OK

What does all this mean?

In Regression Statistics
Multiple R represents to correlation coefficient between Y and X
R Square represents the percentage of Y you can explain from X. A number closer to 1 indicates low variability and a number closer to 0 indicates a random correlation between your X and Y.

Regression represents the number of independent variables
Risidual represents Total – Regression
Total represents the number of values – 1 (minus 1) (likely the number of active rows – 1)
SS represents Sum of Square
MS represents Mean Sum of Square
Lower % and Upper % means that 95% of the time, your coefficient will be between the lower value and the upper value

P-Value – The lower the P-Value, the less variability you have. The result of 1 – P-Value provides you with the percentage that the intercept will be correct

Cover photo credit: Finance Monthly

Purchasing, Supply Chain Management

In pursuing my Post-Graduate Certificate in Supply Chain Management – Global Logistics, I could not help to draw parallels between the components of SCM and my previous career in participant sports event operations. This indirect background in Supply Chain often led to constant back-and-fourth between my instructors and I. The biggest take-away was that all three segments of Supply Chain Management, which include: purchasing, inventory management and logistics (transportation) are required for a well-managed event, whether on a large or small scale. This article focusses on how mass participant event operations relates to the supply chain management component of purchasing (procurement) and is the first in a series of three articles on the topic. The remaining two will focus on logistics and inventory Management.


An event will require the procurement of various goods and services to ensure a quality experience for their participants. Needless to say, large scale events will require more goods and services than medium to small scale events, while benefitting from economies of scale. As mass participant events often allow individuals to register for the event up until the days, or even the day before that event is to take place, accurate forecasting is required. In the case of a marathon, organizers often use a 3-year moving (or rolling) average of registration numbers as of a certain calendar date (sometimes every day of the year) to forecast based on historical data. For example: on September 1, 10,000 were registered in 2015, 11,500 were registered in 2016 and 11,250 were registered in 2017. Therefor we can forecast that 10,917 will register by September 1, 2018. That data is to be compiled in Excel, where a trendline can be used to forecast sales. You can now order the required goods (food, water, medical equipment, timing chips, merchandise, participant shirts, finisher’s medals, etc.) and services (medical staff, parking attendants, waste disposal services, massage therapists, physiotherapists other contractors, etc.).

The Forecast is Always Wrong

The problem with a moving average is that it will lag behind the trend, so it is advised to utilize qualitative (Delphi method, market research, and historical life-cycle analogy) data in combination to quantitative (historical) data for forecasting purposes. New events are forced to rely completely on qualitative data, as no historical data exists. It is best practice for event operations professionals to order extra quantities (safety stock) to mitigate an unexpected last minute surge in registration (inaccurate forecast), as I can assure you that all hell will break loose if you under forecast participant shirts or finisher’s medals. It is often less expensive to order hundreds of one particular item from overseas that are shipped months ahead of time by sea, than a small order of last minute items shipped by air.

However, in the case of merchandise, you want to sell out. As marginal profit is most often lower than marginal cost per unit, the cost of not selling an item of merchandise outweighs the cost of selling an additional item. Therefore your optimal order quantity is most likely lower than your estimated demand. Chances are you overestimated demand anyway as the forecast is always wrong. Plus the inventory carrying cost associated with excess inventory will cause all kinds of headaches down the road.


Strategic Partnerships

As is often the case when negotiating contracts in a Just-In-Time or traditional Order-To-Stock environment, the creation and fostering of strategic partnerships is paramount. In my experience, it is advantageous to give a little extra, for example: taking a less hardline stance when negotiating price. No one appreciates feeling ripped-off, which will lead to cognitive dissonance and a toxic relationship moving forward. Quality, especially in the case of a top-tier/ premium event, is rarely worth sacrificing. Delivery lead time is also rarely worth delaying, with the exception being for the most experienced of event directors.