Solving Problems, Cultivating Ideas Together

I worked for Procter & Gamble Philippines in the late 1980’s.  I was a production manager who oversaw the food packing lines of the company.  As production manager, I was invited at times to join the food brand team meetings led by marketing managers, who were responsible for their respective products’ success. 

P&G is famous for its brand management approach.  Introduced in 1920’s by Neil McElroy, who later became P&G’s president, brand management focused on individual products rather than the overall business.   Every product would have a brand manager who would be accountable for its market share and profitability. 

The brand managers of P&G formed teams represented by different functional members from all over the company.  These included people from product design & development (PDD), finance, sales, market research, and manufacturing. 

For the two (2) food product brands, my senior manager boss of food manufacturing was the member of both brand teams but the brand team at times would invite me to join meetings in cases where they needed some technical input. 

Brand managers delegated problems with their ideas to respective team members to solve.  PDD, for example, was charged with solving product design issues.  Finance was accountable in forecasting profits and presenting costs.  Sales made sure they got customer orders and that the product was distributed in all trade segments and geographic markets. Manufacturing was expected to provide time and resources for PDD’s test runs of product prototypes and to ensure volume targets were met when the product was launched. 

Brand managers would press brand team members to solve problems especially when there were tight deadlines to meet.  The careers of P&G brand managers depended on the successes of their ideas; failure was not an option.

This caused some friction between departments in which brand managers had to work harder to get supportive commitments from team members.  Some did and became successful.  Some didn’t and they left the corporation.   

One factor to why brand managers were unsuccessful was that they overly delegated problems to team members, to the point of blaming them for failures.  These brand managers misplaced delegation with teamwork. 

As much as there may be individual inventors who bring their ideas into realities single-handedly, successful idea-creators see the need to work with problem-solvers. 

Ideas and problems are not mutually exclusive.  Neither idea nor problem is worked on separately.  Problems are not obstacles to ideas and ideas should not be seen as unpleasant disruptions that lead to problems.

We should welcome both ideas and problems.  Ideas are the “a-ha’s”, the insights that are foundations of creative concepts.  Problems are the challenges that can provide us opportunities. 

When we encounter problems while inventing from an idea, we should try to seek opportunities from them, as much as we may try to overcome them as obstacles.  Problems can lead us to better ideas, as much as ideas can lead to problems. 

Team leaders therefore should not delegate as in pass problems with accountabilities to other team members.  Telling a team member to do a job and to do it correctly or else is not delegating; it definitely isn’t teamwork. 

Delegating is about entrusting and empowering a team member to do a job rightly and excellently.  It doesn’t exclude the compelling need to work with people. 

When an idea for a new product is created, a brand team should cultivate it together.  Team leaders and product design experts should tinker with new product ideas together.  Leaders should study profitability with finance experts together.  They should plan roll-outs to the trade together with the field sales people.  And they should test products and observe production runs together with manufacturing. 

The key word is together.  Teams are there together for a common purpose and when it comes to ideas and problems, they should tinker with them together to attain success. 

About Overtimers Anonymous

How Sales & Supply Chain People Can Work Together

Customer inquiries and quotations have long been seen as traditional jobs of sales professionals.  Field sales representatives visit customers and strive to get orders from them.  When customers inquire, sales professionals are expected to answer with accurate information. 

Trouble starts when sales professionals have no adequate answers to give.  Sales professionals may know prices, terms, and promotions.  But they may not know how much inventory is available to promise and when deliveries can be scheduled.  They also may not know how to cater to special requests and instructions regarding product specifications and deliveries. 

Sure, their superiors would have given field sales reps guidelines and information.  Sales reps may also have fixed allocations of how much they can promise to deliver.  But once they are in conversation with a customer, these guidelines and allocations may not be enough for a sales rep in discussion with a customer.

Sales reps have a lot of responsibilities.  They have territories to cover and targets to meet.  They promote products and negotiate contracts with customers.  They seek and open new accounts and they are expected to submit sales reports.  They also have to deal with complaints or worse, customers wanting to cancel orders or return products for refunds.

Sales representatives therefore expect their enterprise supply chains to deliver orders as promised.  The last thing they need is late, incomplete deliveries or pending orders that never get fulfilled. 

There’s a lot that’s been said about forecasting and managing demand, and a lot more about delivering orders.  But not a whole lot about what happens in-between: when customers inquire about products, what are available, and request for quotations (RFQ). 

In the many business meetings I’ve sat in, executives often ask what demand will be or how many orders are pending.  They don’t ask much about what customers are saying or asking.  Either they wait for their marketing people to mention anything or they just make conclusions on their own

In the retail business, store owners usually inquire from their suppliers about the availability of specific items, ask how much the prices would be, if the item can be delivered by what date, etc.  In short, the store owners inquire and expect the suppliers’ sales people to answer.

Whereas demand forecasts offer projected sales of items in cumulative numbers for an upcoming time period, inquiries from customers tell enterprises what they are looking for.  These inquiries can be and are valuable nuggets of information that can generate additional sales for an enterprise. 

But from what I’ve seen and heard, this information never really reaches the enterprise’s executives.  Either the information is forgotten or ignored.  What reaches executives are reports that have filtered the feedback from customers.

I’ve observed there are five (3) stages to demand creation and fulfilment:

  1. Inquiry
  2. Quotation
  3. Order
  4. Delivery
  5. After-Sales Service

Sales usually works exclusively on the first three.  The supply chain typically works on the last two. 

But the divisions of labour and accountability are more of formalities than realities in many cases. 

When customers inquire (1st stage), they ask not only about price, promotions, and product features, they also ask:

  1. How many items do you have available?
  2. How fast can you deliver?

And when the sales person gives a quotation (2nd stage), the customer will ask again:

  1. How long will it take you to deliver?
  2. When will the items be delivered after I place my order?

And when the customer decides to order (3rd stage), he or she will ask the sales person once again:

  1. When will the ordered items arrive?
  2. How many will arrive? 

It’s the same questions repeated at least three (3) times in those three (3) selling stages. 

Sales people naturally wouldn’t be able to answer those two (2) questions without foreknowledge of what the supply chain will do when the orders are received.  I’ve therefore observed that it’s common practice for sales people to call someone at the supply chain to get answers to those two (2) questions. 

That someone can be anyone.  It could be the one receiving the orders, the one who allocates items for delivery, the production planner, and any supply chain manager, or even all of these people all at once. 

In many cases, the supply chain people the sales people call don’t have the answers either.  And even if they did, they can’t or won’t guarantee the time and quantities of what would be delivered. 

Sales people would press whomever they’re talking to for some answers which they then can provide to their customers.  And in many times, the answers aren’t reliable or in the first place, aren’t authoritative. 

The easy way out of this quandary is to formalise the participation of supply chain operations in the first stages of selling:  inquiry, quotation, and order.  This can be done via:

  1. Assigning people from the supply chain who’d know the answers to liaison with the sales people;
  2. Establishing a system to already reserve items that customers want quoted and allocate them when the order arrives. 

It sounds hard and it will take quite some work to do #2 above.  But given that there probably is an informal system of allocation working already between sales and supply chain, the enterprise would do well to just get it set up and running. 

Note that in stages four and five, delivery and after-sales service, both supply chain and sales should still work together.  Even as the supply chain would have a higher accountability in serving orders and providing some after-sales services (e.g., warranty services), sales should be in communication with customers about the status of deliveries, getting feedback, and collecting payments. 

When sales and supply chain people work together in the five (5) stages of selling, they gain more confidence in responding to customer inquiries and requests.  They learn what customers need as much as they find ways to improve serving orders and fulfilling demand. 

About Overtimers Anonymous

Behold The PSI: A Basic Tool for Supply Chain Planning

The PSI or Production-Sales-Inventory is a basic spreadsheet template for supply chain planners. 

It looks like this:

The PSI has three sections:  production, sales, and inventories. 

Production represents the in-flow of an item or what’s going into inventory.  A basic example is finished goods input coming from a manufacturing operation’s output.  We can also call it supply. 

Sales is the out-flow of an item or what’s going out from inventory.  An example is a shipment to a customer.  We can also call it demand. 

Inventory is the stock of an item on-hand in storage, such as how much of an item is in a warehouse. 

The PSI makes visible production, shipments, and inventories over a range of time periods or what we can call time-buckets.  It’s an outlook for planning.  It’s up to the planner if he or she wants to use weeks, months, or even days for the time buckets.  It’s also up to the planner how many time buckets to plan for.  It doesn’t have to be just three as in the figure below.  It can be any number.  Some enterprises use six (6) buckets for a 6-month outlook; others go up to 12.  It is the planner and his superiors that decide what periods to cover (e.g., weeks, months) and how many. 

The PSI’s horizontal rows list the items or products.  Each row shows the production, shipments, and inventory outlook for each item via the quantities in the respective columns or time buckets. 

An item can be a product, material, or a supply or spare part. It is recommended to select an enterprise’s most important items to the PSI.  By very important, that would mean those that executives often keep an eye on. 

Working the PSI starts with a beginning inventory at the zero (ø) column of the inventory section. 

The planner’s basic aim is to track the inventories from one time-bucket to the next.  In the figure below, the planner notes that inventories at the end of week 1 becomes fewer as a result of sales in the same week. 

When the planner, however, inputs the production and sales of week 2, the inventories end with zero (ø) on week 2. 

To put what I just said in a formula:

and to put it to represent every time bucket:

where x is the time-bucket number.

The aim of the supply chain planner is to ensure there will always be available inventory for sales.  Hence, supply chain planners typically prefer there’d be extra stock at every time bucket.  

Supply chain planners typically set inventory targets for every time-bucket in line with their superiors’ policies and strategies.  Sales for each time-bucket usually are based on forecasts and customer orders. From the inventory targets, the planner computes the production or sales needed and still have enough left to meet inventory targets.

Planners focus on either how much to sell or how much to produce to meet inventory targets. 

If it’s production, planners would adapt the ending-inventory formula and make it look like this:

For a desired ending inventory of five (5) units of items A and B, the planner would set production numbers that would match sales but leave at least five units at every ensuing time-bucket. 

When the enterprise wants to plan how much of an item to sell given inventory targets and ongoing production, the supply chain planners would adopt the following formula: 

Which in the PSI would look like this:

…which looks just like the PSI for production.  😀

The PSI in the above diagrams show the same numbers but illustrates a different approach.  The planner either figures out how much to produce or calculates how much to sell for the ultimate purpose of having enough inventories at every time-bucket. 

An enterprise can tailor a PSI for its particular business. 

For an enterprise that buys finished goods and directly sells to customers, for instance, a planner can adapt a PSI from a production-sales-inventory template to one that is purchases-deliveries-inventory:

An enterprise that imports items and converts them to finished goods, a PSI may look like the one below. 

I found this especially useful in a metals manufacturer that was importing metal coils that then were then cut up and converted into steel sheets, plates, tubes and pipes.  As steel coils were the key components of the manufacturer with its weight in metric tons as the standard of measure, the PSI enabled the manufacturer’s managers to plan the quantities and timing of importing and converting expensive metals without having too much on floor for too long. 

When enterprises use a common measure from key materials to finished product, the supply chain planner could expand the PSI to a 4-column spreadsheet consisting of purchases-production-sales-inventories:

A 4-column PSI would be particularly effective for enterprises with few but predominantly high-volume products such as those in commodities.  And it opens up participation of practically the four (4) core disciplines of the supply chain:  purchasing, production, logistics, and planning. 

The PSI doesn’t require sophisticated software or hardware.  One can use an ordinary spreadsheet program (e.g. Excel) or even do it by hand with or without a calculator (or abacus). 

The PSI gives visibility to an enterprise’s supply and demand picture from present to future for key items, whether finished goods, materials, or parts. 

The PSI’s limit is that the more items an enterprise has, the more tedious it becomes to plan and track.  ERP systems coupled with up-and-coming artificial intelligence (AI) software can make up for that.  Many enterprises, however, rely on planners to plan the items they carry.   

Even with its simplicity and features, it’s hard to find an enterprise that actually uses a PSI.  Many planners tend to devise their own templates, using spreadsheets mainly, despite the availability of integrated planning tools provided by expensive software. 

Most of the planning spreadsheets I’ve seen are hard to understand or are very specialised.  When I present the PSI template to planners, however, I’ve gotten very positive feedback with executives welcoming its application. 

A PSI is a basic manifestation of what a supply chain planner does, which is to plan production or estimate the demand needed with a minimum amount of stock at every time period.  It is a basic tool for supply chain planners.  It’s simple to set up and provides a comprehensive canvas of what an enterprise’s supply and demand would look like in the present and future.  It has its limitations in the complexity of an enterprise’s items and operations. But at the very least, it provides a foundation for planners to manage inventories and optimise supply chain productivity. 

About Overtimers Anonymous

Why Shifting from the Month-End Surge to Delivery by Demand is Common Sense

“We just have to live with it,” the General Manager replied. 

The GM was responding to my comment that month-end surges in sales orders were causing inefficiencies in the company’s logistics operations. 

I was presenting an operations assessment report to a company that distributed name-brand computer printers and accessories.  One of the key observations from my report was that the majority of sales orders (more than 50% of monthly sales) came at the end of every month.  Staff from sales, accounting, to logistics rushed deliveries to fulfil the orders and meet revenue targets.  Sales personnel counted on the deliveries to achieve if not beat their quotas and benefit from incentives. Not attaining the targets and quotas was simply not acceptable.  

The company is an exclusive distributor for a large name-brand supplier of printers.  The supplier dictated the monthly sales targets.  The supplier expected the company to meet those targets from month to month, no questions asked.  Hence, the company’s General Manager said that month-end surges were something they could do nothing about.  It was something they had to live with. 

Many executives do not want to shift from the practice of month-end selling and delivery.  “It’s not for discussion,” a consumer goods wholesale executive once told me when I said the monthly surge in deliveries was causing her firm’s transportation expenses to rise.  The executive did not want to change a practice which has become so ingrained in the company’s culture.

Executives don’t dispute that month-end surges bring about inefficiencies and high costs throughout the supply chain.  Surges cause stock run-outs as inventories deplete quicker than suppliers or manufacturing lines can replenish.  The surges also drive up inventories of customers which result in increased product returns especially for products with limited shelf lives.    

Logistics expenses increase as month-end surges strain storage and transport capacities.  Some firms rent additional storage to stockpile products in anticipation of sales surges.  Transport providers tend to sub-contract additional trucks to ensure there are enough vehicles to meet the demand.  Both the additional storage and transport capacities result in higher delivered costs for products.    

Month-end surges are sometimes coupled with periodic sales promotions and price changes which fuel more spikes in orders and delivery volumes.  Surges thus cause a “bullwhip” effect in which the up-and-down delivery volumes and resulting peaks and valleys in inventories amplify speculations throughout the supply chain. 

Executives are reluctant to move away from month-end surges because they fear lower sales will result.  They are afraid shifting from month-end sales would cause a decrease in revenue which they can ill afford in organizations that especially measure performance by monthly targets.

Moving from month-end sales to just deliveries driven by demand is common-sense logical.  It’s just not accepted given the anxiety it would cause among executives. In a demand-driven supply chain, one delivers only what and when it is needed.  The fear is the demand and the subsequent sales might not be up to par with immediate targets.

A downturn in sales would indeed be expected as customers would exhaust overstocked inventories from any previous surge.  In succeeding months, demand would pick up and sales would average closer to what would have been with month-end surges.  But executives would have to have faith that that will happen and executives don’t like to count on faith. 

Stakeholders in many companies measure executives via short-term targets.  Stakeholders want to see continuous growth in their company’s finances especially if they expect dividends and bonuses every year.  Creditors, such as banks who provide loans, also want to see continuous short-term gains to assure themselves that they will be paid the interest and principal of what they lent. 

The month-end surge is a manifestation of short-term thinking.  Shifting from the month-end surge requires changing one’s mindset from short-term to long-term management.    

When delivering only what is needed and when it is needed, all functions of the organization have to work closely together.  Sales needs to forecast future demand from the grass-roots level or from the end-user, whether that be the customer or the customer’s customers.  Marketing would support sales where it sees demand is lacking or where there is potential.  The supply chain from logistics, manufacturing, and procurement would have to build in a capable system and structure to anticipate the demand.  Sales, Marketing, and the Supply Chain, most of all, would need to communicate and come out with a consensus of action every time they review actual and forecasted demand. 

Attaining higher sales is not a product of individual sales persons or a result of incentives for just one group.  It is the product of teamwork.  Any challenge in fulfilling demand and achieving targets can be met if the organization works as a team. 

And isn’t that what organizations are supposed to be doing in the first place?

About Overtimers Anonymous

Originally published in LinkedIn May 06, 2019

How Control Charts Can Help Get Things Done Correctly and Consistently

How can enterprises better control their supply chains?  How does one know if the supply chain is under control in the first place?

A soy sauce manufacturer bragged about its wonderful customer service numbers.  The manufacturer showed charts that it was delivering 98% of orders on-time and complete.  There was no problem with quality as there was barely any rejections from customers.  

Customers, however, were telling a different story.  The manufacturer’s largest buyer, a supermarket chain, complained that orders were arriving at merely 65% of the time.  Fill-rates or order completeness was averaging 50%, i.e., the corporation was delivering only half of the supermarket’s orders.

It was even worse with product quality.  Soy sauce sachets were leaking at the supermarket’s shelves.  The supermarket chain was pulling out damaged sachets every day.

This is a true-to-life story and one that is repeated countless times not only at supermarkets but across industries.  An enterprise boasts outstanding sales numbers, excellent customer service, and second-to-none product quality.  Customers in the meantime grumble about poor service and unsatisfactory quality and frequent out-of-stock.  Who’s right and who’s wrong? Clearly there’s conflict and something should be done. 

Supply chains are product and service streams in which materials flow, transform, and advance in value from their origins (sources) to their final stage as finished goods.   A supply chain’s aim is to deliver products and services correctly and consistently.  Correctly means delivering the right products and services that match customer demand and expectations.  Consistently means delivering products and services correctly all the time

To do things correctly and consistently, there has to be control.  Control is the influencing and regulating of activities, the critical ones especially, to attain discipline in desired results. 

Many firms, particular those that do manufacturing, utilise statistical methods to keep operations under control.  One prominent method is the control chart. 

Control charts makes visible the actual behaviour of operations versus what we would normally expect of them.  The theory behind control charts is that results of most operations would follow a standard normal pattern, what statisticians call a normal distribution.  Products as they are made would have characteristics that tend toward an average result.  The variations between individual products would also follow an expected range, which statisticians measure as the standard deviation. 

The Normal Distribution

If items exhibit results that stray far from the average, that is, beyond the normal distribution curve, then chances are the operations making available the items have become erratic, or in other words, they are going out of control. 

In the case of the supermarket chain and the issue of leaking soy sauce sachets, control charts can track the number of leaky sachets: 

x̅ chart
R Chart

The control charts above are examples of what the leaky sachets can be like at the supermarket’s shelves every day of the week for sixteen (16) weeks.  The control charts track the weekly average percentage of damaged sachets as well as the range or widest difference between daily samples. 

The x̅ (average percentage) control chart shows close to an average 7.4% in leaking sachets while the R (range) chart shows an average variation of 0.4% between daily samples from each week. 

Right away, management of both the supermarket chain and the manufacturing enterprise can see that at least 7 out of every 100 sachets are leaking on the shelves every week.  For the soy sauce manufacturer’s executives, who pride themselves on their company’s reputation for zero defects, this is unacceptable. 

But the point of the control charts wasn’t just to indicate how many sachets are leaking.  The control charts showed that the percentage of leaking sachets was averaging 7.4% to 7.8%.  The range (R) chart illustrates this variation, as differences between items varied at an average of 0.4%.  This meant daily damaged sachets kept to a steady range between 7% to 8% of total.  

There was an instance where one week’s average dropped to 7.2% and fell outside the control chart’s limits.  Even as a drop in damaged sachets was a welcome sight, it was more of an exception.  It wasn’t normal and the damaged average was not in normal control. 

There were two (2) weeks in the R chart where variations spiked or narrowed outside the statistically set limits.  This indicates samples on those two (2) weeks may have been gathered and computed differently or that operations in each of those two weeks were being done differently. 

To put it as simply as possible, sachets are leaking daily at more than 7% average.  From the consistency of the damages, one may speculate that the source of the damaged sachets is an operation at the soy sauce manufacturer’s facility. 

It was later found that the manufacturer’s sachet packing machines weren’t sealing the soy sauce sachets 100% effectively.  The sachets’ seals were deteriorating and opening as soon as the products left the soy sauce manufacturer’s premises.  It was recommended the manufacturer refer the problem to their product research department to review packaging specifications and sachet production protocols.  It was also suggested that the manufacturer and supermarket chain come up with common quality and service measures. 

Control charts can be intimidating given the requirements to compute statistical numbers.  But as much as one needs familiarity and initiative to set up control charts, they are not that difficult to make.  The hard part usually is in identifying what specification or performance measure to chart.

But once they are established, control charts can be very useful as they provide instant feedback on how consistent and correct operational results are. 

The whole point of supply chains is to deliver products and services correctly (matching customer expectations) and consistently (all the time).  Being consistent and correct begins with being in control of the supply chain. 

About Overtimers Anonymous