SupplyChainBrain attended our annual Kinexions user conference, and while there, they completed a number of video interviews with customers, analysts, and Kinaxis executives. And, we’d like to share them!
In this interview, hear Kathyleen Beveridge, director of sales operations with Qualcomm discuss “What’s Wrong With Traditional S&OP?” According to Beveridge, the sales and operations planning (S&OP) process brings great value to an organization, but companies need to take a fresh approach in order to ensure more efficient planning cycles.
Sales and operations planning involves a number of sequential stops. Mistakes anywhere along the way can lead to inefficient planning, says Beveridge. A new approach is needed that allows companies to become more agile in a difficult business climate.
Under the traditional approach to S&OP, it can take upwards of two weeks to compile data. “By the time you get in front of the management team, that data has already changed,” Beveridge says. Qualcomm has adapted S&OP to a weekly cycle, under which it has more frequent discussions with key decision makers. They focus on the state of the company’s supply and demand balance, with an eye toward making “immediate course changes” if necessary. The company also conducts monthly S&OP meetings that focus on longer-range issues.
Qualcomm isn’t throwing out S&OP in its traditional form; it’s simply supplementing the practice with shorter-term solutions, says Beveridge. That becomes necessary “if you’re working at a company where demand is ever-changing. Our lead time is shrinking. We need to augment.”
Integration of supply and demand planning is essential to a company’s ability to react to volatility. Working with Kinaxis, Qualcomm brought together the two disciplines to scrutinize the company’s project road map, with a goal of implementing capable-to-promise functionality. In the process, it’s able to build what the customer wants, instead of what it forecasts demand to be.
The journey isn’t over yet. Having implemented available-to-promise and commitment to finished goods, Qualcomm next wants to extend its visibility and control back to raw materials and semi-finished goods. The ultimate goal is to make possible customization of product. “If we can delay the build-out of finished goods,” Beveridge says, “we’ll be better positioned to satisfy our customers.” And Qualcomm, for its part, will benefit from improved inventory optimization.
I’ve had the opportunity over the past few weeks to investigate how many companies perform their Master Planning practices, and in the process do a pile of thinking about the Master Scheduling role.
My conclusion is that if your company is running smoothly, you need to stop what you are doing right now and hug your Master Scheduler. If your company isn’t successfully executing your plan, you should look at the tools you’ve given your Master Scheduler because with the traditional tools, asking the Master Scheduler to do an effective job is like asking da Vinci to paint the Mona Lisa with a can of spray paint. It isn’t going to be pretty.
If you think about it, the Master Scheduler is the keystone of your business. They have the unenviable job of being the first point of execution in your planning process. The Master Scheduler sets the build schedule for your plant, or perhaps even for your global supply chain. To do this, they need to balance the realities of the supply chain against the randomness of demand (after all, forecasts are…well forecasts. And you know the rule about forecasts – they are always wrong.)
Master Schedulers need to do this while respecting capacity limitations, working the overloads and back-filling the underloads. If that isn’t challenging enough, these constrained resources could be multiple levels away from the point of demand with multiple lead time offsets to consider. Starting to sweat yet? Now think about this; at the same time, the company has firm inventory targets that need to be respected. If your wonderfully leveled master schedule causes you to exceed your inventory targets, it’s back to the drawing board. If you are able to make a schedule that meets all requirements, you no sooner have that schedule ready to go when someone is trying to make it invalid. Scrap, late supplies, demand changes and capacity issues all can force the Master Scheduler to review and possibly adjust their plan.
On top of this, the Master Scheduler has multiple other responsibilities. They can be pulled into new order feasibility discussions with Order Fulfillment, they often are responsible for maintaining planning BOMs and are responsible for setting planning parameters like lead times, demand horizons and lot sizes.
So, I think we can all agree that the Master Scheduler has a challenging job. But, you’ve given the Master Scheduler the best tools, right? Stay tuned for part two to see how you can help your Master Scheduler with more than just a hug.
If your 3PL supply chain problem was to deliver 400,000 items daily from supplier to customer and your on-time in full metric was a six-sigma target standard of 1 failure per million, how would you do it?
What If I was to also constrain the resources you had at your disposal and said you only had 5000 transportation vehicles and your delivery slot was just 1 hour and that your delivery window was always 12pm until 1pm? What if I was then to say that you had no technology at your disposal to manage it and your only transportation methods were bicycles, trains and feet and you had to do it on a budget of 33 cents per delivery?
Well, that’s what the Dabbawalas in India have been doing in Mumbai for over 100 years – delivering meals direct to workers and school desks from the family home with an OTIF of 99.99 %. They don’t use technology but what they do have is a tried and trusted set of highly efficient robust procedures that govern how they manage their work. It’s a methodology that has been established and passed down from generation to generation and has stood the test of time.
So, why don’t organisations with similar problems just invest time in improving their working procedures? Why do we even need technology? Well, the answer in reality is that we really do need both – not all of our problems are only 3PL issues with supply chains having such stable demand signals – same item, same quantity, to the same customer, pretty much every day. Not all of our supply chains have a zero inventory, stable sub-contracted supply – it’s a relatively quick production process to make an Indian meal (2-3 hours), freshly cooked every day often using Tandoor ovens. In addition, the majority of our distribution networks are geographically wider and much more complex.
At Kinaxis, we’re supporting all of the above by enabling multiple disconnected, multi-platform data sources to come together in a single data model. This gives our customers a single view of the entire organizational data model. This means that cross-organisation planning can take place, active ingredient production can support manufacturing, filling and packing operations at other sites, component items and raw material suppliers can be integrated into the single model and collaboration between supplier and customer can take place with a single view of the plan. Because we get visibility, because it’s real time, it removes uncertainty. Removing uncertainty and gaining confidence removes buffers – specifically it removes inventory and lowers safety stock targets – Kinaxis MEIO application simultaneously calculates what is needed at each echelon in the supply chain network and takes cost out, freeing up huge amounts of working capital.
If we then couple those primary short to medium term cost reducing objectives with establishing a level of planning for the future, we can begin to shape the organization to best fit the known environment. In other words, we can establish a robust Sales and Operations Planning process, supported by accurate data, a demand model supported by forecasting algorithms and a supply view that includes capacity balanced resources and key supplier delivery information. The result, a Supply and Demand balanced picture that allows you to make resourcing or promotional decisions to assist in that balancing process and those decisions can be tested using Kinaxis RapidResponse scenario capability. Run unlimited ‘What-if’ analysis, compare those results with other scenarios, share scenarios with colleagues, make accurate decisions and commit the changes to the plan.
Would Kinaxis work with Dabbawalas? Possibly. Do they need it? Probably not.
Do you have a Dabawalla process and a simple supply chain? If you don’t, are you looking to improve your decision making ability within your planning processes? Please keep the conversation going in the comments below.
This week I attended the 5th Annual Pharmaceutical Innovation in Manufacturing Summit near Heathrow. Although the conference was situated in the Edwardian style Radisson hotel neatly decorated with Persian rugs, brass-railed staircases and chandeliers, the location stood in sharp contrast with the innovative character of the Summit.
The objective of the summit was to provide an open forum for highly insightful presentations that span a broad range of topics critical to the biologics field. It was a two-day gathering dedicated to cutting edge technology, innovation and strategy across the entire small molecule & biopharmaceutical manufacturing process.
As good as the sessions were, I always find the networking opportunities the most useful at these kinds of summits. There was plenty of room during dinners and lunch breaks to discuss new ideas with industry peers. Seeing a lot of familiar faces you realize that the pharmaceutical supply chain is a small world.
Distinctive of this summit was the wide variety of topics and themes that passed these two days. Topics that were discussed ranged from strategic supply chain challenges to operational packaging and labeling processes and techniques. While there are undoubtedly some topics relevant for each participant, it seemed very well possible this broad setup of event missed its goal.
Kinaxis was present with a booth and Laura Dionne, Senior Director, Worldwide Operations Planning at TriQuint gave a well-received presentation titled ‘A Healthy Dose of Chips: Supply Chain Lessons for Life Sciences’. In this presentation Laura discussed the similarities between pharmaceutical and Semiconductor supply chains and also the solutions that can be applied for addressing similar challenges.
Don’t worry if you missed the event, the presentation slides from Laura are available and can be viewed on slideshare.
A colleague and I started our morning off with a coffee and a conversation about integrating EOQ (Economic Order Quantity) into MPS (Master Production Scheduling). In no time at all we were debating between lean versus EOQ. While each approach has its merits, the two concepts present some conflicting advice. Here we go again! It doesn’t matter if you’re a technician working on the shop floor or an executive in the board room, if you’re in the business of manufacturing then this is a conversation you’ve had before. Without the right data it’s a debate that’s impossible to win, but I’m convinced that neither solution is perfect in all cases.
EOQ attempts to optimize lot size by balancing manufacturing cost (Fixed + variable costs) with things like inventory holding costs and capacity utilization. Lean relies on minimization of, among other things, lot sizes, inventory and waiting. Traditional ERP systems take fixed (often part specific) inputs for planning parameters and spits out a plan without any thought as to the efficiency (financial/shop capacity, etc.) of that plan. Master schedulers can manipulate the planning parameters to create lean or EOQ optimized schedules, but how do you decide which way is right for your organization?
Companies often swing back and forth between the two ideologies – often depending on which S&OP seminar an executive recently attended. I’ve seen attempts to transition to lean cripple an organization because they incorrectly applied the principles and go too hard and too fast. Yet, going all the way to EOQ could cause over-investment in inventory and tie up capital that would be better invested in new technologies/process that would allow a company to become more lean.
In my opinion, lean appears to be the better solution in many industries, but transitioning to lean is challenging and the reality is that many companies aren’t close yet. So, how do they make that transition? They can go fast, invest a significant amount of cash into the transition and throw a huge team of industrial engineers at the problem to look at everything from all angles. Alternatively, they can go slow, and use a small team of industrial engineers, but where do they start and can they move quickly enough to stay competitive in a rapidly changing world?
With the right analytics and the ability to compare multiple scenarios, it’s possible to find the happy middle ground in between and make a smooth transition to lean. Imagine a tool that allows supply chain professionals to compare both scenarios and understand the complete impact on their business of each option (globally and specifically), and allows schedulers and planners to make the right decision on a case-by-case basis. This could change the conversations of the S&OP/MPS teams as the data can enable rapid and accurate decisions on how to most effectively invest their resources (based on constraints like capacity, inventory holding costs, availability of supply, availability of cash for inventory investment, etc.).
Imagine a scenario:
You’ve got a product line with high run rates and steady demand that screams lean but you’ve still got high fixed costs due to multiple products lines sharing the same manufacturing cell (repetitive tear-down/setup)? Let’s work under EOQ rules until your industrial engineers can come up with a solution that reduces your setup time, changes the planning parameters, and swings the balance back toward lean. Oh, and by the way, here’s a list of parts where your industrial engineers should focus their efforts based on the largest opportunities presented (based on current independent demand data).
You want to go lean, but your customer’s demand schedule wreaks havoc on your capacity plan. Here are the most cost effective parts to re-schedule/ group to balance capacity with cost.
You’ve ‘gone lean’ but aren’t! How do you correct until your industrial engineers catch up with your executive vision?
What are your thoughts? Have you had this debate before? Have you tried to go lean but haven’t received the benefits you expected from your investment? How are you changing the conversation in your organization to ensure you are investing resources effectively? Please keep the conversation going in the comments below.
Our partner Celestica recently published the following article, ‘What If You Could Take The Guesswork Out Of Forecast Planning?’. The author, Osgood Vogler, Director, Analytics, Celestica Supply Chain Managed Services, describes an insight-based demand management process:
So, how do you take the guesswork out of forecast planning? Let’s find out.
Demand planning has a big impact on business performance. Planning error can put revenue at risk by driving component shortages. Persistent planning biases can tie up cash by driving excess inventory. Furthermore, the act of planning and dealing with planning error is time consuming and drives costly overhead. In fact, it is common for supply chain management executives to cite “planning errors” as the greatest obstacle they face to achieving their goals and objectives.
The factors which impact demand management and forecasting are nearly endless. Uncertainty in end markets, shifts in the competitive landscape, constant time-to-market pressure, economic volatility, geopolitical and environmental issues all play a role in component shortages, excess stock and lost revenue. Given this volatility, it is not surprising that organizations are struggling to make effective demand predictions.
To avoid the financial risks associated with planning errors, supply chain leaders and manufacturers should consider building an “insight-based” demand planning process, which brings together analytical tools and data with key human inputs across various functions. This “next generation” demand management approach will allow supply chain operations to evolve and scale with the ever growing volatility and uncertainty of today’s markets.
The insight-based demand management process contains several key principles.
One size does not fit all One solution is never going to address every challenge an SCM executive will face, so it is important to determine the best approach for your supply chain through segmentation.
One planning approach may work well for one group of parts but not for another. Segmenting parts in a supply chain is incredibly useful to help guide the development of a cohesive demand management strategy. There are three questions that are central to the demand segmentation.
• Why is planning necessary?
• How important is the part to your business?
• How predictable is the demand?
Several considerations will likely go into answering each of these questions.
For example, to answer the first question about whether planning is necessary, SCM executives need to determine if supply is constrained and how quickly customers expect their order to be fulfilled.
If planning is absolutely necessary because supply of a particular part is constrained, an organization needs to determine how critical that part is to the supply chain, what profit margin is realized from the sale of the part and whether the demand is predictable across related parts and products.
This exercise is important because it will help supply chain leaders understand exactly where planning is necessary and how to drive exceptional performance in their supply chain operations.
Measure where it matters
Defining what actually needs to be predicted to effectively manage a supply chain is a requirement for accurate and efficient demand planning.
While prediction accuracy is often measured at the lowest level of granularity, such as by item, customer or region, these factors may not actually matter as much as prediction accuracy at a higher level. For example, the overall demand accuracy by part type at a regional distribution center may be more important to supply chain performance than item-customer-region level accuracy. To accurately judge one approach versus another, the primary metric for evaluation purposes may need to be established at a different level.
For example, if a planning process needs to determine “how many widgets do we need?,” the answer might be “we know we need 1,000 pieces.” However, if the demand planning process needs to determine “how many widgets of each color do we need?,” the answer might be “we are not really sure, say 600 black and 600 blue.” In this scenario, a forecast bias was created and it led to an order of 200 additional widgets.
To eliminate these low-confidence guesses and move toward a more informed demand forecasting process, the inputs used to generate a plan should be carefully selected.
Some common examples of guesswork in the demand forecasting process can include systems forcing planners to input forecasts at granularity that is lower than what can reasonably be estimated and sales teams tasked with translating customer intelligence directly into a demand plan.
Guesswork should never be hard-wired into the demand management process. The best results are most often achieved through human knowledge of the market and customers behavior coupled with analytics such as data on observed patterns, market trends and dynamics.
Find the right blend
Effective demand management requires a blend of two perspectives. The first is the customer’s perspective “looking outside in” at an organization’s products and the second is the supply chain’s perspective “looking inside out” to the supply base.
Understanding how the customer’s needs, wants and behaviors translate into demand is just as important as understanding what is known and/or knowable at different points in the marketing, sales and supply chain cycles.
Human wisdom combined with analytical insights need to be operationalized and integrated into a cohesive process. For example, what your sales and marketing teams really know about customers in end markets at various points during the sales cycles needs to be captured and leveraged effectively.
Furthermore, shared parts and bill of materials (BOM) commonality may present opportunities to generate more accurate and meaningful aggregate forecasts for the supply base. For instance, if two parts have BOMs that are 80 percent in common, it may be more effective to forecast the common parts separately from the unique parts.
Always keep a running score
Of course, implementing an insight-based demand management process structured around an understanding of key insights from human wisdom and analytical data is not a “set it and forget it” decision. Segmentation questions and criteria evolve with the business. Modeling and collaboration are ongoing activities. What is now a “guess” may become a “known” and what is currently “known” may become “unknown”. Scoreboards keep us honest and drive constant evolution. Insight-based demand management never stops.
SupplyChainBrain attended our annual Kinexions user conference, and while there, they completed a number of video interviews with our customers. And, we’d like to share them!
In this interview, hear Benji Green, director of global sales operations, outline the successes that the company has achieved – and the direction it intends to take next.
Green has seen some fundamental shifts in the supply-chain planning paradigm. One involves a continuing trend toward specialization: companies focusing their efforts on research and development, while outsourcing manufacturing. Another relates to a faster product-refresh rate, especially in high-tech. “It becomes harder to predict because your lifecycle’s so short,” he says. A third trend is globalization, with an exponential increase in the number of people involved in the supply chain, and a consequent extension of order lead times. In response, companies are looking to replace their vertically structured supply chains with close partnerships.
Planners face the challenge of dealing both with unexpected short-term changes in demand and the need to create longer planning horizons. As lead times become stretched, it becomes more important to have in place detailed contingency plans in the event that things go wrong. Companies need to acknowledge that the forecast will never be 100-percent accurate, and plan accordingly.
Communication among multiple parties becomes more important than ever before. “You’ve got to get data from the other company much faster,” says Green. In addition, top management needs to acquire new skills in dealing with key suppliers, including the ability to negotiate the appropriate contract terms.
Working with partner Kinaxis, Avaya has been on a four-year journey to improve its ability to react to real-world demand. Green says the company has had “a lot of success,” delivering its best-ever run times and inventory turns. Products include phones for both large and small companies, in addition to infrastructure such as servers and gateways that support global collaboration. Manufacturing is 100-percent outsourced. Most fulfillment is carried out with the aid of a third-party entity.
The changes were spurred by new management and its desire to improve return on investment, Green says. “The new leaders have a very aggressive vision,” he says. “We’ve made great progress.”
This past week was the IE Group’s S&OP Innovation Summit at the beautiful venue of the Bellagio in Las Vegas. Kinaxis was well represented, especially with the wonderful keynote speech from Kathleen Geraghty from Celestica. Her keynote hit the main theme of the conference: S&OP Skills. Having attended and presented at many S&OP conferences, I was expecting the standard S&OP challenges of maturity and alignment with cross functional teams. The reason I found this conference surprisingly unique, is the focus on talent and skills.
Celestica’s keynote centered on “Planning with Predictive Power”, which is done as a managed service from Celestica. Having worked many years in the supply chain with the contract manufacturing firms, I find this managed service, sometimes called PaaS (Planning-as-a-Service), extremely intriguing. The contract manufacturer, Celestica, already manages manufacturing and inventory. They are best prepared to do the planning service. Kathleen spoke about managing demand planning and scenario modeling of the Brand’s S&OP process, with the goal of improving forecast accuracy to above 85% and modeling in minutes, not days.
The benefit is directly in the inventory, as seen in Kathleen’s slide.
Celestica is providing the “talent” in this service. With the breadth of skills from being a contract manufacturer, Celestica uses Predictive Power and Kinaxis supply chain solution to insert the talent and skill in the S&OP cycle, directly impacting inventory, order fulfillment and cost.
The Kinaxis Workshop – Learn and Laugh
For the Kinaxis Workshop, my theme was “Laugh & Learn”. From the audience I heard they were pleased to take a humorous journey through S&OP, with follow on comments like, “that was great to break out of the typical S&OP materials”. As well, we shared the Four Keys of successful S&OP, with the audience participating by ranking their company against the keys.
Some of the highlights from the “learn & laugh” session…
1. The S&OP journey is quite an ambitious one. From the early days of using excel and having only supply chain people attend, spending a few years stuck in “Stage 2” doing just demand and supply balancing, to holding real-time tradeoff decisions. It’s a journey of a 1000 miles, but in the end, it does pay off…
2. We shared our war stories about breaking through the corporate culture, and the significant change management needed to adopt this S&OP process. Everyone has heard the saying about tradition, “We’ve always done it that way here…”
3. Ultimately, S&OP is about finding problems. And, done correctly, an effective S&OP will be able to not only spot the obvious problems at the volume level, but also the underlying issues at the mix/SKU level.
4. The S&OP journey leads to a team of leaders that make tradeoffs and decisions. It’s the mark of an effective leadership team to decide those tradeoffs for the best interest of the company. As well, some decisions center on “survival”, using the S&OP to know when to “not make a decision”…
5. My personal favorite ended on the foresight a supply chain leader needs to have. Steering his/her team to a mature, Stage 5, S&OP requires the ability to stand against people who say “it cannot be done”….
This image reminds me of my Apple S&OP days, and taking the team north of San Francisco for white water rafting down the Russian River….
The four keys to a successful S&OP are shown in the box below.
As I walked through the Four Keys, I had everyone from the audience fill out this form, ranking from 1-10 (low to high), how their company performs.
The summary results:
East West Integration: average of 4.8
North South Integration: average of 3.9
Volume and Mix: average of 5.9
S&OP On-Demand: average of 4.4
This is extremely interesting in that the better performing key was volume and mix. This is the ability to take a volume plan and quickly drill down to the mix/SKU level, testing the feasibility of the two, and having the ability to keep the plan feasible. This shows the high level of supply chain participation in the S&OP. Drilling up and down the product supply network is a core competency of the supply chain team.
The lowest Key was S&OP on-demand. I remember my days at AMR Research, and the questions I would get on S&OP cadence. People would ask, “Should I run a Monthly Cycle?” and “How often should S&OP be done?” However, the best ability is to revise the plan and take action anytime S&OP is at risk. Through my past 25 years, I’ve reviewed 106 companies’ S&OP processes. The SINGLE best practice is doing What-If Simulations. Not the kind of simulations that your Stats PhD does over the weekend with his/her Access database, but doing What If Simulations during the S&OP sessions. That requires Speed and Integration with your process and solution.
Speed can be best defined by a few Kinaxis prospects who attended our annual conference at Miramar (where Top Gun was filmed). Coming off the flight path after seeing the Kinaxis demo, these two certainly understood the need for speed…
Integration can only come from a planning solution that pulls the data, policies and structures together, from all the nodes of the supply chain network, running concurrent planning at the S&OP to the MRP levels, in ONE code, not multiple Modules with massive middleware & excel. This is a customer who is very intense about the Kinaxis One Code…
Standing inside the Bellagio, in the entertainment capital of the world, I know the IE Group attendees have been entertained, much beyond the standard S&OP sharing.
Let me know your Four Key’s ranking. Where do you stand against the average? For now, I hope you’ve “learned and laughed”.