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.
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.
If you plan to attend the conference, join Laura Dionne, Senior Director, Worldwide Operations Planning, TriQuint as she presents ‘A Healthy Dose of Chips: Supply Chain Lessons for Life Sciences from a High Tech Veteran’ on Tuesday, February 10th at 2:15pm.
What can a lifelong Semiconductor Supply Chain expert have to say about Pharmaceuticals? A surprising amount it seems! In this presentation we will explore the similarities between these supply chains and also the solutions that can be applied for addressing these challenges.
Laura Dionne, a 33 year Semiconductor Veteran and supply chain change agent will discuss the commonalities including the challenge of planning a wealth of products that can be manufactured from a singular base material, how quality creates an underlying tension that drives customer fulfillment and margins, and also how inventory strategy can make the difference between profit and loss. Cross over of experts between industries is not anything new to the supply chain, but few would recognize what can be learned about the two industries that have shaped the global supply chain… Pharmaceuticals and Semiconductors.
We’ll be posting Laura’s presentation deck along with a recap of the conference, so stay tuned!
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”.
The recently published Gartner report, The Impact of In-Memory Computing on Supply Chain Management (Payne, T., 21 October 2014), describes the potential of in-memory computing (IMC) for supply chain management (SCM) including supply chain planning (SCP) applications, as follows:
“By 2018, at least 50% of global enterprise companies will use IMC to deliver significant additional benefits from investments in SCM, and especially, SCP.”
As awareness of the potential for transformational benefits from IMC grows, companies are asking tough questions about how, where and what type of IMC-enabled supply chain applications they should deploy. This is important because, according to Gartner’s research, the potential “benefits will vary by organization size, functional domain, industry and supply chain maturity.” So while the list of advantages of IMC technology is significant – and includes performance and scalability improvements, facilitation of advanced analytics, and process innovation – like any technology investment, the impact to your specific environment will depend on the chosen solution approach.
Gartner outlines three styles which include:
Native IMC: These applications are “developed from inception on the basis of IMC design principles”
Retrofitted for IMC: These applications were “originally designed on traditional technologies (for example, RDBMSs), but are now replatformed on top of an in-memory data store”
Hybrid IMC: These applications “use IMC design principles and technologies only in part, usually to store (at times, only temporarily) and process the most performance or scalability sensitive application data, or to support real-time analytics”
Interestingly, the Gartner reports states:
“The maximum transformational benefits will come from native IMC, because this approach allows organizations to leverage IMC to drive completely new ways of working in line with the company’s supply chain transformation efforts.”
Kinaxis RapidResponse uses a Native IMC approach. With RapidResponse, the analytics code is directly compiled into the database engine where it has direct access to the data and the various data relationships. The speed and scale that this provides is valuable because it enables businesses to develop new and improved processes capable of delivering breakthrough performance improvements.
If you’re evaluating IMC-enabled supply chain applications to determine how your organization can get the most benefit this Gartner research report is a must-read! It sheds light on the business value that in-memory computing brings to supply chain management in general and provides key findings and recommendations on the potential of IMC across functional domains, industry verticals and solution types. It’s only available for a limited time, so be sure to read it today.
P.S. With a 25+ year history of developing in-memory computing technology, we’ve talked about this topic before, so be sure to also check out some of our other posts:
Just a quick post to let our readers know that we’ll be at the 2015 S&OP Innovation Summit. This year’s event will be held at the Bellagio hotel, January 28 & 29, 2015.
If you plan to attend the conference, join C.J. Wehlage, Vice President, High Tech Solutions, Kinaxis, as he presents ‘S&OP: It’s the Journey, not the Destination’ on Wednesday, January 28th at 11:00a.m.
C.J. Wehlage will provide a true 360 degree view – as a practitioner, leading supply chains at Apple, EMC, Bose and Sony, as an analyst, running the high tech practice at AMR Research, and as a software provider, implementing RapidResponse.
Laugh and learn, as CJ presents the four keys to S&OP effectiveness and how the best in class execute S&OP from both a North-South & East-West integration, aligning demand and supply, as well as integrating finance. They tie volume and mix plans and perform S&OP on-demand, not just on schedule.
We’re a sponsor and invite you to visit us there and follow #SOPVegas on Twitter to get real-time updates from the event.