Update on Forecasting vs. Demand Planning

Often, the terms, “forecasting” and “demand planning”, are used interchangeably. 

The fact that one concept is a subset of the other obscures the resulting confusion. 

Forecasting is the process of mathematically predicting a future event.

As a component of demand planning, forecasting is necessary, but not sufficient.

Demand planning is that process by which a business anticipates market requirements.  

This certainly involves both quantitative and qualitative forecasting.  But, demand planning requires holistic process that includes the following steps:

1.      Profiling SKU’s with respect to volume and variability in order to determine the appropriate treatment:

For example, high volume, low variability SKU’s will be easy to mathematically forecast and may be suited for lean replenishment techniques.  Low volume, low variability items maybe best     suited for simple re-order point.  High volume, high variability will be difficult to forecast and may require a sophisticated approach to safety stock planning.  Low volume, low variability SKU’s may require a thoughtful postponement approach, resulting in an assemble-to-order process.  This analysis is complemented nicely by a Demand Plan Sanity Check, which should be an on-going part of your forecasting process.

2.       Validating of qualitative forecasts from among functional groups such as sales, marketing, and finance
3.       Estimation of the magnitude of previously unmet demand
4.       Predicting underlying causal factors where necessary and appropriate through predictive analytics
5.       Development of the quantitative forecast including the determination of the following:

  • Level of aggregation
  • Correct lag
  • Appropriate forecasting model(s)
  • Best settings for forecasting model parameters
  • Deducting relevant consumption of forecast

6.      Rationalization of qualitative and quantitative forecasts and development of a consensus expectation
7.      Planning for the commercialization of new products
8.      Calculating the impact of special promotions
9.      Coordinating of demand shaping requirements with promotional activity
10.    Determination of the range and the confidence level of the expected demand
11.    Collaborating with customers on future requirements
12.    Monitoring the actual sales and adjusting the demand plan for promotions and new product introductions
13.    Identification of sources of forecast inaccuracies (e.g. sales or customer forecast bias, a change in the data that requires a different forecasting model or a different setting on an existing forecast model, a promotion or new product introduction that greatly exceeded or failed to meet expectations).

The proficiency with which an organization can anticipate market requirements has a direct and significant impact on revenue, margin and working capital, and potentially market share.  However, as an organization invests in demand planning, the gains tend to be significant in the beginning of the effort but diminishing returns are reached much more quickly than in many other process improvement efforts.

This irony should not disguise the fact that significant ongoing effort is required simply to maintain a high level of performance in demand planning, once it is achieved.

It may make sense to periodically undertake an exercise to (see #1 above) in order to determine if the results are reasonable, whether or not the inputs are properly being collected and integrated, and the potential for additional added value through improved analysis, additional collaboration, or other means.

I’ll leave you once again with a thought for the weekend – this time from Ralph Waldo Emerson, “You cannot do a kindness too soon, for you never know how soon it will be too late.”

Thanks for stopping by and have a wonderful weekend!

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The Winding Road toward the “Autonomous” Supply Chain (Part 2)

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Last week, I began this train of thought with The Winding Road toward the ‘Autonomous’ Supply Chain (Part 1)”.  Now, as this weekend approaches, I conclude my piece, but I hope to spur your ideas.

Detect, Diagnose, Decide with Speed, Precision & Advanced Analytics

Detection of incidental challenges (e.g. a shipment that is about to arrive late, a production shortfall, etc.) in your value network can be significantly automated to take place in almost real-time.   Detection of systemic challenges will be a bit more gradual and is based on the metrics that matter to your business, capturing customer service, days of supply, etc., but it is the speed (and therefore, the scope) that is now possible that drives more value today from detection.

Diagnosing the causes of incidental problems is only limited by the organization and detail of your transactional data.  Diagnosing systemic challenges requires a hierarchy of metrics with respect to cause and effect (such as, or similar to, the SCOR® model).  Certainly, diagnosis can now happen with new speed, but it is the combination of speed and precision that makes a new level of knowledge and value possible through diagnosis.

With a clean, complete, synchronized data set and a proactive view of what is happening and why, you need to decide the next best action in a timeframe where it is still relevant.  You must optimize your tradeoffs and perform scenario (“what-if”) and sensitivity analysis.

Ideally, your advanced analytics will be on the same platform as your wrangled supra data set.  The Opalytics Cloud Platform (OCP) not only gives you state of the art data wrangling, but also provides pre-built applications for value network design and flow, inventory optimization, transportation routing and scheduling, clustering, predictive analytics, and more.  OCP also delivers a virtually unlimited ability to create your own apps for decision modeling, leveraging the latest and best algorithms and solver engines.

Speed in detection, speed and precision in diagnosis, and the culmination of speed, precision and advanced analytics in decision-making give you the power to transpose the performance of your value network to levels not previously possible (see Figure above).  Much of the entire Detect, Diagnose, Decide cycle and the prerequisite data synchronization can be, and will be, automated by industry leaders.  Just how “autonomous” those decisions become remains to be seen.

As yet another week slips into our past, I leave you with a thought from Ralph Waldo Emerson, “There is properly no history, only biography.”

Have a wonderful weekend and thank you, again, for stopping by.

The Winding Road toward the “Autonomous” Supply Chain (Part 1)

There is a lot of buzz about the “autonomous” supply chain these days.  The topic came up recently at a conference I recently attended where a topic of discussion was the supply chain of 2030. But, before we turn out the lights and lock the door to a fully automated, self-aware, supply chain decision machine, let’s take a moment and put this idea into some perspective.  I’ve heard the driverless vehicle used as an analogy for the autonomous supply chain.  However, orchestrating the value network where goods, information and currency pulse between facilities and organizations, following the path of least resistance may prove to be considerably more complex than driving a vehicle.  Most sixteen-year-olds can successfully drive a car, but you may not want to entrust your global value network to them.

Before you can have an autonomous supply chain, you need to accelerate what I call the Detect, Diagnose, Decide cycle.  In fact, as you accelerate the cycle you may learn just how much autonomy may be possible and/or wise.

Detect, Diagnose, Decide

The work of managing the value network has always been to detect challenges and opportunities, diagnose the causes, and decide what to do next –

  1. Detect (and/or anticipate) market requirements and the challenges in meeting them
  2. Diagnose the causes of the challenges, both incidental and systematic
  3. Decide the next best action within the constraints of time and capital in relevant time

The Detect, Diagnose, Decide cycle used to take a month.  Computing power, better software, and availability of data shortened it to a week.  Routine, narrowly defined, short-term changes are now addressed even more quickly under a steady state – and a lot of controlled automation is not only possible in this case, but obligatory.  However, no business remains in a steady state, and changes from that state require critical decisions which add or destroy significant value.

Data Is the Double-edged Sword

digital-value-network-matrix

Figure 1

The universe of data is exploding exponentially from networks of organizations, people and things.  Yet, many companies are choking on their own ERP data, as they struggle to make decisions on incomplete, incorrect and disparate data.  So, while the need for the Detect, Diagnose, Decide cycle to keep pace grows more ever more imperative, some organizations struggle to do anything but watch.  The winners will be those who can capitalize on the opportunities that the data explosion affords by making better decisions through advanced analytics (see Figure 1).  The time required just to collect, clean, and synchronize data for analysis remains the fundamental barrier to a better detection, diagnosis and decisions in the value network.

A consolidated data store which can connect to source systems and on which data can be programmatically “wrangled” into a supra data set would be helpful in the extreme.  While this may seem like an almost insurmountable challenge, this capability exists today.  For example, the Opalytics Cloud Platform enables you to use Python to automatically validate, reconcile and synchronize data from various sources, forming the foundation of a better Detect, Diagnose, Decide cycle.

Thanks for taking a moment to stop by.  As we enter this weekend, remember that life is short, so we should live it well.

I’ll be back next week with Part 2.

Do You Need a Network Design CoE?

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Licensed through Shutterstock. Copyright: Sergey Nivens

Whether you formally create a center of excellence or not, an internal competence in value network strategy is essential.  Let’s look at a few of the reasons why.

Weak Network Design Limits Business Success

From an operational perspective, the greatest leverage for revenue, margin, and working capital lies in the structure of the supply chain or value network.*

It’s likely that more than half of the cost and capabilities of your value network remain cemented in its structure, limiting what you can achieve through process improvements or even world-class operating practices.

You can improve the performance of existing value networks through an analysis of their structural costs, constraints, and opportunities to address common maladies like these:

  • Overemphasis on a single factor.  For example, many companies have minimized manufacturing costs by moving production to China, only to find that the “hidden” cost associated with long lead times has hurt their overall business performance.
  • Incidental Growth.  Many value networks have never been “designed” in the first place.  Instead, their current configuration has resulted from neglect and from the impact from mergers and acquisitions.
  • One size fits all.  If a value network was not explicitly designed to support the business strategy, then it probably doesn’t.  For example, stable products may need to flow through a low-cost supply chain while seasonal and more volatile products, or higher value customers, require a more responsive path.

It’s Never One and Done

At the speed of business today, you must not only choose the structure of your value network and the flow of product through that network, you must continuously evaluate and evolve both.  

Your consideration of the following factors and their interaction should be ongoing:

  1. Number, location and size of factories and distribution centers
  2. Qualifications, number and locations of suppliers
  3. Location and size of inventory buffers
  4. The push/pull boundary
  5. Fulfillment paths for different types of orders, customers and channels
  6. Range of potential demand scenarios
  7. Primary and alternate modes of transportation
  8. Risk assessment and resiliency planning

The best path through your value network structure for each product, channel and/or customer segment combination can be different.  It can also change over the course of the product life-cycle.

In fact, the best value network structure for an individual product may itself be a portfolio of multiple supply chains.  For example, manufacturers sometimes combine a low-cost, long lead-time source in Asia with a higher cost, but more responsive, domestic source.

Focus on the Most Crucial Question – “Why?”

The dynamics of the marketplace mandate that your value network cannot be static, and the insights into why a certain network is best will enable you to monitor the business environment and adjust accordingly.

Strategic value network analysis must yield insight on why the proposed solution is optimal.  This will always be more important than the “optimal” recommendation.

In other words, the context is more important than the answer.

The Time Is Always Now

For all of these reasons, value network design is more than an ad hoc, one-time, or even periodic project.  At today’s speed of competitive global business, you must embrace value network design as an essential competency applied to a continuous process.

You may still want to engage experienced and talented consultants to assist you in this process from time to time, but the need for continuous evaluation and evolution of your value network means that delegating the process entirely to other parties will definitely cost you money and market share.  

Competence Requires Capability

Developing your own competence in network design will require that you have access to enabling software.  The best solution will be a platform that facilitates flexible modeling with powerful optimization, easy scenario analysis, intuitive visualization, and collaboration.  

The right solution will also connect to multiple source systems, while helping you cleanse and prepare data. 

Through your analysis, you may find that you need additional “apps” to optimize particular aspects of your value network such as multi-stage inventories, transportation routing, and supply risk.  So, apps like these should be available to you on the software platform to use or tailor as required.  

The best platform will also accelerate the development of your own additional proprietary apps (with or without help), giving you maximum competitive advantage.  

You need all of this in a ubiquitous, scalable and secure environment.  That’s why cloud computing has become such a valuable innovation.  

If you found some of these thoughts helpful, and you are looking for value network capability to support your internal competence, you may want to have a look at the Opalytics Cloud PlatformYes, I work for Opalytics, but the Opalytics Cloud Platform has been built from the ground up for do deliver all of this.  

A Final Thought

I leave you with this final thought from Socrates:  “The shortest and surest way to live with honor in the world is to be in reality what we appear to be.”

 

*I prefer the term “value network” to “supply chain” because it more accurately describes the dynamic collection of suppliers, plants, outside processors, fulfillment centers, and so on, through which goods, currency and data flow along the path of least resistance (seeking the lowest price, shortest time, etc.) as value is exchanged and added to the product en route to the final customer.

The Value Network, Optimization & Intelligent Visibility

The supply chain is more properly designated a value network through which many supply chains can be tracedMaterial, money and data pulse among links in the value network, following the path of least resistance.

If each node in the value network makes decisions in isolation, the potential grows for the total value in one or more supply chain paths to be less than it could be.  

In the best of all possible worlds, each node would eliminate activities that do not add value to its own transformation process such that it can reap the highest possible margin, subject to maximizing and maintaining the total value proposition for a value network or at least a supply chain within a value network.  This is the best way to ensure long-term profitability, assuming a minimum level of parity in bargaining position among trading partners and in advantage among competitors.

Delivering insights to managers that allow them to react in relevant-time without compromising the value of the network (or a relevant portion of a network, since value networks interconnect to form an extended value web) remains a challenge.

The good news is that many analytical techniques and the mechanisms for delivering them in timely, distributed ways are becoming ubiquitous.  For example, optimization techniques and scenarios can provide insights into profitable ranges for decisions, marginal benefits of incremental resources, and robustness of plans, given uncertain inputs.

When these techniques are combined with intelligent visibility that allows you detect and diagnose anomalies in your supply chain, then everyone can make coordinated decisions as they execute.  

I will leave you with these words of irony from Dale Carnegie, “You make more friends by becoming interested in other people than by trying to interest other people in yourself.”

Thanks again for stopping by and have a wonderful weekend!

Supply Chain Action Blog

The supply chain is more properly designated a value network through which many supply chains can be traced. Material, money and data pulse among links in the value network, following the path of least resistance.

If each node in the value network makes decisions in isolation, the potential grows for the total value in one or more supply chain paths to be less than it could be

In the best of all possible worlds, each node would eliminate activities that do not add value to its own transformation process such that it can reap the highest possible margin, subject to maximizing and maintaining the total value proposition for a value network or at least a supply chain within a value network.  This is the best way to ensure long-term profitability, assuming a minimum level of parity in bargaining position among trading partners and in advantage among…

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Resilience Versus Agility

Just a short thought as we move into this weekend . . .

Simple definitions of resiliency and agility as they relate to your value network might be as follows:

Resiliency:  The quality of your decisions and plans when their value is not significantly degraded by variability in demand and/or changes in your competitive and economic environment.

Agility:  The ability to adjust your plans and execution for maximum value by responding to the marketplace based on variability in demand and/or changes in your competitive and economic environment.

You can take an analytical approach that will make your plans and decisions resilient and also give you insights into what you need to do in order to be agile.

You need to know the appropriate analytical techniques and how to use them for these ends.

A capable and usable analytical platform can mean the difference between knowing what you should do and actually getting it done.

For example, scenario-based analysis is invaluable for understanding agility, while range-based optimization is crucial for resiliency.

Do you know how to apply these techniques?

Do you have the tools to do it continuously?

Can you create user and manager ready applications to support resiliency and agility?

Finally, I leave you with this thought from Curtis Jones:  “Life is our capital and we spend it every day.  The question is, what are we getting in return?”

Thanks for stopping by.  Have a wonderful weekend!

A Few Random Thoughts

This week, I was privileged to attend the INFORMS Analytics Conference in Huntington Beach, California and the IEG S&OP Conference in San Francisco.  I heard some insightful points and thought I would list a couple here (with appropriate attribution) along with a few thoughts of my own.  I hope that at least one strikes a chord with you.

If you use a heuristic to solve a problem with 100% complete and clean data, using a data model that exactly represents reality at any given moment, you still have an inexact answer.  But since such data and data models are rare (or nonexistent), even a pure optimization is still inexact and, in effect, a heuristic solution requiring both art and science on the part of the analyst. (Colin Kessinger, End-to-End Analytics)

If the purpose of Sales and Operations Planning is to make the best integrated decisions for running your business, then you will have a firm, published schedule and people will schedule other meetings (even customer meetings) around it. (Bob Ratay, SAP),

Key capabilities in an S&OP decision-making process are business agility, versatility, and elasticity.  (Olaf Gelhausen, Infineon)

S&OP is about a range, not “one-number” – one plan with a range and distribution of probabilities, but not one number. (Olaf Gelhausen, Infineon)

The best business decisions, even very qualitative ones such as those in the fashion industry are built on a foundation of rigorous data analysis and decision modeling, providing the qualitative decision-maker the largest head-start possible by reducing the “solution space” and delivering insight into the most sensitive tradeoffs.

Working with people is the hardest part of any business challenge – by comparison, the mathematics are relatively easy.

In business planning, longer term investment decisions require detailed scenario analysis.  Near term execution decisions require existential insight into the cash flow changes and their causes.  One might call the latter, “analytical awareness”.

Once sources have been qualified, sourcing decisions among sources (both near and far, “in” and “out”) should be cost-optimized and dynamic (Olaf Gelhausen, Infineon).

Thanks for dropping by Supply Chain ActionPlease feel free leave your random thoughts as a comment below or send them to me, and I’ll try to include them in an upcoming post.

Until next week, always choose life, light and love and don’t forget to laugh along the way.

Have a wonderful weekend!

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