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!

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Analytics vs. Humalytics

I have a background in operations research and analysis so, as you might expect, I am biased toward optimization and other types of analytical models for supply chain planning and operational decision-making.   Of course, you know the obvious and running challenges that users of these models face:

  1. The data inputs for such a model are never free of defects
  2. The data model that serves as the basis for a decision model is always deficient as a representation of reality
  3. As soon a model is run, the constantly evolving reality increasingly deviates from the basis of the model

Still, models and tools that help decision-makers integrate many complex, interrelated trade-offs can enable significantly better decisions.

But, what if we could outperform very large complex periodic decision models through a sort of “existential optimization” or as a former colleague of mine put it, “humalytics“?

Here is the question expressed more fully:

If decision-makers within procurement, manufacturing and distribution and sales had the “right time” information about tradeoffs and how their individual contributions were affecting their performance and that of the enterprise, could they collectively outperform a comprehensive optimization/decision model that is run periodically (e.g. monthly/quarterly) in the same way that market-based economies easily outperform centrally planned economies?

I would call this approach “humalytics” (borrowed from a former colleague, Russell Halper, but please don’t blame him for the content of this post!), leveraging a network of the most powerful analytical engines – the human brain, empowered with quantified analytical inputs that are updated in “real-time” or as close to that as required.  In this way, the manager can combine these analytics with factors that might not be included in a decision model from their experience and knowledge of the business to constantly make the best decisions with regard to replenishment and fulfillment through “humalytics”, resulting in constantly increasing value of the organization.

In other words, decision-maker would have instant, always-on access to both performance metrics and the tradeoffs that affect them.  For example, a customer service manager might see a useful visualization of actual total cost of fulfillment (cost of inventory and cost of disservice) and the key drivers such as actual fill rates and inventory turns as they are happening, summarized in the most meaningful way, so that the responsible human can make the most informed “humalytical” decisions.

Up until now, the answer has been negative for at least two reasons:

A. Established corporate norms and culture in which middle management (and maybe sometimes even senior management) strive diligently for the status quo.

B. Lack of timely and complete information and analytics that would enable decision-makers to act as responsible, accountable agents within an organization, the same way that entrepreneurs act within a market economy.

With your indulgence, I’m going to deal with these in reverse order.

A few software companies have been hacking away at obstacle B.”, and we may be approaching a tipping point where the challenge of accurate, transparent information and relevant, timely analytics can be delivered in near real-time, even on mobile devices, allowing the human decision-makers to constantly adjust their actions to deliver continuously improved performance.  This is what I am calling “humalytics”.

But the network of human decision-makers with descriptive metrics is not enough.  Critical insights into tradeoffs and metrics come through analytical models, leveraging capabilities like machine learning, optimization, RPA, maybe in the form of “mini-apps” models that operate on a curated supra set of data that is always on and always current.  So, at least two things are necessary:

1. Faster optimization and other analytical modeling techniques from which the essential information is delivered in “right time” to each decision-maker

2. An empowered network of (human) decision-makers who understand the quantitative analytics that are delivered to them and who have a solid understanding of the business and their part in it

In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. (ftp://ftp.deas.harvard.edu/techreports/tr-06-11.pdf)  Maybe, we don’t need swarm of robots, after all.  Maybe we just need empowered decision-makers who not only engage in Sales and Operations Planning (or, if you will, Integrated Business Planning), but integrated business thinking and acting on an hourly (or right time) basis.

What think you?

If you think this might make sense for your business, or if you are working on implementing this approach, I’d be very interested to learn your perspective and how you are moving forward.

I leave you with these words from Leo Tolstoy, “There is no greatness where there is no simplicity, goodness, and truth.”

Have a wonderful weekend!

Part 3 – Finding the ROI for an Investment in an Analytical SCM Solution

Technologyevaluation.com published a piece of mine on this topic a few years ago, but the ideas are important, so I am recapitulating the them here.  The first post in this series introduced the topic of overcoming the challenges to calculating the return for an investment in an analytical supply chain software application.  This post deals with the second of four challenges.

Part 3 – Second Challenge – Business analysis skills are lacking – “We are looking for the vendor to tell us!”

Can the Vendor Help?

After all, since the software vendor is proposing the solution, shouldn’t the vendor know how it will affect your company?  The vendor probably does have some useful information about whether the decision to purchase will be of some benefit.  They will be able to tell you in general what business symptoms can be affected.  They may even have survey data that show how other companies in your industry, or at least in other industries, have reported benefits.  They should have anecdotal evidence of how some existing customer plans to benefit or has benefited from investing in their approach or solution.

There are a couple of problems with the vendor’s input. First, the vendor cannot be objective. The vendor’s business is on the line.  It is probably a fierce competitor and its representatives may be under pressure to make this deal happen.  Second, directional information, surveys, and anecdotes may or may not be reasonable predictors of how your company will fare.

The current state of your business processes and how they are performing is pivotal to the potential return.

What Should You Do?

This reaction “We are looking for the vendor to tell us!”, is similar to the first challenge and reaction,“We need to know now!”  This second challenge is less driven by time than by the perception that the skill to perform the cause and effect analysis, data gathering, and statistical analysis does not reside within your company.  But, it is important for you to be able to understand, monitor and control the process, even if you use an outside consultant. Following these steps will help you do just that:

1. Identify and quantify undesirable symptoms.

2. Perform cause and effect analysis to find possible root causes.

3. Gather data by reason code (in order to prioritize root causes).

4. Quantify and analyze root causes (Pareto analysis).

5. Estimate the positive impact of your investment decision (e.g. a new supply chain management tool) on your root causes.

6. Extrapolate this to the positive impact on the undesirable symptoms.

7. Perform sensitivity analysis around your estimate in step 5 by varying the estimate and repeating step 6. This will give you a sense for the range of possible outcomes that is reasonable.

Your success at steps 1 through 7 will be most likely if you follow two additional guidelines:

1. “Time box” the analysis to a minimum of 2 weeks and a maximum of 30 days. These time frames are really only a guide to represent the order of magnitude for the minimum and maximum time frames.

2. Assign a primary internal resource for each area of analysis you undertake.

Once again, I’m grateful that you took a moment to read Supply Chain Action.  As a final thought, I remind you of the familiar words to ponder, “Luck is that point in life where opportunity and preparation meet.”

 

Part 2 – Finding the ROI for an Investment in an Analytical SCM Solution

Technologyevaluation.com published a piece of mine on this topic a few years ago, but the ideas are important, so I am recapitulating the them here.  The first post in this series introduced the topic of overcoming the challenges to calculating the return for an investment in an analytical supply chain software application.  This post deals with the first of four challenges.

Part 2 – First Challenge – Limited time to perform analysis – “We need to know now!”

It is usually true that, at some point, the incremental benefit of additional information decreases as one moves along the continuum from limited information toward the goal of perfect information about the future.  However, you will reap significant benefit from knowing with some certainty what you can know in a 2-4 week period.  So, the output of some rigorous analysis should not be under valued.

If you truly do need to know something with immediacy, here are some tips for a quick, cursory approach to identifying the potential return from an investment in several aspects of analytical tools for supply chain or value network, management.

Collaborative Forecasting and Planning

If you track the accuracy of your forecasts, then you have some idea whether or not your company anticipates marketplace requirements well.  However, you must look beyond the aggregate annual revenue projection.  To understand the impact of demand planning on operations, it must be examined at a level that can be executed.  In other words, are you accurately anticipating the requirements for parts, people and processing at a fairly detailed level?  If significant forecast misses regularly occur, then working together with your major customers to plan for demand may have a notable impact on your operating costs.

Your suppliers may levy additional charges because you have passed on abrupt corrections in your demand for their products and services as a response to changes in your own demand profile.  These additional charges derive from additional setups, work-in-process inventory, and lost material incurred by the vendor on your behalf.  If the structure of your industry prohibits suppliers with less bargaining power from passing on these charges, they are still no less real a cost.  Everywhere that the value network generates unnecessary costs, a savings opportunity exists for the members of the value network.  In this case, such savings might be with reach if you extend the collaborative planning loop to include not only your customers, but also your suppliers.

Optimized Manufacturing Planning

Optimized manufacturing planning entails the use of math and analytical tools to choose the least cost combination of plant, equipment, personnel, and material that will meet planning objectives that may include one or more of the following examples:

• Maximizing inventory turns

• Maximizing on-time delivery

• Maximizing revenue

• Maximizing profit

• Maximizing throughput

Because optimized manufacturing planning provides decision support that considers multiple tradeoffs and constraints, it may not be easy to point to one indicator that demonstrates the potential for improvement through implementation of this powerful technique.  However, clues can be found in your manufacturing cost variances and in your performance against the business metrics that correspond with the objectives you want to maximize.

Inventory Planning and Optimization

Look at your financial reports and make a judgment as to whether your balance sheet or your income statement will be positively affected by the decision.  For example, examine inventory levels relative to your revenue.  Calculate inventory turns by dividing revenue by the annual ending (or better yet, trailing 12-month average) inventory.  Compare your turns with your competitors.  If that information is not available, you can use a general industry measure that is more readily available.  The higher the turns, the more working capital you can invest elsewhere and/or the less total interest you pay the bank for the working capital that you borrow.

Gauge your company’s interest expense.  If turns are low and interest expense seems high, then you probably have some significant room for improvement in the way that you make decisions about acquiring and producing inventory.

Does your company keep a financial reserve account against inventory assets (a contra account)?  Does the proportion of your inventory that may have to be written down at the end of the year indicate that your company is making enough of the right decisions around purchasing, distribution and manufacturing?  If the reserve account seems high, that underscores the importance of having the right inventory at the right time in the right place.  It means that obsolescence is becoming an issue because your planning process is not keeping pace with the volatility of supply and/or demand.

Synchronized Planning and Scheduling

Does your company pay the freight for the product or do your customers pay it?  Perhaps it varies by customer.  It may be that you are paying a significant amount of premium freight in order to meet customers’ demand.  If the premium freight you have paid each month for the last several months is anything but negligible, there may be an opportunity to eliminate most of that expense through tools that facilitate synchronized planning and fast planning cycles.

Take a walk through the plant.  Do you see a lot of inventory that is partially completed?  Are there piles of work-in-process inventory that are not being rapidly used up, either on the shop floor, or in the warehouse?  That is an indication of a planning problem.  It may be that the distribution, purchasing and scheduling requirements are not synchronized.  Or, perhaps there are bottlenecks that the plant manager cannot deal with systematically because he does not have the right tools.  There could also be significant setup times that can be eliminated with more sophisticated planning algorithms.

Accurate Order Promising

Tally up the amount of charge backs you have received from customers in the last 12 months for late delivery.  If you are consistently getting charge backs for late deliveries or short orders, that is another area of cost savings that should be available to you. Accurate order promising that considers your real capabilities might eliminate a portion of those charges.

The sales force may also have a feel for orders that they lose because they cannot accurately commit to customers in real-time.  An integrated software application that provides that capability might yield a competitive advantage.

Transportation Planning

There may be savings available through transportation planning.  If you have any significant level of less-than-truckload shipments, you may be paying too much for freight.  The challenge of determining the least cost route when many alternative groupings of multiple stops into routes must be considered requires the rapid use of advanced algorithms in order to achieve an optimal, or near optimal result.

If most of your shipments are to consumers, almost every pair of order lines that ship separately to a customer within a given 24-hour period is an opportunity for improvement through co-packing.

Statistical Process Control

Another place to look is in the area of returns.  Unless you are an electronic retailer or a mail order house, returns should not be a significant cost of doing business.  How are they trending?  Talk to manufacturing, distribution, customer service, or all three and you will get an understanding of how often things come back and why. You may find an indication of a quality problem in manufacturing, packaging or distribution processes (shipping and handling, or possibly sorting).

That’s Part 2 — the longest part, so I promise the others will be shorter.

Thanks again for stopping by. I’m not sure who said this, but I will leave you to ponder it this week:  “Don’t be troubled if the temptation to give advice is irresistible; the ability to ignore it is universal.”

 

Why the Soft Side of Analytics Is So Hard to Manage

No real post this week, but I’ll point you to an article of mine that was published this month in Analytics.  You may recognize it as a combination and enhancement of two of my previous blog posts.

Answering Questions that Your ERP and APS Can’t

I have worked for some large software companies.  I loved many aspects of those experiences.  But, do you want to know the toughest part of those jobs?  It was meeting someone from one of their customers and getting a reaction like, “Oh, you are the enemy!”  Yes, that’s literally what one actually woman said to me verbatim. 

Now, of course, she did not stop to consider all the things that were much easier for her company to do and to keep straight with an integrated, enterprise suite of software applications from accounting through manufacturing to procurement

What flashed to her mind were the things that she and her colleagues could not do with the software.  That’s the way it is with software.  The first things we notice are what we can’t do, not what we can now do that was impossible before.

What we cannot do with our enterprise software systems, however, is a real problem.  To make matters worse, your knowledge workers can easily out-think a software application vendor’s development cycle.  There are some fairly legitimate reasons for this, of course, but the fact remains that ERP and APS vendors have no shot at supporting the need for ongoing innovation on the part of you and your colleagues who must make constantly make faster, better decisions.

Of course, that explains the popularity of Microsoft desktop applications like Excel and Access.

In the meantime, business managers who are not paid to be statisticians, data scientists, algorithm engineers, or programming experts struggle to build and constantly recreate the tools they need to do their work.

They are paid to ask important questions and find alternative answers, but the limitations of their enterprise resource planning (ERP) and advanced planning systems (APS) systems keep them wrestling just to find and format data in order to answer the really challenging analytical and/or strategic questions.

While it is possible to hire (internally or externally) the talent that combines deep business domain knowledge with data analysis, decision-modeling and programming expertise to build customized, spreadsheets in Microsoft Excel™, faster, more comprehensive and ubiquitous cloud solutions are emerging.  What’s needed in this approach is the following:

  1. A hyper-fast, super-secure, cloud of transaction level data where like data sources are blended, dissimilar data sources are correlated, and most of the hundreds of basic calculations are performed.  This needs to be a single repository for all data of any type from any source.
  2. A diagnostic layer where the calculations are related to each other in a cause and effect relationship
  3. A continuous stream of decision-support models (e.g. econometric forecasts, optimization models, simulation, etc.)

If you ever need to make better decisions than your competition (Duh!), then this kind of framework may speed your time to value and result in a more secure, scalable, and collaborative solution than desktop tools or point software solutions can provide.   

Such a platform would allow you to see what is happening in business context, why it is happening, and a recommendation for your next best action.    

It also provides a way to build decision “apps” for your business.  You know what apps on your phone have done for you.  Imagine what apps for your enterprise could do . . . and all the data is already there or could be there, regardless of data type or source.

I will leave you with these words from William Pollard, “Learning and innovation go hand-in-hand.  The arrogance of success is to think that what you did yesterday will be sufficient for tomorrow.  (http://www.thinkexist.com)

Have a wonderful weekend!

Make Analytics Useful, Meaningful and Actionable

Last week, I identified reasons for the organizational malady of failing to fully leverage analytics to make higher quality decisions in less time.  As promised, this week, I want to share a remedy.

For the analyst, I recommend the following:

  1. Put yourself in the shoes of the decision-maker.  Try to step back from the details of your analysis for a moment and ask yourself the questions he or she will ask.
  2. Engage your decision-maker in the process.  Gather their perspective as an input.  Don’t make any assumptions.  Ask lots of questions.  They probably know things that you don’t know about the question you are trying to answer.  Draw them out.  Schedule updates with the decision-maker, but keep them brief and focused on essentials.  Ask for their insight and guidance.  It may prove more valuable than you think.
  3. Take time to know, explore and communicate the “Why?” of your analysis – Why is the analysis important?  Why are the results the way they are?  To what factors are the results most sensitive and why?  Why are the results not 100% conclusive?  What are the risks and why do they exist?  What are the options? 
  4. Make sure you schedule time to explain your approach and the “Why?”  Your decision-maker needs to know beforehand that this is what you are planning to do.  You will need to put the “Why”? in the context of the goals and concerns of your decision-maker.
  5. Consider the possible incentives for your decision-maker to ignore your recommendations and give him or her reasons to act on your recommendations that are also consistent with their own interest.
  6. “A picture is worth a thousand words.”  Make the analysis visual, even interactive, if possible.
  7. Consider delivering the results in Excel (leveraging Visual Basic, for example), not just in a Power Point presentation or a Word document.  In the hands of a skilled programmer and analyst, amazing analysis and pictures can be developed and displayed through Visual Basic and Excel.  Every executive already has a license for Excel and this puts him or her face-to-face with the data (hopefully in graphical form as well as tabular).  You may be required to create a Power Point presentation, but keep it minimal and try to complement it with Excel or another tool that actually contains the data and the results of your analysis. 

Frustration with your decision-making audience will not help them, you, or the organization.  Addressing them where they are by intelligently and carefully managing the “soft” side of analytics will often determine whether you make a difference or contribute to a pile of wasted analytical effort. 

Thanks again for stopping by.  I hope that these suggestions will improve the usefulness of your analysis.  As a final thought for the weekend, consider these words from Booker T. Washington, “There is no power on earth that can neutralize the influence of a high, pure, useful and simple life.” 

Have a wonderful weekend!

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