Supply Chain Customer Focus – New Year Recommendation – Part Three

Supply Chain Customer Focus“Do what you do so well that your friends will want to see it again and bring their friends.”  -Walt Disney

This is the last in a three-part series on supply chain recommendations for the new year. To recap, I started this series by reviewing the ‘best of the best’ trend predictions from the last 5 years, and then making recommendations for supply chain modifications to match those trends. I looked at output from 4 different groups: Gartner Analysts, IDC, Ferrari Group, and SupplyChainBrain. I saw prediction patterns emerging that led to my own recommendations for the year ahead.

The first two blogs in the series presented profitable proximity and risk management, both trending supply chain topic predictions for the coming year. As promised in the last blog, though, I feel that this third and final topic for the supply chain is the ‘best’, or what I feel offers the most promise for your investment: customer focus.

Prediction #3: Supply chain customer focus will continue as a strategic priority.

Supply Chain Customer Focus

Customers have been in the forefront of supply chain predictions for the last 4 or more years:

  • 2009 IDC Prediction #6: Customer Relationship Management (CRM) and consumer-centricity efforts continue to grow across the modern supply chain as manufacturers attempt to improve innovation efforts. The sale is just the start as services become an increasingly important part of the ‘product experience’.
  • 2013 IDC Prediction #3 – On the demand side of the supply chain, recognizing the need for better service levels and mass customization, manufacturers look again to postponement techniques and data analytics to drive more effective customer insights and ‘smarter’ fulfillment.
  • 2013 IDC Prediction #5 – Service excellence becomes a strategic priority.

Leading consultants like Forrester have defined the “Age of the Customer” as a 20-year cycle wherein CIOs and CMOs will reinvent themselves to win in this age. Forrester points to a transition from focus on manufacturing, to distribution, to information management, to lead up to today’s more towering power of the customer. They say that the leaders in use of technology within this customer obsession hold the key to winning that customer race.

This seems obvious, doesn’t it? But the technology push to deliver a smarter, more innovative product, at a quicker pace, for less cost, and with more satisfaction, is accelerating. Customers expect it, and pay back with their loyalty, and the company stock prices reflect it time and time again. Think about companies like Starbucks, Amazon, and Apple: all at the top of their game, with soaring customer ratings. Amazon has mastered the customer relationship model with customized suggestions based on your purchases. Starbucks is well-loved because of the customer experience as much as the product. Apple, with innovations and scheduled announcements of new products to meet continual customer demand for a product more powerful than the last, came in at the top of the PC ratings for the 10th year running, and in 2012 took over as the world’s most valuable company, with a 4% piece of the S&P 500 pie.

Supply Chain Customer Focus

So with those companies on the pinnacle, they stay ahead if they prioritize supply chain customer focus.  Mostly, it’s about competition: besides being more cost-effective, those companies know that they simply have to have the best customer satisfaction.

  • Customers increasingly want their orders faster. This allows the companies who offer rapid delivery to force out those who don’t keep finished goods inventories. In this environment, good demand forecasting is a must for companies to level out production quantities, build the most competitive transportation and warehousing structures, compete the best supplier contracts, and maintain the most efficient operations.
  • Internal organization can improve customer experience. Collaboration is being encouraged within companies to give the customer the experience from purchase through customer service. Our best relationship with one of our most recent vendors underwent seamless transitions from sales to implementation to customer advocates: we’re hooked!
  • External factors give breadth beyond historical and seasonal forecasts.  Traditional forecasting methods were based on historical and seasonal data, and do not reflect the impact of the economic market’s volatility and resulting customer shifts. For example, consumer attitude, even after financial situations are taken into account, is a leading  indicator to durable goods spending every year. Tracking of indices like fuel costs, unemployment rates, and weather patterns are more examples of leading indicators to consumer demand. One of our customers, a manufacturer of snow-clearing products, faced a winter drought that severely decreased demand for their product. That year they admitted that this volatility wreaked havoc on their profits!  Their reliance on external indicators of weather patterns, as fed into our forecasting platform, is now allowing them to predict and adjust their manufacturing and inventory levels to those conditions in real-time, drastically reducing required inventory, and leveling out production and logistics costs.
  • Providing the latest and greatest products can draw customer loyalty. Customers depend on innovation, and will offer their loyalty to those with the newest, biggest ideas. But studies show that more R&D spending does not equate to more revenue. Only a small percentage of product ideas make it to launch. Less money is lost on a ‘kill’ of a product release pre-launch than a ‘fail’ post-launch! Demand forecasting plays a large part in segmenting what products are worthy of adding to the supply chain. Also, even improvements to old products can alter demand, so demand needs to be analyzed BEFORE any resulting disruptions in production, finance, and logistics are made.
  • The closer you are to the customer, the better your service. Sales and marketing research keeps a hand on the customer behavior dynamics through reward-based questionnaires, online forums, blogs, and interviews, and retargeting. Direct feed of information through technology by way of Point-of-Sale or Point-of-Use gives priceless real-time feedback. Evolving from this is the cycle of sensing consumer behavior, measuring marketing effectiveness, adjusting the marketing for optimal impact, all leading to demand-driven forecasting.
  • Design your supply chain to meet customer predictability. A key to supply chain optimization is to know your customer and your products in terms of predictability, and adjust accordingly. Employ more lean supply chain tactics in more predictable markets, and more agile supply chain tactics in less predictable markets. Toyota, for example, evolved its lean philosophies under periods of predictably high demand. Agility, though born out of necessity to disruptors to the supply chain such as demand volatility and new product introductions, leads to high customer satisfaction: items always on the shelf, no back-orders, no waiting for special orders.
  • Given the above, find the best and broadest talent possible to optimize your supply chain for the Age of the Customer.

If you compare the list above to my recommendations in the prior blogs about profitable proximity and risk management, it is clear that the supply chain customer focus goals are more numerous, and more impactful to business survival. Demand forecasting is the common thread above, and the window to the customer’s behavior. Speaking of forecasting, Gartner expects 10.6 percent growth in 2014 investment in these B2B analytics, particularly in the SCM space. (5) Best-of-breed providers know that providing differentiators like personalization, ease-of-use, learning engines are a few of the ways to help their clients stay focused on the customer at all times.

Recommendations for Supply Chain Customer Focus

PadlockThere are many roads to great customer focus. Based on my research and experience with our clients, here are my top recommendations for supply chain customer focus:

  1. Build a talented supply chain team that will innovate for the customer’s needs and collaborate internally to build brand loyalty, and design your supply chain with demand volatility and customer satisfaction in mind. See if supply chain segmentation can turn your customer focus into supply chain success.
  2. Keep your finger on the pulse of the customer, and your competitors, and listen for cues to market demands, delivery competition, and customer satisfaction ratings. Using a demand-driven strategy in your supply chain helps you focus simultaneously on profitability and the customer.
  3. Forecast demand to achieve optimal inventory in existing and new products, with priority toward maintaining and growing customer satisfaction. Use all methods available to increase your forecast accuracy, including external indicators.

I recently read an article on sales with the message that if we could just maintain our current customers, and limit expenses to that revenue, that all new customer revenue would be just ‘gravy’. How easy that would be with great customer focus!  After all my recommendations, I believe that if you can only do one of the recommendations above, choosing one from the Customer Focus category should come first. Both B2B and B2C customers will remember your successes and especially failures.  Years ago, after a full day on Colorado mountain trails, energized but hungry, my group went to a popular eating spot best-known for their chicken dishes. That day, they were out of … chicken. It was a long time until we returned there for a meal!

Next time, I will compile the full list of my supply chain recommendations from all three categories predicted by experts, under the categories of profitable proximity, risk management, and customer focus.

How did customer focus play a part in your supply chain up until now? Did it make a negative, neutral, or positive impact to your business?


Dilbert, United Feature Syndicate, February 2, 2001.
Journal of the American Statistical Association, Volume 58, Issue 304, 1963,pp. 899-917, Ten Years of Consumer Attitude Surveys: Their Forecasting Record
Industrial Marketing Management, Vol 29., No. 1., 2000, “The Agile Supply Chain : Competing in Volatile Markets”, Martin Christopher

New Product Forecasting – Then and Now


New product forecasting is not new itself at all. It has been around for decades. However, the speed of new product releases and the subsequent product lifecycle have changed radically with the advent of advancing technology and more sophisticated consumer demand. Think about it: the color television was introduced in 1954, and did not go ‘main-stream’ until 1964. 10 years! Now, fast forward 60 years. Since 2001, a little over a decade ago, the following were a few new products that were introduced: the Apple iPod, Hybrid cars, Bluetooth earpieces, and satellite radio. The pace is at break-neck speed and not slowing down.

New Product Proliferation

Why the proliferation of new products? Here are some of the most important reasons for the increase in new product introductions:1

• Growth companies show a greater investment in new products over existing products.

• New product introduction correlates with a larger market share, while the market share of older products is impacted by competitive challenges and dwindling customer interest.

• Companies are increasingly dependent on new product revenues to drive their top lines every year.

• New products allow companies to grow revenues and retain high margins by creating new customers in new markets.

• Even when a company’s top line isn’t increasing, it needs new products to replace existing products that are reaching end-of-life.

• New products drive growth, which drives value, and high valuations allow companies to raise capital, acquire competitors, and attract the best talent.

• Companies with a robust R&D strategy are statistically 73% more profitable. See the chart below for a look at the correlation between R&D spending and GDP growth.



Profits Reflect R&D Investments


Not surprisingly, new product revenue as a percentage of total sales is on the rise, with recent figures placing the number at over 30%.2 Grocery stores, for example, add an average of 10,000 more SKUs a year, and then optimize profitability down to a shelf level, escalating the pressure for accurate demand forecasting on manufacturers and their suppliers.2 With that, however, new product forecast error within the first 6 months is about 50%, or twice that of the error for a baseline SKU.2 After all of the painstaking work to develop, launch, and build forecasts for those products, 70 to 80% of them fail in the first 10 years.2 I believe that most people think like I do: We can do better than this!

New Product Forecasting – How is it Unique?

New product forecasting is more complicated than for established products, primarily due to the lack of historical data that is the foundation of most models. There is no long time series of data or the accompanying trajectory from the past demand on which to base future demand. The forecasting accuracy, though, is even more important with new products, as getting it right from the outset can be key to future sales, in a kind of snowball effect. Lost sales that result from an underestimation of demand could lead to the loss of future revenue stream from the loss of related sale of accessories, maintenance contracts, spare parts, and complementary products. Even worse, the competition can step in to take the market share that is left on the table. This ripple effect makes it even more important to come out of the gate with the best possible new product forecast accuracy.

Evolution of New Product Forecasting Methodologies

I took a look back in time at how new product forecasting has evolved. I was surprised that a lot of the practices and techniques used today were used as far back as over 40 years ago. As far back as the 1970’s, experts in the field already recognized that forecast accuracy was key to new product profitability. These sources expressed that their concerns for the forecast were not just in demand, but in what could become changes to the product profitability and lifecycle. Back then, the methods they recommended, ordered by estimated quality of the results, were qualitative in nature, based on expert opinion, and often done without a computer3:

• Market Research: Consumer data gathered via questionnaires, surveys, and any available analysis. Viewed as the best of the methods.

• Delphi: Expert panel interrogated with questionnaires. Originally introduced in the 1940s. Anonymity used to reduce biases.

• Historical Analogy: Comparative analysis of introduction and growth of similar new products.

• Visionary Forecast: – Personal insights, judgment, available facts analyzed based on past events. Viewed as the least scientific of all methods.

Believe it or not, these same methodologies are still being used today, albeit in a more automated form.  Aided by the digital age, a big shift has been in the expansion of the Market Research category. Some of the new market research techniques are:4

• What-if and scenario analysis is now done to gauge consumer reaction before traditional forecasting methods are employed.

• Estimates are based on outgrowth of old products, as a substitute for an existing product, or on the basis of a pattern of growth of an established product. But these are now refined with sample sales, surveys, market penetration analysis, and the use of knowledgeable dealers with greater customer knowledge and interaction.

• Demand experiments, as they are called, are now more widely conducted on a small group of customers, with the results extrapolated to a larger population. For example, marketing firms will often test a new consumer product in a geographically isolated “test market” to establish its probable market share. This experience is then extrapolated to the national market to plan the new product launch.

Best Practices

Armed with the methodologies above, best practices will help you achieve the best new product forecasting. Here are some guidelines that I recommend:

• Build a time and monetary commitment, with full support from the C-suite, and try to reduce competitive and bias forces between departments.

• Use forecasting data sources that bring the forecaster as close to the consumer as possible. Methods beyond surveys can include demos, focus groups and forums, and product demonstrations. Structure market analysis to remove as much subjective data as possible.

• Use a variety of methods throughout the product development process to develop a better forecast, and use continuous improvement to refine.

• As always, manage uncertainty with risk mitigation techniques, especially for those new products that don’t have the benefit of a ‘like’ product with which to obtain historical forecasting data.

My Takeaways

1. Innovative products keep your revenues strong, increase your market share, and grow your business.

2. New product forecasting is becoming more important than ever with shortening lifecycles and proliferation of new products in many industries, from manufacturing to high tech to food to retail.

3. The correct forecasting framework for process, people, and technology, becomes even more important with new product inherent difficulties of lack of historical data, biases of judgment data, and errors introduced with consumer surveys.

Yogi Berra

New products are at the core of the leading companies, and the old adage ‘Change or Die’ fits here very well. The investment made in new products from R&D to manufacturing to distribution requires follow-through in demand forecasting to have a success story that can further a company’s revenue. Profit and growth result from better supply chain effectiveness, reduced labor costs, optimum cash flow, and high levels of customer satisfaction. But the success stories do more than just drive the bottom-line: they can further a company’s very brand identity. Remember the new products at the beginning of the blog? I am betting that the forecasting efforts behind the scene played a large part of the ultimate success of all of those new products. In taking a look at the methodologies here, I think that was no easy task! But in the face of these challenges and uncertainties, it’s good to laugh once in a while. As Yogi Berra once said, “It’s tough to make predictions, especially about the future.”

Add your comments to the conversation!  I would love to hear your feedback and lessons learned.


1.  Singh, Mahender, ESD 260 Lecture, September 20, 2006.

 2.  “Achieving Excellence in New Product Forecasting”, July 30, 2013, IBF Supply Chain Forecasting and Planning Conference 2013.

 3.  John C. Chambers, Satinder K. Mullick, and Donald D. Smith, “How to Choose the Right Forecasting Technique”, Harvard Business Review Magazine, July 1971.

 4.  “Three Simple Methods for NPD Sales Forecasting (Methods)”, Global NP Solutions.

Image “Time for Innovation” courtesy of Stuart Mills /

Image graph courtesy of “R&D Spending Slows”,

Image “Yogi Berra” courtesy of Gary Bedingfield /

External Data – The Next Frontier

 Considering External Data in Demand Planning

When you make business decisions, you are almost always looking forward. You’re thinking about the future. This means you’re thinking about forecasting and planning. And what this really all means, is that you are thinking about demand.

When you make critical decisions around demand, you need information from disparate data sources about your market, your customers, the economy, the weather, your costs, your profit margins, what your competitors are doing, your ability to stimulate demand, your company’s capacity to meet the expected demand, among other things.

When thinking about all these factors, and when looking into the future to make these decisions and achieve the desired outcomes, it seems obvious that we have a problem. The data that has historically fed the forecast (past orders, past shipments, last month’s prices) is going to be less than adequate.

The fact of the matter is that the most important business decisions, and the fundamental practice of forecasting itself, are based primarily on backward-looking, after-the-fact, inward-looking data. This is why it’s no mystery that a majority of companies are dealing with 50% or greater error at the execution level of forecasting measured on an absolute basis. With this in mind, can you think of a better way to control business costs than to reduce forecasting error?

Besides improving the forecast platform, improved information would be the single most important tool for reducing forecasting error. If you could obtain more direct feedback from your customers (what they’re selling, what they have in inventory, how their latest promotion was performing) would that help your forecasting and planning? If your business is seasonal, would more accurate weather information help in your decision-making? If you supplied the residential construction market, would daily updates on housing starts have an impact? Does unemployment impact the consumption of high-end craft beers, and does this vary by region? Does overcapacity in the market among your competitors impact your profit margins? Do more than two or three external factors impact demand for your product at the same time?

Yup – we are going to have to talk more about this one. External data quality and timeliness, and then managing that information to optimize your decisions, will be the next frontier in business management. The good news is that Demand Foresight believes we have the platform, and there is now a great proliferation of more accurate information and competitive data markets available for more industries. Any input, experiences, examples, questions and critiques will be welcome.

What our forecasting and planning software can do.

Put up or shut up: The corporate guarantee

By Gene Tanski, CEO, Demand Foresight

Things were getting heated at the sales meeting. The cause of my anger was an old theme: Industry-wide, client expectations for business software were so low that stories about the failure of big enterprise projects had practically become wallpaper.

Where were the repercussions for the business performance that never materialized? The big systems failed to deliver what they were supposed to over 70 percent of the time and the big checks just kept getting cut with no accountability. The whole dynamic needed to be nuked.

In the heat of our discussion about the institutionalized negligence of our gigantic competitors and how we could exploit it, a 25-year-old, Xbox-playing member of our team, said: “Dude, if we’re that bitchin’, why don’t we guarantee it?”

“What?” I asked him.  “Are you nuts?  Do you have any idea how software works?”

“No, not really. But I hear you guys constantly complaining about how everyone else over-promises and under-delivers. Why not do something about it?”

That simple dare became our biggest differentiator – and, more surprisingly, revolutionized the way we run our company.

During the dot-com boom, new businesses were founded on completely new thinking by young professionals, unencumbered by any notion of what was or wasn’t possible. Most of that potential was never realized, though – at least not in the first wave, since the young visionaries had no grounding in the disciplines that would sustain their visions over time.

However, we wondered, could our team fuse the experience of the old hands with the “anything is possible” optimism of our young teammate?

Once we got our minds around the concept, the experienced guys on the team were able to adjust some long-held assumptions and work through how to handle the risk, build the pricing and generally operationalize the concept.

It was a little bit like learning how to fly, as characterized by Douglas Adams in his “Hitchhiker’s Guide to the Galaxy” books: the key to flying was to throw yourself at the ground really hard, and miss.

It was exhilarating. I felt like we had just missed the ground by a huge margin, and instead were flying straight to a business model that embodied the exact opposite of everything we hated about the IT and consulting world.

The guarantee was an explicit one – with no wiggle room. Clients would measurably improve their business performance — in our instance, a 25 percent minimum reduction in absolute forecast error — or we wouldn’t get paid. Not a dime.

It could have been a disaster, but taking this leap of faith actually did incredible things for our organizational focus – and ultimately helped cement our culture and internally align all divisions of the company.

The developers know that the software has to work and be relevant to specific job responsibilities or they don’t get paid. Implementation and technical support? They better get it right or they don’t get paid. Sales people? They had better understand the client problem and know exactly how to solve it, or … well, you know…

Another benefit of this ‘put up or shut up’ philosophy was the elimination of the need to micromanage. Once everybody understood that the promise would not bend, I found I could trust everyone to solve problems the way they thought best.

Vacation policy? Didn’t need it. Our team was entrusted to take the time off that they knew they could afford to take. Office? Wherever they could open a laptop and do their best work. This culture tells us a lot about the kind of people we should hire — can they stay motivated and productive in our unique environment?

So an energetic, passionate clash of skilled professionals turned out to be lightning in a bottle. It let us fuse the brashness of youth with organizational know-how.

We still argue in meetings, of course. But these days I enjoy it. You never know what sorts of benefits it can produce.

This post first appeared on Venture Beat: Entrepreneur Corner on October 26, 2010

Head in the Cloud? Keep your feet on the ground.

Cloud computing/SaaS ascendancy — used as interchangeable terms in some conversations — picked up lots of media steam last year and continues to be the hot topic of 2010. While this entry is not intended to be an exhaustive dissertation, there are couple of points that resonate with me  – what do you think?

BI in the cloud could be the next killer application. That word — “next” — is important. Because we must look at the cloud not only for its current limitations and capabilities, but through the filter of what technology means to your business strategy, your identity, and those capabilities that make your company different and special and competitive. Because cloud or no, ultimately you need technological solutions that enable your business success. Altering your business model to fit the platform might fundamentally damage your ability to compete.

Can the cloud do heavy lifting?
I have no doubt that magnificent things are possible in the cloud, but many of the current advances seem more suitable to CRM and the like: collaborative applications like Salesforce let companies offload the cost of ownership of hosting the app, and everybody knows who talked to which customer, about what, and when.

But what happens when a company needs to know what a 10% reduction in their product price during Christmas would mean in terms of increased demand, impact on other products, and their industry as a whole? Heavy demand planning  and forecasting/modelling functions like this can’t be easily or reliably done in the cloud right now.

Could all this change in the next few years? Absolutely. But computationally demanding, mission-critical practices that require rapid response on massive amounts of data are on the other side of the wall, as it currently stands. So as we rhapsodize over the cloud, it’s important to remember that the cloud can’t solve everything, at least not yet.

Getting your feet off the ground: the leap of trust required to get over the cultural barrier
One of the biggest pros for the cloud is the power of intra-enterprise collaboration — bring enterprises and professionals together to help improve all participants of the value chain. But what we face here is a cultural obstacle rather than a technological one: companies have the technology right now to collaborate across company boundaries. But can we come to grips with security issues and not owning our data? Can we trust our informational lifeblood to other companies, even our customers?

In order for the cloud to reach its potential, these are the cultural questions that every company will have to solve. We have to trust that the information is secure, and that customers or channel partners won’t take advantage of the information. The real power of SaaS is almost beside the point: the real issues are culture, trust and acceptance.

When Marco Polo and the Italians began opening up new trade routes, cultural differences had to be overcome, new relationships built. Now companies and the professionals who give them voice are standing in front of another huge opportunity, with only mistrust and fear of the unknown in between them and the new possibilities. Seems like the world’s repeating itself all over again.

The dangers of fitting your company to a platform
There are subtle but profound dangers in trying to apply the cloud correctly for your company.  Human nature leans towards the comforts of standardization, and it’s no less true in the technology strategy of most companies. Having uniform processes and knowing what to expect every time eases our minds. But there’s an ironic downside to this: the more you standardize, the easier it is for your tech department to be outsourced. And the more you standardize, the less you focus on competitive advantage. Too many companies fit themselves to the tool, and not vice versa.

You want the power of the Cloud for when it’s appropriate, but be sure not to limit your enterprise in how you can compete and build on your strengths. The ones who stand out over time are the ones who agree their vision and ensure that everything in the enterprise, including technology,focuses on achieving that vision. At this particular point in time, with the advent of the Cloud, SaaS 1.0 and the legacy of ERP, what your company needs more than ever is a clear vision of what your competitive advantage is: decide what makes your company better, and find the right mix of technology (and ongoing adaptation/evolution) that’s going to preserve and enhance that advantage.