Terra Technology

The Third Act

by Lora Cecere on May 2, 2014 · 0 comments

An antagonist (from Greek ἀνταγωνιστής – antagonistēs , “opponent, competitor, enemy, rival”, from anti- “against” + agonizesthai “to contend for a prize,”) is a character, group of characters, or institution that represents the opposition against which the protagonist , or main character, must contend. In other words, an antagonist is a person or a group of people who oppose the main character(s). 

Wikipedia

The stage is set. We are now in the third act. In the script, the supply chain leader is attempting to get value from supply chain software. The pressures are mounting, the service failures are many, and the drama is high. They reach out for answers. Technologies have advanced and they believe that there MUST be a better way. It is less about the cost of software than the delivery of value. The stakes are high. Their career rides on the decision.

If they are a gray hair, like me, they have survived the first two acts of the play. They are callous and skeptical. The stories of “consultant answers” fills their bookshelves like fairy tales stacked on my grandson’s shelf. They know that there is something better out there, and they are looking.

How does the third act end? I don’t know. Let’s look deeper at the plot of the first two acts.

The first act centered on the “birth” of supply chain planning software. The best-0f-breed (BOB) market was a cast of characters. The stories of “bad behavior” are now legend. Unfortunately, the fight became one of market share. Companies like i2 Technologies and Manugistics fought each other. As they battled for market share, the focus on innovation and serving the customer dissipated.

The second act was the promise of the “integrated supply chain.” In this act, very large systems were sold with big price tags and high expectations. The market became mired with large implementations and expensive consulting engagements. The planning systems in this era of software were inferior to the first generation, but they were sold with the belief that 80% would be sufficient. And, that one size could fit all…. Supply chain leaders now know that this was not the answer.

In the third act, companies are waking up. The business requirements have changed. Growth has stalled, and demand and supply volatility is greater. The business pain is high. The complexity of managing a global supply chain has changed everything. Uncertainty is rampant. Due to the amount of investment in supply chain technology in the second act, the CIO is dragging his feet. He does not want to talk about a new system or a different approach. The CIO believes that if he just pushes harder on the tightly integrated ERP providers, that they will step up to the plate.

The third act is very different. Supply chain matters more than ever, and the CIO plays less of a role. To succeed line of business leaders have to learn about new forms of technology and use their influence management to drive supply chain innovation. The traditional definitions of architectures disappear. Here is what I think happens:

  • Analyst Frameworks Matter Less. As the supply chain planning and execution technology landscapes get redefined, new software products, services and taxonomies are defined. As a result, the supply chain technologies of the next five years will be difficult to graph in traditional four-box models.
  • New Capabilities. While the traditional focus for planning was to take transactional data as an input and drive time-phased data as an output, leaders now know that this is not sufficient. Technology capabilities up the ante. As a result, the new solutions will focus on sensing flows and patterns, driving visualization and insights, and producing intelligent rules and policies as outputs. It will be about end-to-end orchestration of volume, mix and profitability. The inputs will be both structured and unstructured data types. It will be less about integration and more about data synchronization. New forms of visualization will make decision support easier.
  • Cloud and Non-Relational Databases Drive New Capabilities. The use of the cloud, and the evolution of Software as a Service models become mainstream.
So, how do I write the script of this act? Who are the players? Let me give it a try.
  • New Players Change the Story. The rise of the dutch software solutions and North American analytics providers changes the course of the play. The conservative, product-centric dutch, offer an alternative to the market giving the buyer a new set of choices. As the anger rises against JDA and Oracle maintenance policies, more and more companies turn to these new solution providers like AIMMS, OM Partners, Ortec and Quintiq. As a result, JDA and Oracle become less relevant.
  • New Forms of Analytics and Concurrent Planning First Confuses, and then Advances the Market. Technology providers like DecisionNext, Enterra Solutions, Llamasoft, O9 Solutions, Solvoyo, Terra Technology and Tools Group offer new capabilities and possibilities. With the confusion, business leaders have to re-skill to understand the new opportunity. As the curtain rises, the first set of demand architectures is unveiled. Supply chain analytics combine advanced optimization with cognitive learning to drive new levels of insights from the outside-in. For the first time, supply chains can test and learn in-vitro around the clock. The fights between IT and line-of-business reach fevered pitches; but dissipate when IT understands the capabilities for insights and visualization.
  • SAP Stumbles and then Recovers. SAP, the provider that has built the strongest and most capable system of record, but has failed at delivering excellence in systems of differentiation, is called onto the carpet. The company stumbles and then recovers at the end of the third act. The announcement of SAP APO re-write onto the HANA platform raises customer ire. As commissions fall for the SAP sales personnel, the company adapts and then recovers. At the end of the third act, SAP starts to copy the best-of-breed innovation that has powered new levels of corporate performance. The press releases and celebrations are served with great fanfare.
  • Logility and Kinaxis Survive and Thrive as the No-nonsense Solutions. Logility and Kinaxis continue to survive and thrive as the focused vendors. They become the partner of choice, based on industry requirements, for a system of record for companies .5M to 2B.
  • Canonical Integration Layers and Collaborative Multi-party Applications drive New Capabilities. With the rise and acceptance of B2B Supply Chain Business Network Providers, EDI VANS carry fewer messages and are less relevant. New forms of application capabilities are developed and birthed on Many-to-Many Architectures. The business value between a synchronized and a tightly integrated supply chain becomes painfully clear for the manufacturers that fail at the start of the next recession.
  • Infor Finds a Niche. The ION architecture and social collaboration with Ming.le offer new opportunities to retrofit very capable old architectures. The pragmatic buyer celebrates the new business model that does not require rip and replace.
One of the things about writing the script for the future is that you are guaranteed to be wrong. These are my thoughts; but more importantly, what do you think? Lend your voice. At our upcoming conference, Imagine on September 10th-11th, we will give supply chain planning leaders a room and a facilitator to sort this out and come up with their vision of the third act. You will not want to miss it. It is a unique opportunity for leaders to talk to leaders to figure out their version of the script. We hope to see you there!

 

 

 

Things Have Changed: What Do We Do NOW?

by Lora Cecere on November 10, 2013 · 0 comments

This week I interviewed Robert Byrne, Founder of Terra Technology, on the results of their fourth benchmarking study on forecasting excellence.  For those that do not follow this work, let me give a preamble. The work done by Terra Technology, in my opinion, is one of two accurate sources of benchmark data on forecasting in the industry. The other is Chainalytics demand benchmarking.

There are many forecast benchmark studies in the industry, but most have a tragic flaw. The issue with most forecasting benchmarking is that the data is self-reported.  Demand planning processes lack standardization and self-reported data is suspect.

Background on the Study

Eleven multinational consumer products companies participated in the study. They are large and significant, representing a total of $230 billion in annual sales.

Complexity Escalates. Companies want to grow. Success in new product launch and trade promotions is critical to accomplish this goal. However, the increase in new products and trade promotions makes the task of forecasting tougher than it was four years ago. In the study, new products represent 17% of total cases shipped. New product shipments increased 10% over the last three years.  This was coupled by an increase in seasonality and promoted items. Traditional forecasting processes support the forecasting of turn volume, or baseline products, well, but are not well-suited for new, seasonal and promoted products. New products and promoted items had 4-5X the bias of turn volume. Products in the long tail of the supply chain have an average error of 70% MAPE and a 15% bias.

Figure 1.

  • Tougher in Europe. Both bias and error are higher in European supply chains. The average MAPE for North America was 36% while the European average MAPE was 45%. The average bias of European forecasts versus North America had 2% more bias.
  • Process Excellence Helps. Forecast Value Add (FVA) analysis has increased in popularity. The use of this continuous improvement process had a significant major impact on the bias and error of leaders.  The average MAPE for top performers in the study is 46% and the use of FVA and other techniques reduced bias from 7% to 2%.
  • Technologies Need to Change. In addition, the use of statistics to replace rules-based consumption (often termed “demand sensing”) reduced demand error of the forecast at the warehouse level by 33% as shown in figure 1.

My Take:

If growth is important to your business, you cannot manage demand planning processes like you did ten years ago.  My recommendation is to:

  • Use FVA: Aggressively implement Forecast Value Add (FVA) processes.
  • Focus Outside-in. Get serious about demand modeling. Many of the forecasting systems in the market just do not have the depth to do the type of modeling that is required in the face of this complexity. Reimplement traditional forecasting systems to model “what is to be sold” using attribute-based modeling. Aggressively integrate multiple demand streams (downstream data, warehouse withdrawal data, and market intelligence).
  • Flexibly Manage Attributes to Help Modeling. Manage history based on market attributes and aggressively move from ”SKU-based modeling” to an “attribute-based model” based on attribute-based views of history. Synchronize and harmonize downstream data using an attribute-based model.
  • Build Global Excellence. Carefully define the role of the region and the role of the global team in the reduction of bias and error. Actively use FVA to improve and align global modeling.
  • Implement Demand Sensing. Companies that have successfully implemented demand sensing to improve the forecast at the warehouse DC have reduced inventory on the balance sheet by 10% within two years. I do not see the same results from the multitier inventory projects.

I look forward to getting your thoughts.