Why You Don’t Need Perfect Data to Begin Implementing Sales & Operations Planning

Royal Boon Edam a global market leader in entry solutions, was looking to shift towards a combined business model of “made to stock” and “assembly to order” – where modules which could be placed into a configuration requested by the customer would be ready for production, this meant the company needed a different logistics approach to fulfilling these orders.

An interview with Boon Edam’s Aron Waas

Implementing Sales and Operations Planning (S&OP) has many benefits.

To truly leverage it to improve business performance and predictability, you need to embark on a change management process and you need the right technology to self-enable your team.

Often, teams think they also need plenty of clean and accurate data to do it right.

But starting small can pay off. We spoke with Aron Waas, Global Supply Chain Director at Royal Boon Edam International to hear about his company’s experience.

Hello Aron, can you tell me more about Boon Edam and your role as Global Supply Chain Director?

Boon Edam is a private, family-owned company that is over 140 years old. We are a manufacturer of premium entry systems, such as revolving doors and security access gates.

We have 3 factories, one in the USA, one in China and one in the Netherlands (in the city of Edam). We have over 20 sales subsidiaries and, at this stage, 3 different Distribution & Support Centers.

These centers (or D&SCs) support our sales subsidiaries with all their inquiries, service requests and the delivery of products and services.

I am part of the global management team, responsible for everything that has to do with supply chain management. The directors of our D&SCs report directly to me.

You are currently using AIMMS to enable your S&OP process. What was the driver to look for S&OP technology and how did you do things before?

We have worldwide demand for all kinds of products and services and as I mentioned before, we have 3 different factories. We were trying to optimize the workload between these factories to have our manufacturing be as efficient as possible.

We had a financial reporting tool and based on the financial forecasting of our different sales subsidiaries, we made a forecast for products and services which was translated into a monthly demand plan and a capacity plan. This process was based on a lot of assumptions.

Read more at Why You Don’t Need Perfect Data to Begin Implementing Sales & Operations Planning

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6 Ways Quality Can Strengthen Supply Chain Profitability

To thrive in today’s competitive global business environment, manufacturers must have a top-to-bottom quality-oriented approach that infuses innovative thinking into every part of the supply chain in order to deliver world-class performance through products, processes and people.

Some promising news, according to a recently published report by Forbes Insights and ASQ, is that senior executives and quality professionals see a direct connection between the success of their continuous improvement initiatives and the success of their organizations as a whole.

The Forbes Insights/ASQ research surveyed 1,869 executives and quality professionals from around the world and focused on the links between quality efforts and corporate performance, as well as the evolving business value of quality and its relationship to the supply chain. Thirty-six percent of enterprises surveyed said that they regard themselves as an established quality organization, while 39% reported that they are still developing their quality programs and 25% said they are struggling to implement quality in their companies.

For those organizations that do have established quality programs, more than half say their initiatives already encompass a range of key corporate functions, including operations and supply chain management.

This focus on quality for the supply chain is especially crucial when one recognizes that supply chain management is often motivated to achieve the least cost when identifying and qualifying new suppliers. Supply chain leaders are often rewarded for these cost-savings. But then extra costs are incurred once the final product is manufactured and delivered and it is discovered that reworks are required due to the focus on price and not quality.

Read more at 6 Ways Quality Can Strengthen Supply Chain Profitability

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Supply Chain & Big Data ÷ Analytics = Innovation

Google the term “advanced analytics” and you get back nearly 23 million results in less than a second.

Clearly, the use of advanced analytics is one of the hottest topics in the business press these days and is certainly top of mind among supply chain managers.

Yet, not everyone is in agreement as to just what the term means or how to deploy advanced analytics to maximum advantage.

At HP, the Strategic Planning and Modeling team has been utilizing advanced operational analytics for some 30 years to solve business problems requiring innovative approaches.

Over that time, the team has developed significant supply chain innovations such as postponement and award winning approaches to product design and product portfolio management.

Based on conversations we have with colleagues, business partners and customers at HP, three questions come up regularly – all of which this article will seek to address.

  1. What is the difference between advanced and commodity analytics?
  2. How do I drive innovation with advanced analytics?
  3. How do I set up an advanced analytics team and get started using it in my supply chain?

Advanced analytics vs. commodity analytics

So, what exactly is the difference between advanced analytics and commodity analytics? According to Bill Franks, author of “Taming The Big Data Tidal Wave,” the aim of commodity analytics is “to improve over where you’d end up without any model at all, a commodity modeling process stops when something good enough is found.”

Another definition of commodity analytics is “that which can be done with commonly available tools without any specialized knowledge of data analytics.”

The vast majority of what is being done in Excel spreadsheets throughout the analytics realm is commodity analytics.

Read more at Supply Chain & Big Data ÷ Analytics = Innovation

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