Author: Nick Perez-Lozana Alonso

From Chaos to Customer Focus

From Chaos to Customer Focus

A Brand Pharmaceutical company asked Zinata to help their operations become more flexible and responsive to change.


Situation

An entire product line with a large number of products was transferred to a manufacturing plant. The plant became overwhelmed with the increase in volume. A severe backorder crisis resulted and the plant lost control of the situation.

The plant was disconnected from the Sales groups. Market changes were not communicated in a timely manner. The company was struggling to respond to unexpected events. The lag time between the receipt of customer demand and the processing to supply orders received by the plants was causing an imbalance between demand and supply. Cycle times became longer. Results were poor customer service, excess inventory, high costs, and inefficient use of capacity.

The overall cycle time was almost a year. There are two things that contribute to very long supply chains and very long production cycles. One is the approach to sequencing of operations. The other is the handling of unexpected events. Throughout the supply chain, things go wrong or surprises occur that cause the chain to stop or require that the chain deviates from its planned course. Supply cycles become long if it takes long to solve those surprises.

Prescription

It was determined that the supply chain as a whole and the internal Plant operations in particular were not flexible and scalable enough to cope with drastic changes in demand and supply. Their entire value chain was fragmented with gaping lags between process steps. Their supply chain and operations management practices were primitive and robust systems were not utilized to manage the environment. Essentially, the entire operation needed to be transformed, starting with understanding the Voice of the Customer.

Implementation

A desired end state was defined where Sales and the plants work together to support market demand. Demand management was simplified, cycle times were compressed, visibility of information improved, exception management was introduced and processes were supported by social collaborative models.

Demand management processes were redefined such that the supply chain connected directly to the end customer eliminating purchase orders between Sales and the plants. Demand patterns were analyzed and corresponding supply flows were aligned to these patterns. Their systems (ERP and Planning) were restructured to support the new processes.

Through data analysis the right balance between make to stock and make to order products was defined. The manufacturing operation was restructured to operate in continuous flow, creating virtual value streams matching products of similar scale and demand patterns. Changeover times were minimized through proper sequencing. The planning of purchased materials was integrated into the overall planning of the supply chain.

Collaboration, using social media was introduced as a way of quickly responding to unexpected events. When someone encountered a surprise, they post it in social media. Shortly thereafter people from a community of competencies will see the issue and start reacting. No meeting is required. The dynamics of social media are such that those who need to be involved will be drawn to the issue and participate in the discussions. In NOW Mode, the right people gravitate to the problem quite rapidly and the problem gets resolved relatively quickly. The impact is greater when multiple organizations are involved.

Outcome

Service levels recovered to target levels in 6 months. Production cycle time was reduced by 70 percent. Social networking created a more cohesive and co-operative organization. Changes to demand and supply are now considered ‘normal’ and the organization is well equipped to work in the NOW Mode.

Learning to See

A large consumer products company needed to reduce inventory. A simple Zinata tool made inventory visible, and thus reducible.


Situation

A large consumer products company’s global inventories had remained relatively constant for a number of years. There were significantly different inventory levels by business and supply chain. Also, there was significant sku turnover as new skus came into the market and old skus were discontinued. But new skus enjoyed varying levels of success, which added non-performing inventory in all markets.

Efforts to reduce inventory were not sustained, as service levels led to “just in case” rather than “just in time” inventory decisions.

A new approach was needed.

Prescription

Knowing that systemic and sustained improvement had to start with a clear declaration by leadership, corporate and business unit goals were set and leaders assigned. Business silos destruction was accompanied by a search for the best tools and processes. One that emerged in this search was a graphical inventory analysis tool that had started in a regional business known to have the best inventory globally, as measured by overall day’s inventory. What made it so successful? It was simple. It made inventory visible. It could be understood from the board room to the shop floor. It was time to bring it to all businesses in all regions.

Implementation

The Learning to See Inventory (LETSI) tool is a graphical display of available inventory by sku (or group of skus) by day, typically for a year. Overlaid on this display is safety inventory. LETSI was used by planners and inventory analysts to see where there was dead stock / non-performing inventory that had not been used. Planners then made safety and / or planning adjustments to reduce or eliminate this inventory without exposing the business to any service risk. In many instances, up to 10% of overall inventory was found to be dead stock. Interventions using LETSI resulted in virtually all dead stock being eliminated – and these reductions maintained over time. People were finally able to connect the dots between parameter settings, inventory levels and service.

LETSI’s ease-of-use enabled its rapid acceptance and application. While originally created in Excel and made available quarterly, with corporate support LETSI was integrated into SAP Business Warehouse data toolsets and given on-demand to planners and inventory analysts globally. LESTI capability is now embedded in the organization.

Outcome

Corporate finished goods inventories were reduced by 10% due to LETSI. Customer service levels either remained the same or improved – a win-win. Focus was then extended to raw and packing material inventories, with similar reductions in cost and no harm to service. LETSI’s simplicity and effectiveness saw its ready acceptance and use across all businesses and regions permanently. It has proven a perfect complement to value stream mapping and accelerates the finding and correcting of inventory root causes.

Wheel of Fortune

A large nutraceutical company needing to improve asset utilization asks Zinata to “connect the dots” between scheduling and production.

Situation

The client, a large nutraceutical company, was facing intense competitive cost pressures and relatively unproductive assets. Overall Equipment Effectiveness (OEE) at a key packaging plant averaged less than 40%, far below world class standards. It was imperative to significantly increase OEE and line throughput, so they could satisfy all customer orders with fewer lines operating.

Prescription

Zinata was engaged to improve OEE and packaging line throughput. Our analysis showed one of the highest OEE losses was time lost in product changeovers. Digging deeper we learned there were up to fourteen parameters (bottle diameter, bottle height, cap type, tablet type, allergen content, etc.) that could be affected by any given changeover. The degree of change required was not being adequately considered in the scheduling process – there was a disconnect. As a result, too many changes were required and most changes required more thorough cleaning and mechanical adjustments to more parameters than a more logical schedule would need. An improved scheduling methodology and process was needed.

Implementation

Zinata’s solution called for “Product Wheel” scheduling as a way to “connect the dots” between scheduling and manufacturing. Product wheels are a very effective way to level production and match products to lines by product family groupings. The optimum frequency and campaign length for each product is developed, then sequenced to minimize the number of changes and then reduce the parameters which must adjusted on any changeover. A great example is sorting products by bottle sizes and allocating a narrow group of sizes to each line. This alone reduced bottle rail changes (the most time consuming change) by a whopping 62%. Other optimizations significantly reduced the number of those irritating runs of low demand products (while increasing the size of each such run). In the end, total changeovers dropped by over a third and those that remained were less complex and took less time.

For wheels to be successful they have to be used every day religiously to schedule. Zinata developed product wheel tools, excel based for familiarity and simplicity, to make use of the wheels in day to day scheduling simple and direct. Training and 1-1 support (scheduling together) was provided to embed the knowledge of wheels and tools and create the habit of their use – building client capability.

Cross functional team work was critical for success – so Zinata helped bridge the internal silos. The wheels were designed by planners, schedulers, mechanics, and supervisors, led by a Zinata Product Wheel expert. Along the way Zinata was able to highlight and help improve critical management parameters like run rates and characteristic relationships. Working with the schedulers, the Zinata team designed and evolved the product wheel tools using rapid development techniques. Most recently adding the ability to pull future orders from the ERP system and present them to the planner in a format aligned with the wheel design.

Outcome

Product Wheels resulted in an OEE increase of 12 points, which delivered a 34% increase in throughput and resulted in the ability to meet demand using two fewer lines. The crew reduction labor savings is worth $1.5 million annually. The new approach gives the client a systems view of their product line-up rather that their traditional piecemeal, one-at-a-time view. This is leading to further operating improvements. The benefits extend throughout the product value chain. The standardized, repetitive wheel patterns enable them to predict future tablet, bottle type, and cap type needs on a week-by-week or month-by-month basis several months into the future. This makes for better supply chain planning and labor crew planning.