ACSEA, the forty year old 2bn USD South East Asian subsidiary of a Japanese pharmaceutical group suffered a blow to its pride in 2003. A competitor which started operations just ten years back now surpassed it in the volume of Pharmaceutical-A produced, and its cost was now 13% lower than ACSEA's. The only hopes of responding effectively lay in the company's South East Asian Technical Centre whose role is to provide technical support to the factories and develop process technologies aimed at cost reduction for the organisation.
However morale at the centre was low, and its contributions to cost reductions for Pharmaceutical-A amounted to a measly 1% per annum. Hiroyuki Fukushima, a general manager with ACSEA, was sent to head the centre in July 2003. He immediately set about improving things to make the SEATC more effective. His boss believed he was doing very well and he tended to agree with this assessment...
Until he read the 2000 Percent Solution by Don Mitchell, Carol Coles and Robert Metz. In his words, he was shocked at the extent to which stalled thinking had limited his achievements and those of the SEATC. He quickly took up the challenge to remake the SEATC using the ideas from "the 2000 Percent Solution".
Realise the Importance of Measurements
Excited by the possibilities Fukushima realised that if SEATC could innovate 20 times more than they were doing already, they could make ACSEA the top company in the group. He set that as their new vision and introduced measurement systems to manage performance.
Decide What to Measure
Before this time, the technical centre tracked the number of reports produced as a way of assessing its contributions. Fukushima realised that this and similar measurements had nothing to do with the purpose of the SEATC. He started measuring the cost drivers of the product Pharmaceutical-A.This led him to target energy, intermediate chemicals, chemicals and depreciation (construction costs) as major cost drivers requiring improvements if the new vision was to be realised.
Identify Future Best Practice
In trying to identify likely future best practices for the major cost drivers, Fukushima reached the conclusion that for energy, co-generation was the way to go. For intermediate chemicals, they were to be eliminated. This would require development of new enzymatic reactions. Similar future best practices were identified for depreciation (construction cost) and chemical consumption. Implement Beyond Future Best Practice Cost per ton of Pharmaceutical-A were expected to reduce from $350 to $265 if the future best practices were implemented - a very different picture from the 1% per year improvements being achieved already. Meanwhile, current best practice in the industry was $310 per ton. Fukushima and his team designed projects with a maximum implementation timeline of three years to achieve these.
Identify Ideal Best Practice
For ideal best practice, Fukushima assumed the best solutions that were scientifically possible. This meant for energy cost for example, they would make use of a renewable source like solar. For intermediate chemicals, ideal best practice would mean increasing the yield of enzymatic reactions from 60% to 100%.
Pursue Ideal Best Practice
Considering the capabilities of SEATC, Fukushima decided to give priority to the development of a new enzymatic reaction. He also decided to have his process engineers develop a simplified process to reduce cost of new plant. Both of these projects are estimated to last five years.
Implementation of these practices will yield a cost per ton of $158.
Provide People and Resources
Realising that he needed his very best people to implement the planned changes and improvements, Fukushima decided to select - to use his words - self actualised team members to spearhead the projects.
Repeat
Fukushima began this journey about eighteen months ago and is well on the way to achieving the future best practice targets. He realises that the very successes they achieve will give birth to new stalls and is already on the look out for the next 2000 Percent Solution opportunity.
