Bio Pharma
Introduction
Biopharma Inc. is a global manufacturer of bulk chemicals used in the pharmaceutical
industry (Chopra, 2019). The company holds two chemicals called High Cal and Relax
Internally. These drugs are distributed to different manufacturers in different countries. In 2013
problems arose when it came to the finances at the organization. There were declines in plants
that were in Japan and Germany. Even though there was demand for the product there was a
surplus of capacity and that was costing the president Phil Landgraf more money than usual. He
then started to look where he could cut cost. After analyzing the case study, solutions will be
revealed on how that can happen and how the business can continue to thrive.
BioPharma’s Production Network
When looking at the case study it is shown that in 2013, BioPharma should have been
getting more use out of their production network. The data in the study shows that the facility in
Japan was only using 20% of their capacity. The facility cannot keep functioning like that
because it is not utilizing as much as they could. This could possibly get the facility in Japan shut
down. According to the data, the plant in Japan shouldn’t even be operating anymore because of
that disruption. The Germany facility should have only produced certain things and remained
idle when it came to that process of production. The annual cost for this would be Facility-
189.80, Production- 1059.55, Tariffs- 17.829, Total cost 1267.18. Evaluating this would allow
for BioPharma to meet their ultimate production demands while being financial smart in order to
meet uncertainty within the global market they are operating in (Chakraborty & Ikeda, 2020).
Landgraf Structure
When reviewing the case study, the exchange rates from the Japanese Yen as well as
other currencies have decreased in the last couple of years. The Euro as well as the US dollar has
depreciated in comparison to the Yen while it appreciated in comparison to the Pesos and the
Rupee. Although there was some fluctuation the Brazilian currency stayed flat. The Mexican and
Brazilian currency has risen over the years. So, if there is more output in the plants in Mexico
and Brazil it will bring in more money and it will put the global production network in order. In
comparison to Japanese chemicals, having a complete output in the factories will cause the prices
to decrease. Looking at just the currency issue, it would only be logical to produce in countries
that have a weak currency and focus on producing in regions with strong currencies.
Adding Capacity
There isn’t a plant that would be worth doing that. Adding additional capacity does
absolutely nothing now. All the plants are not operating at capacity because they are not
maximizing the capacity that they have in their facilities. In this circumstance, capacity shouldn’t
be added on. The facilities should use the capacity that they already have first before thinking
about adding more. Evaluating the capacity of each facility along with the operation costs and
the allows for the organization’s leadership to determine which facilities can take on extra
capacity (Reich et al., 2020).
Recommendations
Apart from Japan and Mexico all the capacity in Latin America and Asia should be
maximized to decrease taxes. Japan and Mexico have high import duties and that raises the costs
of things. Output should be expanded in those facilities but be sure to avoid importing product
from the US, Germany and Japan. By doing this the local demand can be met. The reduction of
duties would lead to an expected tightening of global supply chain networks (Chalavadi et al.,
2020).
Yield Differences
To keep the percentage under 100, the capacity of the plants will be decreased by the
percentages that were loss. Or the yield variations between the different plants could be treated
as losses to account for the inequalities. Then the yield losses can be added to the variable of the
loss.
Factors
The global supply chain network is exposed to many risks and uncertainties that can be
different based on each organization (Piprani et al., 2022). The decisions made for the supply
chain should only be made after assessing the likelihood of the events that could happen as well
as the effectiveness of the plants that could be created. Examining these certain variables will
make the model more dependable. These include disruptions, delays, forecasts, inventory,
systems and capacity
Conclusion
It is shown in the case study that some countries have the resources that they need they
just aren’t using them the way they need to. Maximizing capacity can be a huge help to some
countries because if they have it then why not use it? Closing certain plants does not have to be
an option but cutting down what is produced in the plant is an option. It is shown that by only
selling one chemical out of a plant can save fixed cost by 80 percent. These facilities can
continue to thrive they just need to allocate their resources accurately.
References
Cai, J., Hu, X., Chen, K., Tadikamalla, P. R., & Shang, J. (2019). Supply chain coordination
under production yield loss and downside risk aversion. Computers & Industrial
Engineering, 127, 353–365. https://doi.org/10.1016/j.cie.2018.10.026
Chalavadi, V., Das, S. P., Sridharan, R., Kumar, P. R., & Narahari, N. S. (2020). Development of
a reliable and flexible supply chain network design model: a genetic algorithm based
approach. International Journal of Production Research, 59(20), 6185–6209.
https://doi.org/10.1080/00207543.2020.1808256
Chakraborty, A., & Ikeda, Y. (2020). Testing "efficient supply chain propositions" using
topological characterization of the global supply chain network. PloS one, 15(10),
e0239669. https://doi.org/10.1371/journal.pone.0239669
Chopra, S. (2019). Supply Chain Management: Strategy, Planning, and Operation (Vol. 7).
Pearson.
Piprani, A. Z., Jaafar, N. I., Ali, S. M., Mubarik, M. S., & Shahbaz, M. (2022). Multi-
dimensional supply chain flexibility and supply chain resilience: the role of supply chain
risks exposure. Operations Management Research, 15(1-2), 307-325.
https://doi.org/10.1007/s12063-021-00232-w
Reich, J., Kinra, A., Kotzab, H., & Brusset, X. (2020). Strategic global supply chain network
design – how decision analysis combining MILP and AHP on a Pareto front can improve