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Developing an Analytics Team
Background
JHP corporation is a manufact
urer of industrial products such as centrifugal pumps, compressors, waste water treatment system, and so forth. Being successful in business, the company recently became from midsized company to a large firm. The company hired more sales staff along with employees for other departments, and therefore its production scale also became larger. JHP built more factories and added a new product line that it could not handle before due to the complexity of technology and difficulties in adopting required manufacturing system: gas turbine engines.
JHP is aware of the benefits
of analytics. The company outsourced several analytics companies to conduct a few of operations research to optimize the amount of raw material use and to increase production. JHP did not incorporate an analytics department in its business and maintained outsourcing strategy up until now.
The Problem
The leadership of JHP realize
d a major change must be made in its manufacturing system. The new product line for the gas turbine engines requires new parts and materials, that the old manufacturing systems did not adopt, to be procured and used. Therefore, the company decided to upgrade its systems. Before fully establishing the new systems to all of its production facilities, JHP wants to test them. However, due to significantly increased size and number of factories, the company found it is costly to dispatch maintenance engineers to all of the factories to check the systems. On top of the testing being problematic, the company anticipates that managing all of the facilities after the upgrade would be costly as well. To effectively address all of the problems above, JHP decided to test the upgrade of the systems by implementing the technology called Internet of Things. IoT devices gather data through their sensors and enable the company to monitor its manufacturing systems both remotely and in real time basis. This way, the company can efficiently address the testing and management of the new systems afterwards, and the engineers can be sent only when a problem is detected. Now the challenge is how to implement the new technology and test the new systems.
The Gaps
The use of IoT to test the ne
w systems requires the company to deeply engage in analytics. However, the company does not have much of direct experience in it. And this is the company's first time implementing IoT in its business. There are many things the company must prepare. First, the company RFID (radio frequency identification) and IoT specialists to be knowledgeable for the new environment. Second, JHP needs to customize its old systems' software aligned with the new ones. Third, considering the large magnitude and numerous product lines of the business, the data size will significantly increase. Therefore, the server capacity of database must be increased accordingly (after upgrading the whole systems, the data scale is expected to be big data and implementation of big data technology such as Hadoop will be required). Last but not least, all of the data would be useless if data science and analytics are not implemented to analyze the data, monitor the test procedure, and come up with actionable plans or ways to improve the systems. Yet, on top of the lack of the experience, knowledge and technologies, the most critical resource the company lacks is "the right" people. The company has outsourced analytics service and does not have the best people for the job.
On the other hand, JHP is res
ourceful in relatively more "traditional" disciplines: system engineering, project management, and operations. JHP's engineers, project managers, and operation managers in these disciplines have rich experience and expertise.
The Team
The task force is responsible
for two tasks: implementing IoT on the test of the new manufacturing systems and finding out whether continuous use of the new technology for the systems justifies the cost of the implementation. The best structure of the team in this case is Agile for the following reasons:
1. Testing a new system may i
nvolve with many unexpected situations such as system failure, malfunctions, and an operator's mistakes. The testers must be able to quickly adapt and react to these unexpected events. The testers also need to be able to realize what actions are needed for improving the system and to quickly apply changes.
2. The team members need to g
ive feedbacks and critiques, and share ideas to figure out the best way to implement IoT and settle the systems. Hence, interactions among team members are critical.
3. Every testing costs signif
icant amount of time, capital and financial and human resources. Therefore, the work environment must allow each member to focus on his work.
4. The process of manufacturi
ng systems can be broken down into several stages: raw material preparation, fabrication as per design, stage testing, assembling, final testing, and packing. The testing job can also be easily broken down into several sprints accordingly.
5. The company does not have
experience in IoT and analytics. Therefore, no guidance is given. Each member must be fully capable of doing his job, eager to succeed, autonomous, initiative and self-managing.
6. The benefits of Kanban, re
ducing lead times and the work in process, are highly desirable in manufacturing operations.
7. Testing environment is vol   (ÀÌÇÏ »ý·«)

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