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Data as a backbone for operational excellence

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Data as a backbone for operational excellence

From using data to measure your success To data as a catalyst for operational excellence

Who Has Got Time for Operational Excellence?

Running an enterprise in life sciences has increasingly become a rat race over the years. Quick changes in demand and regulations require speedy research, quicker development, and seamless operations. At the same time, quality must be maintained throughout the value chain, while innovative competitors are eagerly waiting to jump into niches and conquer market shares.

Fortunately, digitization and experience enables us to keep up with the pace. We know more than ever and keep getting better at interpreting data and measuring effectiveness. However, keeping up is not enough. Operational excellence requires enterprises that are on top of things, thinking ahead and preparing for the future.

Operational excellence: hard to achieve without proper data

Enterprises in life sciences operate in a complex environment. Most organizations have multiple manufacturing facilities, across the globe, that deliver their products to a great variety of customers in multiple countries. This might seem complex. But it’s only the tip of the iceberg. Add compliance, handling raw materials, changing regulations , suppliers, currency changes and financial transactions and you might get a glimpse of all the factors that influence your operations.

So, we want to achieve operational excellence. Where do we start? I feel that we must be realistic: the computing power of a human brain is incapable of overseeing all these processes. Most strategies are based on what worked in the past (which is no guarantee for the future) and gut feelings. These strategies may result in improvements on a smaller scale, but it will not result in excellence. As a matter of fact, operational excellence should be achieved across the extended value chain or value chain network.

Should we give up on operational excellence then?

Certainly not. I merely suggest that you get some help. Smart use of data can help us to achieve operational excellence in 2 ways: (1) Mapping actual processes and (2) enable fact-based predictions.

1: Mapping the actual operations and processes

Analysts might think they have a clear idea of the processes in an enterprise. Their descriptions might be logical and by the book. But is that really how it works? We find that a process analysis based on data usually yields unexpected results and reveals interconnected processes that might be the key to a higher level of excellence.

2: Making fact-based predictions

Using the huge processing power of current computer networks, we can combine and analyze data from around the world. A combination of real time data, analyses of historical data and artificial intelligence will enable enterprises to, proactively, make adjustments in their operations to fit the needs in the future.

With the help of data and Intelligent Automation, decision making will become easier and require less effort. Enterprises have to guess less and can, in a way, get ready for the near future.

Conditions for data oriented operational excellence

As things are now, life science enterprises only use a fraction of their data’s potential. Data-based excellence and foresights may not always be possible now, but we believe they will be standard practice in the next 5 to 10 years. At least, if the focus is there.

There are 4 main conditions that must be met to achieve operational excellence:

1: Data needs to be available in real time

Speed is of the essence. Therefore, accurate data should be readily available at any given time, while data integrity is guaranteed. This will require constant processing, analytics, and quality checks.

2: A pragmatic approach to data selection

To achieve operational excellence, it is vital to focus only on the data that is needed to service clients. Trying to use all data will likely result in reduced data integrity, due to a lack of focus and oversight. We do want to be careful not to cut too much into the data. Information that is not important in one process, might become relevant again in a consecutive part of the value chain. That is why it is important to analyze the process for a molecule to become a drug product and focus only on the data needed to improve this process.

3: Having a flexible (value chain) data backbone

However great the selection, the amount of available data will still be overwhelming. Data will have to be structured and available in a way that limits the amount of processing power needed. It is vital to determine which data is required where.

4: Getting sufficient computing power

The more data we would like to include in our analyses, the more processing power we need. This reasoning is quite simple, but the practical implications are huge. A solid foundation is needed to support all the computing power needed in the near future. There are limits to the capabilities of our servers and computers. Building more might not be enough. We will need smarter technology.

Starting small and making it bigger

Consider the value chain as a system of pipes and coupling pieces that has leaks in different places. As we close all the leaks in different departments, we achieve operational excellence on a lower level. From there, we can go further and work on techniques that will enable us to find new leaks in the whole system.

As I mentioned, there are limitations to what we can achieve now. I suggest starting small and making it bigger as technology advances and people get more accustomed to a data-based approach. Building on a solid data network now, will provide a basis for dealing with the amounts of data that will be the key to operational excellence in the future.

Louis Hendriks (CEO,Global Value Web)

Louis Hendriks (CEO, Global Value Web) shares his vision on operational excellence and the role of data.

Striving for operational excellence nowadays is a job for human analysts. But will they be able to keep up with the ever-increasing demand for speed in the complex life sciences industry? Data may help them retrieve the upper hand.

Global Value Web is a network of data experts and technology partners that allow organizations to make the most out of their data. We offer valuable insights across the value chain that will lead to more efficient production processes and reliable quality products. We focus on a better execution today, while keeping in mind the challenges for tomorrow. With our shared knowledge and expertise, we prepare your data flow for a bright and profitable future.

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