On top of the adverse healthcare implications brought about by COVID-19, the economic downturn and disruption to global supply chains have impacted businesses across all industries. Zuellig Pharma – one of Asia’s largest and oldest healthcare services groups that distributes and provides drugs, medical supplies, and services across 13 countries – is no exception.
Zuellig Pharma has been on the front line in the battle against the COVID-19 pandemic, and has had to navigate novel challenges during this time; they have had to contend with shifts in their inventory portfolio, and maintain visibility over the needs of its staff, suppliers and clients.
Zuellig Pharma has heavily invested into a “digital, data-first culture” over the past few years, and it has paid dividends – with accelerated skills training for their traditional workforce, employees are empowered with access and skills to direct data insights. Everyday business users are equipped with the core business intelligence skills to empower self-service analytics while the analytics team function as the enablers, focusing on more specialised work. With these, they have been able to make data-driven decisions rapidly in response to the pandemic, whilst also keeping the organisation relevant in the new digital era.
We talk to Tristan Tan, VP Data & Analytics, Zuellig Pharma on the data culture in place in the company and how its cultivation has paid off during the pandemic period, as well as its collaboration with Tableau in making this happen.
What does the term “data-driven” mean in a concrete sense for Zuellig Pharma? How about “data culture”?
As one of the leading healthcare providers in Asia, we ensure that essential medicines and healthcare supplies are accessible to 13 markets and over 350,000 medical facilities in Asia. With such extensive operations, it is important for us to have access to accurate, real-time data to better monitor our business, make agile decisions, as well as spur innovations.
When we talk about being data-driven, we are focused on ensuring that our tactical and strategic decisions are all backed by data. Instead of relying on gut instinct or heuristics in the decision-making process, we must make decisions with a requisite level of information. We now have a critical mass of people who understand that data must inform decisions and who are very clear on the benefits of doing so.
Also crucial is the idea that “data-driven” is not simply an intangible characteristic or corporate value we hope our people exhibit. Rather a big part of our belief is in the importance of embedding data practices and assets into business process. Ensuring that a piece of information, a data report, a dashboard or analysis, is a regular part of normal business process has been key.
For example, in many of our warehouses, daily and weekly stand-ups are mandated for operators to jointly review operational KPIs and dashboard driven statistics on how different warehouse processes are either negatively or positively impacting these KPIs.
This then informs how the operational teams focus their efforts.
What are some of the data points Zuellig Pharma needs to leverage to become more efficient in its operations? Where are the sources of these data?
Our logistics and supply chain operations are naturally one of our biggest priorities, and we have a big role to play in ensuring medicines reach clinics, hospitals, pharmacies and patients in the most timely and efficient manner.
There is a myriad of factors and variables that will impact this outcome – all information pertaining to where a product is at any given time (e.g. where and for how long it has been stored) and what has ‘happened’ to it so far (e.g. how it has moved through the supply chain or any packaging changes that have occurred) can be critical in helping us identify inefficiencies or issues that can then be tackled.
Knowing what is happening to our products and how they are flowing through the chain at any given time will not only help us monitor in real time our operational KPIs but it will also allow us to drive optimization models that could help to drive further process efficiencies.
Taking a broader perspective, however, Zuellig Pharma is only responsible for a part of the global supply chain and our efforts at optimizing operations only relate to our end of the chain. We currently are not able to see what is happening both upstream and downstream with our shipping or manufacturing partners, and there remains gaps to true visibility. Without collaboration with our supply chain partners, there will always be pockets of inefficiency that remain unresolved and that continue to impact our patients.
Our recent investments in blockchain have been designed to address this gap.
With a well-designed blockchain network, we have found that we are now able to allow different parties on a supply chain to better collaborate and share critical information on product storage and movement.
This is allowing us to finally form a holistic end-to-end picture and will allow us to finally address more macro-level supply chain inefficiencies with our partners. This topic has become especially critical today, where manufacturers are racing not only to develop a COVID-19 vaccine, but also to develop solutions on how to get it to the mass market.
Why did you choose Tableau over its competitors? Was there a proof of concept/pilot done to evaluate the software, and how it applies to your business case?
There were a few important criteria we had when selecting our data visualisation partner.
The first was around interoperability – we wanted a visualization tool that would allow us to work of a variety of data source technologies, types and formats in a way that would not sacrifice performance and that would future proof us as our internal technology landscape evolved over time.
The second was to ensure that visualization could be well integrated with data science activities. Choosing a partner who had thought through not just descriptive analytics features in their solutions but also the predictive and prescriptive, was important. Better still, tools such as Tableau allow easy integration of code into dashboards and other descriptive analytics which then give more options to our teams in terms of how to deliver outputs to their audiences.
Third, the tool had to facilitate self-service and should not require specific expertise knowledge when being used as it would need to empower the average business user. Our focus was to ensure democratization of basic insight and analytics generation – everyone should be able to use it and benefit from it. Lastly, it was important to us that the visualization provider was investing heavily in product development and R&D. Technology today moves so rapidly, we needed to ensure our decision was future proofed and we would not find ourselves in a position that our choice in software had become anachronistic after we had rolled it out in the organization.
Tableau was uniquely positioned to meet each of these requirements and we continue to be impressed with their commitment to product design and feature releases. I can confidently say that Tableau as a product improves noticeably every year in a way that deeply considers customer needs and latest developments. The recent addition of Tableau prep for agile data management and exploration was a particularly well received one for us.
There were also other intangible aspects to Tableau’s corporate culture and offering that we have greatly benefited from. Rolling out a visualization software in a company involves a lot of stakeholder engagement, change management and successful proofs-of-concept. Building value-adding use cases is key. Tableau was able to match our agile development process and have remained flexible and liberal in their openness to supporting proofs-of-concept together with us, truly partnering with us in their focus on value creation – not just selling a software.
More importantly, we are moved by Tableau’s commitment to customer success. Since the early days of our data journey, the Tableau team we have worked with has been proactive in the provision of training, coaching and co-creation activities – not just in the usage of the software, but most impactfully, in helping us unpick some key business questions. They understand our challenges and needs internally and are very helpful in working with us to navigate these.
What were some of the disruptions experienced during COVID-19, and how did access to data and analytics help alleviate some of the complexity?
Simply put, during COVID-19 the traditional patterns around both supply and demand were significantly impacted.
From a supply perspective, global logistics disruptions were driven by lock-downs in markets, travel restrictions and workforce constraints (socially distancing). It became much more difficult for supply chain actors to move product from one location to another and there was always the fear of out of stocks because of this.
On the other hand, patterns of demand were also deeply impacted. There were short term changes as patients and consumers rushed to stock up on essential products. There were also deeper and longer-term trends as health awareness, social distancing and lock downs changed the medication consumption patterns in many markets.
For instance, demand for chronic medication has been resilient to overall market slow-downs with higher adherence levels and greater patient sensitivity to adherence messages. Anti-infectives on the other hand have diminish as social distancing and social awareness help alleviate common infectious illnesses.
These individual nuances to the shifts in supply and demand have made it difficult for supply chain players and distributors such as ourselves ensure healthy supply and provision of medication to our patients. Being successful in data-driven predictions has allowed us to differentiate the short-term from the long-term fluctuations and has been key to determining the effectiveness of our decision making this year.
In situations like these, it is not simply about tracking what is happening in the market but predicting where the market is likely to go – so that you can strengthen the resilience of the supply chain and ensure maintenance of key operational metrics.
We are currently working hard with academic organizations and drug manufacturers to develop intelligent systems of prediction down to a granular geographic level – to anticipate demand rather than react to it. This has only been possible through the availability of data and our earlier efforts to ensure we are well positioned to move, manage and bring-to-bear our data assets.
These efforts will only make us stronger as we prepare for the arrival of the COVID-19 vaccinations and consider the challenges of cold-chain related to their distribution.
How does Zuellig Pharma plan to leverage data in the future? Are there specific plans to use even more of it, are there visible gaps in productivity it can help fill?
At Zuellig Pharma, we have a great data set that comprises a lot of useful information for our patients, but face limitations in what we can do as an individual entity. There is a huge potential for our industry to collaborate and engage in conversations on the massive role of big data in improving patient outcomes.
However, this is hampered by data fragmentation in the region. The data that is required to answer crucial questions sits across various locations and is owned by different players. As we continue to focus on strengthening data privacy and confidentiality, we must also think about how to bring different data assets together to maximise benefits for our society. We want to play an active role in these discussions and move the needle to unlock the potential of data – by sparking more conversations around data integration to support healthcare outcomes.
How does access to data directly impact business decisions? How are employees who are not data-savvy still able to make use of data they are given access to?
Different employees have differing responsibilities, but they all benefit from having access to data.
After all, data serves as a single source of truth to help them make accurate decisions efficiently, which not only reduces bottlenecks in the decision-making process but also frees up time for them to pursue new business directions in line with their career goals and interests.
What is important to keep in mind is that data access alone is not enough, organisations need to think about building a holistic framework around the use of data and make sure that data is embedded into employees’ daily work.
The more we can make the concept of data less intimidating the more successful we will be. Training of the workforce obviously plays a massive part in this but so does thinking carefully of the types of data required for specific business activities. Why provide 100 data fields when you can just provide the key 5 fields that a person needs? Why require data transformations by business users if we can just deliver the insight they are looking for, on an automated dashboard?
The goal should not be to increase our staff’s usage of data from a data handling and manipulation perspective – but to increase our staff’s usage of data from an interpretation and ‘so-what’ perspective. Building a process and framework that does this is important to ensure everyone benefits from data – even if they are not data savvy.
What is being done to enhance data literacy among Zuellig Pharma employees?
We believe in the importance of investing in our employees to make sure they are equipped with the skills of tomorrow. From a data perspective this means the foundational skills of how to interpret data and insights, using them for business decisions. And for the more savvy – foundation skills on how to turn data into insights that can drive business decision making.
To this end we have built a set of organizational assets that help drive and encourage learning in data and analytics and that help facilitate communities of data-interested individuals to form. Building data literacy is also not seen as an academically heavy, highly intellectual affair. We strive to ensure simplicity in data and analytics and relevance to every individual’s specific area of work.
In our training courses for instance, when we conduct dashboard and automation training for our employees at Zuellig Pharma, lesson plans are designed to revolve around real-life use cases.
Course attendees are required to turn up for training with a number of scenarios / deliverables from their day-to-day jobs and the focus for the rest of the training is to equip them with the specific skills to solve them through data.
We also encourage self-learning and have established a dedicated online Academy (modelled after Coursera!) to allow employees across all job functions to sign up for courses on an online portal. Here, they can then go through 10-week lesson plans on key areas of data and analytics; and receive certifications at the end of the course. It allows interested employees to take charge of their learning and do it at their own pace. The academy is now being opened not just to Zuellig Pharma staff but also to partners, clients and customers.
