Distributing drugs, medical supplies, and services across 13 countries, Zuellig Pharma is one of Asia’s biggest and oldest healthcare services.
While it might be close to a century old, the company has adapted to meet the demand of the fast-evolving healthcare and pharma sector, and now serves more than 350,000 medical facilities, hospitals, clinics, pharmacies and, as a result, millions of patients in a mission to make healthcare accessible across Asia.
Given such extensive operations, it’s imperative for the firm to have access to accurate, real-time data to better monitor the business, make agile decisions and spur innovation.
Despite its long reign, however, a panoptical view of operations is a relatively new addition to the organization.
“Our long heritage was actually a bit of a double-edged sword for us and until around 5-6 years ago, technology adoption and data capabilities were relatively low across the business […]” said Zuellig Pharma’s VP of data & analytics, Tristan Tan.
“In 2015, a new management team came on board that were convinced about the critical role digital and data would play in driving future sustained growth – and the need for transformation.”
Zuellig’s new leadership was determined to make the firm technology-led and set about building the foundations necessary to install a culture of data accessibility throughout its ranks. This phase saw the creation of data pipelines and data management structures using tools like Hadoop, Spark, HANA and Tableau.
All these efforts were tied by a commitment to data velocity, Tan explained, or maximizing the speed of access to data within the business.
But the necessary infrastructure was just one part of the process. Zuellig had to ensure its people had the foundations to embrace data culture. The firm focused on training staff on the benefits of using data and analytics, it educated clients and customers about the value of this new information and built a robust but agile data governance framework.
“As traction among staff, clients and customers grew, so too did our data culture and the number of ROI accretive use cases.”
Only after putting the foundations in place could the company explore more advanced areas: “[…] we have now started leveraging blockchain in our handling of information with our partners across the supply chain and have embarked on organization-wide automation agenda using data-science and robotics process automation to drive efficiencies in our operations,” Tan said.
“These efforts would not have been successful without the foundations we built in the earlier phases of our journey.”
Now the company has a “critical mass” of people who understand the importance of ensuring data is informing the work being done across the organization. Data culture is not an intangible concept, but is embedded practically into business processes.
“Ensuring that a piece of information, a data report, a dashboard or analysis, is a regular part of normal business process has been key to our data transformation,” Tan said.
For example, daily and weekly stand-ups are mandated for operators in the firm’s warehouses to jointly review real-time operational KPIs and statistics, which informs how operational teams focus their efforts.
While Zuellig’s data culture is comparatively fresh, the methodical approach to embedding it means the workforce, and the company’s partners and customers, have been able to embrace it confidently. Tan told us that this approach to data had been crucial during the COVID-19 pandemic as a “primary medication provider”, despite the operational challenges.
Data accessibility, tied to “very straightforward data science” has allowed the firm to better predict, plan, prepare and succeed in the “fog of war”, and react quickly to ensure medications and key supplies like vaccines are allocated to where they’re needed, even during lockdowns.
So, how can other companies begin to embed their own data culture?
Firstly, organizations must invest in the right technology that will allow for good data management and easy-to-use insight generation, such as Tableau. Then, companies must encourage individuals to look for ways in which data can create value in their teams, either by improving processes or creating additional quality to their work output.
“The main objective here is to encourage individuals across the organization – down to the most junior – to drive their own ‘data use cases’ within their roles,” said Tan.
“Successful – or even sometimes unsuccessful but well-meaning – efforts should then be rewarded and publicized to others in the company to build a ‘data-friendly’ atmosphere.”
Once these use cases become more common and more established, the more successful of them should then be embedded into existing business processes so that usage of data in decision-making becomes less dependent on individuals over time, becoming a consistent part of the organization as it grows.