Data: From Operational to Strategic Tendering

It’s all about data: everywhere, in all processes. Life sciences tendering is no exception. Data is required to achieve optimal tendering processes, along with continuous learning and improvement. Starting with the awareness phase, to participate in tenders you must know what tenders are published. Moving forward, you must know who the tender authority is in order to enable tender shaping activities. Of course, relevant dates need to be tracked. Those operational aspects should not be overlooked and are key to win tenders. Once these data sets are available, the tendering strategy can be brought to the next level. Data is the enabler of strategic tendering.

Assuming you defined a harmonized governance, you probably have objectives in terms of minimum tender prices and profitability levels, but you still may not be able to achieve your objective. Affiliates constantly raise exception cases to participate in tenders and urgency is business as usual. What could be missing?

Transforming data into your strategic tool

One of the beauties of tendering in the life sciences space is the cyclicality. Compared to other public entities procurement, most of the life sciences tenders repeat after the end of the first tender. This is only reality because of the type of demand the industry is facing. With vaccines, demand stays fairly steady. The same is true for a number of surgical operations. Stable and easily forecasted demand (and fluctuations) enable companies to build strong sales prediction models and processes.

Bringing this cyclicality to the strategy is essential. Supply chain integration is one of the central aspects of tendering, whether you are trying to increase the profitability or simply to respond to tender to keep your manufacturing utilization high, integrating the supply chain department is a must. However both the cyclicality and the supply chain integration rely on data management. Dates are of course key, when is the first delivery due, how many shipments will there be over which total duration? What is the expected Tender Authority demand? Those sound simple points but aggregating them brings you to the next level.

Optimal demand planning process can rely on this strong characteristic based on the aggregation of good quality granular data. Supply chain and manufacturing capabilities can be based on those and therefore bringing the company in a better position to respond to tenders. Profitability decisions can be made with much more leverage due to economies of scale and accuracy efficiencies. Knowing for instance if the tender has been accounted for during the budget process would lead to different choices on participation. Marginal costs are different then fixed costs and thus a tender incremental to budget may be more profitable as only marginal costs would be involved.


Data would also allow companies to perform market archetyping. It will be much easier to define which country or cluster is following a certain trend. An archetype can be defined quickly if for example the number of tenders, the type of procedures, the tender authority type, the duration and the therapeutic class are available. You could imagine to go even one step further, collecting data on the members served by the tender authority as well as the switching patterns of patients in scope for the tender. Once the archetypes are available, the next step is to define the proper strategy and respective operating model. For sure the business model is different in Canada Hemophilia market compared to Poland. On the one side of the spectrum two customers publishing 1 tender a year versus a market with more than 200 tender authorities publishing up to 2000 tenders. This strategic view is only possible if the companies have such data available. Besides those easy points, the awarding criteria need to be rolled bottom up. Each lot is specific and data is the way to bring those criteria with the associated winning rate and therefore knowing in which market to play.

Business intelligence is the key

Improving the supply chain structure and your operating models are two key strategical questions but data will also support the evolution of those operating structures. The only way to exhibit a solid reliable trend is to perform analysis. Inference can be made only if the history has been properly analyzed. It is valuable to use business gut feelings but it’s better to establish resource allocation decisions based on solid facts. Exhibiting trend, such as the increased importance of quality criteria in Europe, can impact the 5 years plan both from a tender shaping perspective but also from a manufacturing and marketing perspective. Having the possibility to update the products to fit the needs of the authority is not always possible and therefore this is where tender shaping comes into play.

Finally, business intelligence is enabled with data. If countries’ perform religiously the tendering governance and track the different data points available, the regional and global teams will be more easily able to define the competitors’ behavior and even trend it. It’s of course valuable to know which competitor is seeking for lowest price only tenders. It is at least as much important to know who the players are seeking for quality criteria. Collecting the data requires the in-country team to see the value of it. Therefore, processes should be in place for the global team to provide insights back based on the global analysis. This is the only way to sustain a successful process.

Ultimately, the end goal is to move from an ad hoc tendering process into a pro-active and real fact-based decision making at each level. From pricing to supply and response package, all the aspects of the bid should be viewed as critical and backed up by data. This is the real purpose of a tendering strategy and so should it be for your tendering data.