Five Steps to Sustain and Optimize Effective Delivery of Statistical Programming Services in a Globally Distributed Model

Dr. Chitra Lele Ph.D.

Several best practices when outsourcing and offshoring clinical research related activities are well known, especially to companies that have been doing this for a number of years, though they may be applying these to varying degrees. Practices such as defining clear communication channels apply equally to all types of activities being globally sourced. However, there are certain practices which are more relevant and important to implement when statistical programming (primarily, efficacy analysis related programming) is to be executed by a global workforce. This is because statistical programming requires a highly technically skilled workforce which is in limited supply, and though it can be built from the vast raw talent pool available in emerging markets, the time and effort taken to train and mentor and to build the skills to the desired level is substantially higher than for most other types of work. This technical workforce also has somewhat different personal and professional development aspirations.

1) Maintaining steady state and balanced mix of onshore and offshore resources: The first consideration for Pharma companies who have offshore programming teams is maintaining a balanced mix of in-house and onsite resources versus offshore resources. This applies equally to small, mid-sized and large biopharmaceutical companies. Getting these numbers right during each phase of outsourcing and offshoring is crucial to ensure that there’s enough in-house/onsite/onshore capacity available to provide mentoring and oversight as capability is being built within the offshore team, and while its productivity is ramping up. Managing peaks and troughs both in the onshore and the offshore requirement is easier if contract resources are available at both locations. Using a good partner who can provide flex capacity offshore, as against only having a captive team offshore, and having some contract resources onshore to supplement the core in-house team will address this need.

2) Assigning the right kind of work to the offshore team: It is crucial to consider the right kind of work to be assigned to the offshore team and how it needs to change over time. Rather than allowing work to be sent through as it arrives, it is best that the work assigned to the offshore group is carefully planned so as to gradually increase the complexity of their work, to match with the gradual growth in capability, bearing in mind the high lead time required to achieve optimal productivity and quality. Ability and acceptance of the in-house and onshore teams to manage change should be continually monitored, especially with respect to change in the type of work they do, such as more of oversight and strategic responsibilities rather than hands-on and operational tasks, so that the value of letting go of certain tasks and retaining others is appreciated.

3) Optimizing productivity: Productivity is a crucial element of a streamlined, effective and efficient working system and becomes even more important when moving into new markets and working with international teams since high performance and cost efficiency are key objectives of this model. High levels of engagement and involvement in the offshore teams, whether captive or service provider teams, can make a real difference in this area. Having a sense of involvement and belonging will help improve their contribution and productivity. Various measures can be employed to achieve this, including onsite opportunities and involvement in end-to-end projects rather than discrete and isolated tasks spread across several projects.

4) Sustaining Productivity: Once optimal productivity has been achieved, sustaining these levels is at the top of the sponsor’s and service provider’s priorities, especially in the competitive setting of an emerging market. In order to ensure optimal continued productivity, it is essential to define, measure, and track metrics to monitor the success of the engagement. Statistical programming lags behind CDM or Pharmacovigilance (PV) in this respect since it’s challenging to define measurable and meaningful metrics. Hence this needs more attention. With evaluation procedures in place, along with mutually agreed targets, it is possible to monitor the health of the engagement, and anticipate problems before they turn into an emergency. The ramp-up time to build desired level of capability in the emerging markets has to be factored in while outlining expectations and defining service level agreements (SLAs).

5) Hiring, training and developing the right people: The people aspect can’t be overemphasized for an activity like statistical programming which is so heavily dependent on the skills of individuals, rather than the process. The demand and supply skew in emerging markets must also be kept in mind. A certain level of volume fluctuation and attrition has to be assumed and there should be a strategy (such as a ready pool of buffer resources) to mitigate any risk to the business. Also, the average staff profile in emerging markets is often different from what companies may be used to developed markets with mature drug development services – this group may have unique needs for professional growth and development. A continued focus on training will ensure that all parties achieve the best possible results throughout.