Pharma organizations are driven by the ability to effectively and quickly understand their competency requirements, bench strength, resource availability when producing a drug.
Allocating the right resources to the right tasks remains the cornerstone of this drug development journey. Assigning specific individuals, rather than generic roles or forecasts, to project tasks based on their skills, defined roles, and availability is also known as named resource management. With this process, teams delegate specific tasks to employees at specific times making resource utilization more accountable and accurate.
But is named resources only for line manager’s visibility? Not entirely true, when done right, it can improve the employee engagement, trust and enhance leadership to assess the workforce impact and cost implications. The key to achieving granularity in named resources is data integration.
Having a clear view of available resources, comparing them with project demand forecasts, tracking actual effort through time reporting, and forecasting future resource needs enable successful data integration journeys to take shape. Once all these disparate data is collected, resource planners can spot patterns offering new insights on their portfolio.
In biotech, data-driven insights empower everyone, from line managers to leadership, to optimize resource management by focusing on key performance metrics and day-to-day operations.
Here’s a closer look at each of the contributing data sources in the data integration journey in named resource management.
Master resource data
Supply data on resources gives you a clear picture on the type of workers present in your organization across portfolios. This is the starting point for your named resources data integration journey. You can derive this data from HR systems that define an employee’s job title, years of experience, and staff class for operational planning.
But organizations also need to stratify people into planning roles, agnostic of title, location and years of experience, aligned to a specific skill set that helps support the portfolio.
This master resource data offers a foundation for resource managers to identify capacity constraints and proactively appoint resources based on the variations in the working hours by country, part-time resources and contactors, and attrition rates.
Demand forecasting data
Accurate estimations of resource demands entails projecting the short-term and long-term resource needs to deliver portfolio projects. Approaches to the right demand forecasting vary based on the type of function, access to data, technological maturity and organization scale, size and budget.
Effective demand forecasting data can enable planners to mobilize resources according to sudden changes. Managers and leadership also can find the right resources when there is a need without scaling the business up or down.
Having the correct demand forecasting approach that best aligns with your organization’s goals, technology investment and data assets is imperative. A smaller pharma organization with limited technology resources and source data may opt for a templatized forecasting approach, while a larger organization can go for a sophisticated AI-driven machine learning approach that automates insights at the most granular level.
Time recording data
Time recording or the analysis and measurement of effort spent to execute work -both internal and external is critical in the decision-making process. This goes beyond checking time trackers for reviewing charged times.
Resource managers rely on algorithms to provide more projectability when resources are needed during projects and rationalize resource time on strategic priorities. This helps teams to monetize tax benefits and credits in the long run.
Effective time tracking provides resource managers with the opportunity to estimate the effort accurately in projects. It enables them to highlight capacity constraints and gives insight into burn-out and attrition rates – the two reasons why employees leave the organization.
One of the core challenges for named resource data integration is ensuring that disparate data for resource supply, time tracking sheets and others are standardized. Inconsistent data can disrupt the integration and produce misleading analysis.
2. Data quality
Improving the data quality remains of paramount importance with pharma teams establishing strict protocols for data integration. Regular audits and specialized training in data management is also needed within teams for a smooth integration journey.
3. Strict data security and regulatory compliance
Ensuring data security in pharma teams is of utmost importance and this can be a significant challenge given the complexities of processing data. Every step needs careful consideration, and even minor glitches can have consequences for resource planning in organizations.
4. Interoperability and data competency
Crafting interoperability standards for pharma data by implementing data sharing policies, developing robust data execution standards are also important in named resource management. Proper competency in data integration tools is eventually necessary to harness the exact potential in named resource management.
Effective named resources align data from all the above-mentioned multiple sources effectively. This enables the organization’s vision to match with business outcomes. It helps drive capabilities toward achieving key business goals.
Traditionally, the tools for naming resources, include whiteboards, Excel sheets and larger project management tools. These come with several limitations as organizational complexity increases.
Whiteboards or napkin notes are simple and agile, but they lack collaboration, become reactive, compromising decision quality when scaling up. Excel offers more structure and flexibility but demands significant manual updates and becomes increasingly difficult to scale, leading to unreliable decision-making.
Project management tools like Project Online or Planisware provide improved scalability and collaboration, but their complex interfaces and slow adoption cycles can hinder effectiveness. These tools often focus on high-level planning, leaving the granular details needed for day-to-day resource management underdeveloped, which can limit their utility in functional execution.
As we have seen, named resource management relies on integrating data from numerous touchpoints residing in multiple systems. This is why having a framework with intentional integrations is so critical. Without manually collating resource data, relying on flexible customizable options like Alloc8 is always an efficient option.
Here’s how.
Alloc8 offers a superior alternative by seamlessly integrating data from various systems, eliminating the need for manual maintenance. Unlike traditional tools, which often require cumbersome data management across multiple platforms, Alloc8 pulls all necessary data into one centralized system, enabling effective forecasting by allowing teams to predict staffing needs at the individual, project, and portfolio levels with precision.
It integrates easily with larger PPM tech stacks, offering a cost-effective solution without the need for complex API integrations.
This level of integration and flexibility ensures that resource allocation is both accurate and efficient, making it a far more reliable tool compared to traditional methods.
It excels in offering a unified view of named resource management data. By pulling in critical inbound information from various systems, such as portfolio prioritization from strategy teams, project activity data from project teams, resource forecasts from larger PPM solutions, and staff information from HR systems, Alloc8 ensures that every aspect of resource allocation is covered. It also integrates contractor information and actual hours worked from time-tracking systems, giving a complete picture of both demand and availability.
Outbound data is equally important in this data integration journey, and Alloc8 supports seamless communication by generating reports for functional leaders, alerting teams of changes to their work assignments, and comparing actuals with forecasts. These insights help leaders make informed decisions, identify trends, and take timely action.
By breaking down data silos and helping in the integration of data from different departments, Alloc8 provides a comprehensive, real-time view of resource allocation across projects, geographies, skills, and roles.
This holistic approach ensures that all stakeholders, from HR to finance to project teams, have access to the most relevant, real-time data integration for smarter decision-making. You can define skills, roles within functions, and assign individuals to specific tasks to glean comprehensive and actionable insights on overall resources.
With granular visibility in named resources planning, take the first step with Alloc8 toward a focused, empowered approach to managing your precious life sciences assets.
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