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Reinventing Supply Chain Analytics for a Global Pharma Giant

Reinventing Supply Chain Analytics for a Global Pharma Giant

Overview

The global pharmaceutical giant offers a wide range of products and services across geographies. This spread brings in a lot of consistent business but exposes decision makers to the monumental task of managing a complex network of distribution centres & vendors – along with inefficient processes at each level. At the same time, the process was prone to human error and turn-around time for reporting was longer than expected.

With a view to completing the digital transformation of the entire enterprise, eliminating inadequate practices and fuelling innovation led by dynamic supply chain planning and analytics, the global pharma giant implemented were evaluating a platform and seeking a partner who could help them eliminate incongruities, modernize the key pillars of their SCM gamut - as in, inventory planning, spend analytics and vendor analytics - each of which was to underpin their emerging business requirements. Polestar partnered with the key customer’s stakeholders and implemented the overall solution by leveraging Qlik, NPrinting, Power BI (backed with a DWH), which helped in removing all the hassles through automatic calculations & revisions, suggesting scenarios to course correct. The implemented solution acts as a single version of truth for supply chain data, analytics and report – which, in turn, enables data-driven decision making

Key Challenges

The global pharmaceutical giant offers a wide range of products and services across geographies. This spread brings in a lot of consistent business but exposes decision makers to the monumental task of managing a complex network of distribution centres & vendors – along with inefficient processes at each level. Here is how the key challenges can be summarized:

Solution Implementation

The SCM team needed to keep the nature of inventory and spend management dynamic due to the very nature of the business. But, at the same time, this called for going back & forth multiple times, and consequently, adding up to the complexities and furthering the chances of human-errors. Consequently Polestar partnered with the key stakeholders to help them traverse their journey of modernization SCM data consolidation, analytics and reporting. Polestar’s Team engaged with the SCM team who were primarily mandated with the responsibility of keeping track of the payments and spending on raw materials, packing materials and transportations. They were also required to keep track of inventory and inventory shortage. The team worked in collaboration with the customer’s team and conducted extensive requirements gathering phases in order to understand and also brainstorm various aspects of SCM reporting & analytics needs such as – data sources, integrations, data quality needs, analytics needs, reporting needs, etc.

The contemporary processes at the SCM department were largely dependent on manual extraction of reports from different data sources for the preparation of excel based periodic review/tracker reports. SAP and Excel will be two major Data Sources. SAP for extracting SAP related data and Excels to extract Budget/Plan related data, wherein MM, QM, FI, and PP were the major modules.

The overall Discovery Methodology was 5-pronged and included:

Given the insights from the Discovery phase, and with an objective to eliminate all the key challenges, Polestar commenced with the implementation of an enterprise-wide analytics and reporting platform based on Qlik, NPrinting, Power BI and the backend DWH.

Leveraging these modern technologies helped in modernizing the way below modules (& sub-modules) used to function and bring in unprecedented advantages:

Inventory planning
Value analysis,
Inventory NODs,
Shortage, ageing and shelf life analysis
Spend Analytics to highlight budgeted vs actual spend
Vendor Analytics, to enable vendor evaluation in terms of quality, cost and delivery

Specifically around Inventory management, Polestar’s Team collaborated with the key business stakeholders to established a platform enables toe complete horizon of inventory management & analytics, which included:

Inventory Demand Forecast - involves using historical inventory consumption data to predict future consumption rates
Economic Order Quality - to enable calculation of the level inventory to be maintained
Safety Stock Calculations - which determines the level of stock required to minimize stocks
Re-order Triggers - enables stock management team to determine the ideal re-order time for stock
Inventory Ageing - age categorization of inventory to reduce old / obsolete stock

The implementation team built a roadmap of establishing a set of KPIs that would act as the guiding force into the decision making process. Outlined below a few of them, among others:

Resulted Benefits

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    Shift from manual work to an automated environment for reporting

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    An Established single-version-of-truth

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    One place to govern data (no duplication of effort and data)

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    Faster turnaround time for the real-time reporting

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    Data-driven decision making

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    Consistent approach to data cleansing, formatting, validation and transformation

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    Single platform for all business stakeholders – right from the company board to the individual distribution centers

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    Faster, efficient and scenario decision-making enabling prescriptions of the best-next-move

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    Transparency and accuracy infused across various levels with rightly implemented Master Data Management

Business Outcomes

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