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About the Authors

Ashwin Patil
Director, Analytics and Information Management
Deloitte Consulting LLP

Ashwin Patil is Deloitte Consulting LLP’s lead Manufacturing industry director for Analytics and Information Management. He has over 15 years of experience in the manufacturing industry, as well as extensive multi-industry exposure. He has led multiple solutions, implementations and go-to-market strategies in the analytics and information management space and is a thought leader in areas of business intelligence strategy, advanced analytics, performance management, and information management.

Lane Warshaw
Senior Manager , Information Management
Deloitte Consulting LLP

Lane Warshaw is a senior manager in the Information Management practice of Deloitte Consulting LLP. Lane has more than 18 years of experience in the manufacturing industry specializing in enterprise data management (EDM). His recent experience includes delivering data solutions that enable sales, marketing, and supply chain focused analytics through the use of big data, visualization, and agile approaches.

Supply Chain Comment

By Ashwin Patil Director, Analytics and Information Management Deloitte Consulting LLP and
     Lane Warshaw Senior Manager , Information Management Deloitte Consulting LLP

August 6, 2015

A Business-Driven Approach to Supply Chain Analytics

Moving From Traditional Data Service to Rapid and Agile Business Intelligence

The promise of advanced analytics gives companies the ability to mine troves of supply chain data – from procurement and manufacturing to logistics and warehousing – to pinpoint inefficiencies and opportunities, and to fine-tune their increasingly complex global supply chains. 

Yet, the traditional method to capture and capitalize on this data is to:

Patil and Warshaw Say:

Embracing visualization tools and agile methods can provide an environment that supports self-sufficiency.
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Identify all enterprise data


Design a data warehouse schema to house it


Provide a single authoritative data set to deliver analysis 

It’s a tried-and-true method, but as a “one-size-fits-all” approach to integration and data management, it’s just not nimble enough for the business.  Establishing the infrastructure, information governance and data models is costly, time consuming, and will likely mean many business opportunities will be missed. Further, once built, business users do not have direct access to the data and the request process to receive a report can lag –which can often result in missed opportunities or supply disruptions like stock outs. Moreover, with the advent of ‘big data’, the approach of starting with data consolidation has become even more expensive and time consuming.

The supply chain management function has specific data and analysis needs, and most companies want strategic insights delivered in real-time, as well as segmented by various dimensions like business group, geography, product category, etc.  These market demands have been met with new delivery methods coupled with a class of visualization and analytics tools that deliver rapid, and agile, data analysis capabilities.  Analytics and visualization platforms empower the business user with a self-service, data discovery tool that provides direct access to data analysis. 

We are seeing a new wave of agile development methods and approaches like design thinking, which model how specific business users, called personas, go about their daily tasks to make business decisions through journey maps.  Combining journey maps with the power of visualization and analytics tools helps transform the traditional data service model and delivers meaningful insights much more rapidly with data that is based on business behavior, not on data formats and types.  It allows global fortune 500 businesses that have grown through acquisition to bring data together from a variety of internal ERPs, manufacturing and supply chain systems to better manage forecasts, inventory, and lead times, and improve manufacturing planning.  These rapid prototypes demonstrate to be immediately valuable to the business, and serve as a model for IT, in building the longer term infrastructure to rollout solutions across business units.

An important consideration in taking this approach is the necessary shift in the business culture to support an analytics-driven organization.  There are two key transformations here; first, the IT team should be willing to collaborate with the business users to ensure that analytical projects reach their potential and deliver high value to the business, as well as to suppliers and customers.  Second, decision-makers should be willing to accept analytics as metrics for which the enterprise will use to help drive the business. 

A key component to making the transformation is forming an analytics center of excellence (COE).  Similar to creating a data governance model in IT, the COE is designed to bring together a community of skilled analysts who can facilitate and enhance the adoption of analytics within an organization.  Establishing a COE enhances the quality of the company’s analytics efforts as a whole by helping to ensure that the methods, tools and technologies are standardized, and that people can understand how to use the tools to perform their jobs at a higher level.

We’re in the midst of an exciting transition in how data can be used to transform business.  Embracing visualization tools and agile methods can provide an environment that supports self-sufficiency.  IT is elevated to a role where the team can focus on supporting the business, while maintaining the data and analytics infrastructure in order to deliver real-time and targeted business intelligence in an agile manner that is much more rapid than the traditional methods of the past.  As data volumes continue to grow, organizations that can proactively respond to a dynamic marketplace with easy-access data insights have the opportunity to capitalize on their agility to build a more sustainable, competitive advantage.

Column Sponsored by: Qlik

Qlik enables organizations to explore supply chain data and processes in unprecedented ways, discovering hidden insights which result in better decision making and drive improvements in supply chain operations.  Built on the industry’s leading Data Discovery platform, Qlik supply chain solutions help customers connect and manage the supply chain from end to end while increasing visibility, reducing risks, and optimizing operations.  With Qlik, organizations can analyze, visualize, and explore relationships between complex data sources.  The result is a more connected customer-centric supply chain which drives better business results and a competitive edge.

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