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Leveraging Analytics to Manage Supply Chain Complexity in Highly Innovative Companies: A Consumer Goods Industry Perspective White Paper Consumer Packaged Goods

Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

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Page 1: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Leveraging Analytics to Manage Supply Chain Complexity in Highly Innovative Companies:

A Consumer Goods Industry Perspective

White Paper

Consumer Packaged Goods

Page 2: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Will Ruiz

Will Ruiz is a Consulting Partner with the Consumer Packaged Goods (CPG) and Retail business units at Tata Consultancy Services (TCS). With over 25 years of experience in the areas of new product development, manufacturing operations and strategy, IT strategy, and business process innovation, he currently heads the unit's North America Consulting practice. Before joining TCS, Ruiz held strategic roles at various companies – the leader of HP's US Consumer and Retail Consulting practices, a principal with IBM's Business Innovation Services group, a manager with Ernst & Young's Management Consulting Performance Improvement practice, and a senior manufacturing engineer with Analog Devices, Inc. He holds an MBA degree (high honors) and an MS degree in Manufacturing Engineering from Boston University, United States, and has completed the Strategy Value Creation Programme at the London Business School, United Kingdom

About the Author

Page 3: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Consumer goods companies are constantly on the lookout for smart business strategies that help improve the effectiveness and efficiency of the product development process, which helps sharpen an organization's competitive advantage. The rate of successful product introduction in consumer goods companies has not improved over the years.¹ Additionally, the need to manage the ever-increasing number of stock keeping units (SKUs) has made it difficult to maintain operational expenses while increasing process complexity. Annual SKU rationalization and the optimization of New Product Development and Introduction (NPD&I) processes can help streamline supply chain management and allow companies to reinvest savings in brand-building activities or game-changing innovation. This paper discusses how an analytics-based approach can transform organizational performance and recharge innovation processes.

Abstract

[1] IRI, 2014 New Product Pacesetters, April 2015

Page 4: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Contents

The Need to Address Supply Chain Complexity 5

Recommended Approaches for Effective Supply Chain Management 5

SKU rationalization 5

Optimization of NPD&I Processes 7

The Importance of Data 10

The Road Ahead: Reimagining Business Performance with an Analytics-driven Approach 12

Page 5: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Collect, Aggregate, and Analyze SKU Data

LeveragePre-Determined

Criteria to Identify Candidates

-Develop

Rationalization Plan

Execute, Plan, and Manage

Value Realization

Establish Annual SKU

Rationalization Process

Leverage Analytics

The Need to Address Supply Chain ComplexityNothing drives true top-line growth and competitive advantage more than innovation. It’s therefore not a surprise to see this topic rank high in the strategic priorities of senior executives of consumer goods companies. However, with the continued drive to introduce new products into the market, many companies are realizing that managing a growing and significantly larger set of stock keeping units (SKUs) is increasing business complexity and operating costs. These costs typically include investments related to the design, development, manufacture, customization, warehousing, distribution, and marketing and promotion of products. This is especially true in ‘highly creative companies’ where, on a yearly basis, new products with a relatively short lifecycle constitute a high percentage (>50%) of the total saleable (active) products portfolio.

While some level of product complexity (that which serves to meet consumer needs) is welcome, not all scenarios are recommended. For instance, unwanted product variations with limited appeal tend to consume resources that could otherwise be directed to brand-building activities in support of products that are succeeding in the marketplace, or invested in game-changing innovation.

Recommended Approaches for Effective Supply Chain ManagementHere are some strategies innovative companies can employ to manage supply chain complexity.

SKU rationalization

SKU rationalization is a process that leverages product information such as revenue, margin, and sold-to data, as well as the strategic relevance of a product in a given geography, to decide which SKUs should be retired from a product portfolio. This being a one-time event, a company should have a defined annual process to decide which active SKUs need to be eliminated. An overview of a typical rationalization process is depicted in Figure 1.

5Figure 1: An Overview of the SKU Rationalization Process (Source: TCS Internal)

n Identify required SKU data

n Identify source systems for the data

n Aggregate data to provide end-to-end and top-to-bottom view of SKU performance

n Analyze SKU data

n Leverage criteria for sales, variable margin, and strategic importance / value of SKU (e.g. product portfolio, retailer, and geographic region strategies) to identify candidates for rationalization

n Review and discuss list of candidates

n Develop a rationalization plan

n Determine the business value impact of executing the plan

n Communicate plan to key stakeholders

n Execute rationalization plan

n Track and manage business value of the rationalization efforts

n Implement an annual rationalization process

n Ensure it is conducted by a cross-functional team

n Establish a supporting communications plan for all key stakeholders

Page 6: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

6

When properly executed, the first step of the rationalization process can provide the basis for a fact-based analysis to identify SKUs that are the most likely candidates for retirement. A typical analysis of the profitability of SKUs, and their relation to the overall profitability of a company, is given in Figure 2.

Figure 2: Sample Analysis of SKUs (Source: TCS Internal)

% o

f Pro

fita

bili

ty

% of SKUs

TargetMargin

Product Line/SKUs

0% 20% 40% 60% 80% 100%

Candidates for increased investment in resources

and brand-building activities

Candidates for marginal improvement strategies

Candidates for rationalization

Mar

gin

s

Page 7: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

To make the right decision, it is not enough to only understand the actual costs incurred by an SKU (real profitability data based on activity based costing can help with that). Understanding how a particular SKU fits – from a value perspective – in a company's product portfolio, retail, and market (growth and market share) strategies is also vital.

Once the appropriate strategic value has been taken into account, the company will be able to classify its SKUs into three categories: (1) Candidates for rationalization, (2) Candidates for marginal improvement strategies, and (3) Candidates for increased investment in resources and brand-building activities.

SKUs that are considered for marginal improvement should be evaluated for the possibility of:

n Reengineering the product to improve its cost structure

n Renegotiating raw material, sub-component, and manufacturing costs

n Renegotiating price and sales allowances

n Increasing their Direct-to-Consumer (D2C) business (by selling a product through the company-owned website)

Freed-up resources and working capital can then be directed to improve the competitive positioning and performance of products that are doing well in the marketplace, as well as to conceptualize and develop new products.

Having described how companies can implement an ongoing yearly process to streamline their product portfolios by eliminating non-performing SKUs, the key question then is: Are there ways in which companies can leverage data to improve their new product development success rate, and 'permanently' reduce the need to rationalize SKUs at the rate they are doing today?

Optimization of NPD&I Processes

A number of products fail to succeed in the market due to the fact that they do not meet or satisfy the wants and needs of the end customer. Others (especially those in the fashion or toy industries) are not successful simply because NPD&I processes are not agile and robust enough to ensure the product makes it to the market at the right place and at the right time, missing the required on-shelf availability date or quantity. This is particularly true for product launches tied to seasons, holidays, and promotional events such as film releases.

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Successful innovation not only requires a well-articulated strategy and a clear understanding of latent or future consumer needs, it also demands the flawless execution of NPD&I processes.

Page 8: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Best practices in New Product Development (NPD) suggest, among other things, that companies leverage concepts such as concurrent engineering, rapid prototyping, and virtual reality as part of a flexible stage-gate process to successfully develop new products (see Figure 4).

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The operational aspects of NPD&I are depicted in Figure 3.

Figure 3: An Overview of the Operational Component of Successful Innovation (Source: TCS Internal)

Well-ArticulatedInnovation Strategy

Operational Component of NPD&I

Understanding of(Future) Consumer Needs

Flawless Executionof the NPD&I Processes

SuccessfulInnovation

n Objectives for achieving sustainable competitive advantage

n Required cross-functional processes, organizational skills, and underlying enabling technologies

n Social media to communicate directly with consumers

n Co-innovation networks to enhance new product discovery or identification

n Formal Stage-gate process

n Cross-functional ownership

n Concurrent engineering, rapid prototyping, and virtual reality

n Formal post-launch reviews

n Database of raw materials, formulas, specifications, packaging, processes

n Database of best practices and regulatory mandates

Page 9: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

However, we have observed that mastering this process can be elusive for companies. The lack of process discipline, inability to recognize process variability due to product complexity, no formal post-launch reviews (PLRs), and limited central repositories of reusable materials, components, and processes, are some of the challenges companies face when executing NPD&I processes. All of this gets compounded when shorter product lifecycles, higher number of yearly seasonal and event-driven product introductions, rigorous licensing approvals, and outsourced manufacturing are added to the mix.

To help companies deal with all of these challenges, we recommend an in-depth analysis of their end-to-end NPD&I process data, including in-market sales performance. In our engagements with industry players, we have observed that such an analysis enables them to segment their products (even within product lines), and determine how product characteristics drive product development complexity and process variability.

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Execution of Events, Promotions , Allowances

Generate and Manage Ideas

Define/ Develop and Test

Concepts

Develop and Test Product

Develop Artwork and

Packaging

Manufacture Product

Launch Product

Manage Product Lifecycle

= Gate Reviews

Engineering/Production

Manufacturing, Supply Chain

Sales, Marketing &Brand Management

LaunchPlan

Inventory and Distribution

Plan

Product Constraints, Test

PlansBrand

Requirements, Product DesignTechnical

Feasibility

Strategic Portfolio, Resource, and Project Management

Functions

Ideation Mgmt.

UnderlyingCapabilities

Integrated Data Analytics and Insight Development(Includes Business Process Management)

Collaboration with Business Partners, Customers and Consumers

(Internal and External)

(Internal and External)

IT

Database of Components, Raw Materials, Formulas, Specifications, Packaging, and Processes

= Structured Post-Launch Review(s)

(Internal and External)R&D

(Including Licensing Process Mgmt.)

Licensor (Internal and External)

Figure 4: Concurrent Engineering in the New Product Development Process

Understanding how product design choices impact NPD&I processes is key to a company's success in bringing new products to market, on time, and in the quantity necessary to meet the required shelf-fill rate.

Database of Best Practices and Regulatory Mandates

Page 10: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Our analysis of the NPD&I process at leading industry players reveals that even within a major product segment (for instance, fashion or toys) and its underlying product lines, there is room for multiple variations of the process. This is above and beyond the typical time variations attributed to minor modifications, line extensions, and completely new products. Figure 5 provides an overview of how a company can develop models for each type or segment of their products.

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Figure 5: Leveraging Analytics to Optimize the NPD&I Processes (Source: TCS Internal)

By following this approach, a company can gain granular insights into its NPD&I processes, by product line or segment. Additionally, with insights on which product features or process steps are most likely to contribute to project delays, companies can more closely monitor their performance against the standards for the new NPD&I processes. The result of such a comparison can serve as the 'early predictor' of potential success or failure of a newly introduced product.

These early predictors will allow companies to make timely course-corrections during product development, or make a decision on the viability of continuing with a project that is likely to not deliver a successful market introduction outcome (thereby reducing the proliferation of non-performing SKUs).

The Importance of DataIn order to make NPD&I analytics work, it is vital to have ready access to clean data, with the ability to display and analyze it in a way that enables business decisions. It is equally important to address the organizational change management considerations related to understanding how the new NPD&I process should be executed in the light of new data and models.

Identify and collectSKU data, and perform SKU

segmentation

Review datafor errors, gaps, completeness,

and so on-

Aggregate data toprovide full view of

SKU lifecycle

n Identify data sources

n Collect and stage the data

n Segment SKUs (classification criteria could include seasons, major promotional events, and so on)

n Review the data to identify and correct errors

n Fill in the gaps in information, standardize formats where required

n Create (if appropriate) attributes based on certain SKU characteristics

n Create a database containing aggregate SKU information from concept generation to in-market sales performance

n Develop hypotheses to be tested

n Perform analysis to determine key factors driving success/failure of new product introductions

n Determine NPD&I process duration by product line or segment

n Leverage models and analyses to predict, at an early stage, if an NPD&I project is in trouble

n Develop and implement a process health and early-warning dashboard

n Leverage learnings to optimize models and the NPD&I process (by segment)

Develop hypothesesand perform statistical

analyses by segment

Incorporate insightsinto the NPD&I processesand implement a process

health dashboard

Page 11: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

Successful 'full lifecycle' SKU analysis requires integrating large sets of data from disparate (internal as well as external) source systems such as product lifecycle management (PLM), enterprise resource planning (ERP), point of sale (PoS), supply chain management (SCM), and manufacturing applications and databases (see Figure 6).

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Figure 6: Information and Data Sources (Source: TCS Internal)

We have observed that all of the typical data sources tend to have limitations and contain data inconsistencies, as well as errors. These typically stem from manual data entry, inadequate process discipline, incomplete or incorrect master data, and outdated SKU information residing in the systems. Before companies attempt to automate this type of analysis, it is advisable to work with a set of pilot data. The pilot phase will allow companies to fully understand any shortcomings the data might have. It will highlight when business resources at the R&D department or the supply chain and brand management division may need to 'systematically' intervene to review and correct the data, or inject business context into the analysis.

n Product Strategy

n Geography/Market Strategy

n Sold-to/Retailer Considerations

n Sales/Revenue Targets

n Variable Margin Targets

n Rationale for Product Variations

PLM Data ERP DataDemand & Supply

Planning Data

ManufacturingData

“Authoring” “Execution”

n NPD&I Data

n Product Characteristics

n BOM

n Initial Forecasts

n Complexity of NPD process by SKU

n Adherence to NPD process/milestone timing

n Design changes by SKU and by NPD process step

n Costs for each type of change

n Product Hierarchy

n Product/Item Master Data

n BOM

n Financial Data

n Actual Product Costs

n Materials n Manufacturingn Distribution,

Logisticsn Marketing/

Promotionn Sales

n Sales and Sold-to Data (by Market)

n Inventory Data

n SKU Forecasts, Orders

n Market Introduction Date

n Promotional/Event Calendar

n Sourcing, Lead Times

n Capacity

n Quality

n Ramp Up

n Shipment Data

Page 12: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

The Road Ahead: Reimagining Business Performance with an Analytics-driven ApproachIn a world where consumer tastes, needs, and preferences are changing rapidly, new product introductions continue to accelerate, while product lifecycles shrink drastically. This is especially true in segments such as fashion (apparel, footwear, and so on), toys, and consumer electronics, but increasingly so in other consumer goods segments (such as food, beverage, and household items) as well.

To succeed, companies will need to revamp and continuously evaluate and optimize their NPD&I processes. With analytics, companies can tailor and fine-tune their innovation processes to ensure they use the best-fit product development and launch strategy, and execute the plan flawlessly in order to maximize revenues in today's fiercely competitive marketplace. Those that do this will have a notably better chance of winning over their competition, and delivering superior shareholder value.

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To survive and thrive in an environment marked with rapidly changing consumer preferences and shrinking product lifecycles, CPG companies need to continually reinvent their NPD&I processes. Analytics can be of great help in achieving this.

Page 13: Leveraging Analytics to Manage Complexity in Highly Innovative Companies - A Consumer Goods Industry Perspective

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About TCS' Consumer Packaged Goods and Distribution Unit

Tata Consultancy Services (TCS) has strong experience in the CPG and Distribution industry and specializes in designing solutions that are aligned with customer needs and emerging trends.TCS blends domain knowledge, technology expertise and delivery excellence in the CPG and Distribution Industry. We leverage our core offerings and provide specialized capabilities in Mobility, Big Data, Digital Marketing and Analytics to create solutions that transform areas of greatest impact for CPG and Distribution companies in Sales and Marketing, Manufacturing, andSupply Chain Management.

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