Managing Operational Complexity - KPMG · Increased complexity can challenge fulfillment, drive up...

Managing Operational ComplexityAn innovative approach for product companies—2016

2© 2016 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

Research suggests that today’s product companyis “over-SKUd” by as much as 25-30%.

Sample #1 Sample #2 Sample #3

“On average, 36% of SKUs accounted for only 3% of sales

and 2% of profits”

“On average 35-40% of inventory was stuck in non-performing, slow-moving SKUs whose cumulative contribution

was less than 5%”

SKUs Gross Margin

61%

39%

95%

5%

SKUs Sales Profit

64%

97% 98%

36%

3% 2%

“In this sample, the average grocery company carries 40,000 SKUs - and over 70% of did not sell a single item in a 32

week period”

SKUs Gross Margin

40,000

30%

70%No

units sold

Today more than ever, product companies continue to operate with portfolios containing a large number of unprofitable and obsolete SKUs.

The challenge


Case Study #1

Case Study #2

Case Study #3

Case Study #4

20%60%

80%

180%

ProfitsTotal Customers

20% of customers drove 180% of

total profits

25%

75%

Total Customers

-125%

Profits

225%

Profits

75% of customers either “broke even” or eroded profits

25%

15%

Total Customers

145%

Profits

-50%

Profits

-80%

Profits

0-5%Profits

15% of customers accounted for

145% of profits

Total Customers

-65%

Profits

165%

Profits

20% 80% of customers were value

destroying or neutral

80%

Even more profound is the impact of unprofitable channels and customers – due to high costs to serve.

The challenge - (cont’d)


Volume-based incentive structures can drive excessive product proliferation –as sales teams sell “whatever a customer wants” to achieve their annual targets.

Changing customer segments and dynamic demand is allowing small niche players to serve specialized needs – and pose a threat to larger product companies.

The growing importance to win on “customer experience”, along with increasing supply chain transparency, is forcing customers to demand more from suppliers.

To keep up with dynamic demand, variations in product characteristics are put into place –causing product families to rapidly expand into multiple SKUs.

Advances in innovation mean there are new products entering the market and inventories can reach obsolescence at a faster pace.

Customers are demanding more specialized products to address their needs –and greater product availability than ever before.

Dynamic demand

Increasing customer demands

Threats from niche products

Pace of Innovation

Frequent product changes

As companies go through acquisitions, they acquire more SKUs. It is not uncommon for an acquisition to increase the total number of SKUs by 20-30%.Acquisitions

Sales Incentives

Most manufacturers are susceptible to this challenge – because of numerous forces on their business.

Why it is happening


For Manufacturing

Increased variety will lead to frequent setups and shorter production runs, driving up manufacturing costs.

For Inventory

Proliferation of SKUs and channels can cause difficulties in forecasting sales and safety stock requirements - ultimately increasing inventories.

For Distribution

Increased complexity can challenge fulfillment, drive up transportation costs, and increase safety incidents related to storage hazards.

For Sales & Marketing

SKU proliferation can result in dilution of brand power and shelf space clutter.

For Procurement

Proliferation can create supplier fragmentation leading to loss of buying leverage and ultimately higher material costs.

For Transactional Costs

Companies can face increased transactional taxes and costs which have a direct impact on operating margin.

For Capital Allocation

Proliferation increases the risk of tying up capital in obsolete inventory and for over-demanding customers –challenging a company to get the most out of its limited resources.

Based on a recent sample – replacing the bottom 25% of SKUs with “value

positive inventory” increased profits.

+20-30%

Excessive SKU and customer complexity can severely constrain a company’s agility – and have serious financial consequences.

Why it matters


Unable to measure “true profitability”

Decisions based on “qualitative” views of

silo-ed teams

Inadequate understanding

of “root causes”

Problems with the “industry standard” approach

Most companies rely on “top line” metrics – and do not account for all “lifecycle costs” at the unit or customer level (including the cost of using company resources).

Most companies do not manage their portfolios frequently enough.

When they do, they fail to address the real “root causes” of poor performance (e.g., by chopping off the tail).

Most companies do not rely on enough “quantitative” input from outside of Category Managers and Sales teams (e.g., Finance and Supply Chain) when making portfolio decisions.

Most companies rely too much on SKUs and customers that absorb capital, do

not generate sufficient returns,

and ultimately destroy value.

As a result…

In most cases, companies are unaware of their risk exposure – largely due to how they evaluate their portfolios.

Where companies go wrong


Where companies go wrong – (cont’d)

Despite the abundance of “big data” – internal barriers prevent companies to reach meaningful insights and actionable decisions that create value.

Lack of robust new-product gate keeping

Poor understanding of complexity costs

Lack of internal alignment

(Perception of) losing volume / sales

58%

65%

55%

23%

67%

50%

25%

33%

What are the biggest internal barriers that limit your ability to manage complexity?Pick all that apply (percent of respondents)

Product Manufacturers Retailers

Most internal barriers can be addressed through greater profitability insights, understanding of root causes, and decision making tools.


More powerful tools for data ingestion

Better measure ofEconomic Profit

Analytical models that verify root causes

Proprietary technology tools and methods that allow for the ingestion of raw and unstructured “transactional” data – from a diverse range of sources.

Approach and techniques for measuring the “true profitability” of unique SKUs, Customers, and Suppliers (beyond high-level metrics such as Gross Margin) – including the cost of unique service conditions.

Advanced analytical models that define the most critical “root causes” behind the results and the most sensitive drivers – allowing you to understand how to unlock value.

Dynamic tools that allow for

scenario modeling

Interactive dashboards and tools that allow for scenario planning and modeling across your functional teams - so you evaluate all relevant levers (i.e., not just “keep vs. don’t keep” decisions).

Concurrent Operational and

Tax Review

A concurrent review of the financial (i.e., tax, trade and treasury) and operational consequences taking a holistic view to optimize total enterprise value.

KPMG has developed new tools and techniques that offer a better way to optimize product and customer profitability.

KPMG’s solution

Measuring ‘True Profitability’


“Economic Contribution” defined…

The difference between a product’s or customer’s net profit - and the cost of all company resources used to make, sell, and deliver those products - and to serve each respective customer.

Accounts for the fact that companies have limited resources to put to work - and products/customers need to generate a return above their cost of capital.

Can be applied to different levels of assets throughout a company’s portfolio (categories, brands, SKUs, suppliers, channels, customers, locations, etc.).

Overall, the best proxy that links product and customer performance to the intrinsic value of the business.

Allows management to understand which assets are truly profitable - and define initial “keep vs. don’t keep” candidates.

Net Profit (after all

lifecycle costs)

VS.Cost of

Assets Used(to make, store, sell,

deliver & serve)

To understand the “true profitability” of products and customers, we start by quantifying “Economic Contribution”.

Introducing Economic Contribution


Data Ingestion

To obtain the information we need, KPMG’s proprietary tools can ingest “raw transactional data” from your ERP systems – regardless of format, size and ERP sophistication.

CustomerOrders

SupplierInvoices

FreightReports

WarehouseManagement

Reports

Bill of Materials

Point of Sale Data

Marketing& SalesReports

S&OPReporting

SupplierMaster

CustomerMaster

ProductMaster

OtherReporting

Examples of “Transactional” Data Sources “Bottom-Up”Economic Contribution Model

KPMG’s proprietary tools can efficiently ingest massive amounts of unstructured “transactional” data tables – into a single economic model.


Sample Outputs

Our tools provide the flexibility to “drill down” into any selected unit (or group of units) and evaluate profitability drivers to define the highest risk areas.

-100

0

100

200

300

400

500

600

Economic Contribution Breakdown(High Volume / Unprofitable SKUs)

vs. Benchmarks

vs. Benchmarks

vs. Benchmarks

vs. Benchmarks

Results will be categorized

and compared to benchmarks

to further expose high

risk areas

A breakdown of profitability can be provided for any

selected unit

Net Sales COGS Distribution Other Operations Invested Capital

vs. Benchmarks

The contribution of every driver will be

quantified

Details will align with the product’s unique Economic

Contribution formula.

Verifying ‘Root Causes’ and Evaluating Scenarios


Defining “Root Causes” and Scenarios

Advanced analytics can verify the most important “root causes” – and expose a wide variety of improvement scenarios to consider.

Options/Levers to evaluate

Remove SKU?

New Service Terms / Charges?

Customer “Gain Share” Incentives?

New Trade Spend allocation?

New Inventory policies?

Component Standardization?

New Sales Targets / Coverage?

New Transportation Pricing?

Forecasting Adjustments?

Changes to SKU Availability?

Volume Commitments?

New Pricing & Promotions?

Bundle with Other Products?

Reduce transactional taxes?

etc.

Scenario Modeling

OPTIONS / LEVERS

(A) (B) (C) (D) (E) (F) (G)

Statistical “heat map” analysis of root causes

SKUs

Economic Contribution Inputs

Systemic issue to

transform?

Product to completely

retire?

Isolated issue to fix?

Customer or channel issue to resolve?

Customers or Channels


Interactive Scenario Dashboards

We deliver information to you through a powerful and interactive dashboard – providing you with the flexibility to evaluate all types of scenarios.

22


Drill Down Analytics – New product development

These insights and tools can also enable your teams to better evaluate new product opportunities –providing a better measure of a SKU’s true payback.

80

-20

20

-1020

35

50

60

-40

-20

0

20

40

60

80

100

120

140

R&D Commercialization Period 1 Period 2 Period 3 Period 4 Period 5 Period 6

Economic Contribution – Payback(SKU #164-127-998)

Pre-Launch(costs)

Post-Launch(Economic Contribution)

Comparison of EC to pre-launch costs will specify a unit’s “true payback

period” where traditional methods will commonly overstate results

Using Economic Contribution to evaluate

future new product development will enable

better investment decisions and promote

Integrated Business Planning

All relevant pre-launch costs should be

quantified - to define the unit’s payback hurdle

Payback hurdle

Upfront Development Costs

Economic Contribution (Return)


Adopting “repeatable” capabilities

Institutionalize new tools, capabilities, controls and financial cost metrics within specific groups (typically Marketing) to

ensure regular monitoring and management (to include cross-functional

collaboration), and execute such plans in a tax-efficient manner.

“Outsource model”“Hybrid model”“In-source model”

Establish a central (independent) “Center of Excellence” – in a tax-efficient manner (e.g., typically within an offshore Finance

team) to regularly track and analyze performance, and to authorize and

manage corrective actions.

Establish a collaborative partnership with a third party – that will efficiently obtain data,

analyze & report on asset performance, and recommend change scenarios) – on a

frequent basis, and execute such plans in a tax-efficient manner.

Following a successful review, companies should evaluate its preferred model for “institutionalizing” capabilities - to monitor and manage complexity on an ongoing basis.

Models for sustainable Complexity Management

ContactsThe contacts at KPMG in connection with this report are:

Chris Gottlieb

[email protected]

(201)-417-6025

Chandra Sekhar

[email protected]

(706)-589-4742

Jack Lippy

[email protected]

(704) 400-0927

Ammon Matsuda

[email protected]

(720)-415-6324

© 2016 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved.

The KPMG name and logo are registered trademarks or trademarks of KPMG International.

The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation.

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Managing Operational Complexity - KPMG · Increased complexity can challenge fulfillment, drive up...

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