Food manufacturers are not unique in the problems they have in evolving and becoming more competitive in their market place. This is a short presentation that talks to the main reasons manufacturers find it so hard t adapt and change and improve their performance.

1. Why
manufacturing
struggles to
evolve
A summary of the systemic reasons manufacturing
companies fail to adequately address operational
strategy
A. Wilson 22 October 2020
FINIDHYN

2. • There are 3 main drivers of a manufacturing
business:
• The Financials of the business
• The Commercials of a business
• The capability of operations to deliver the
business
Finance
Commercial Operations
Optimised
operating
model
FINIDHYN

3. • At the heart of most manufacturing
businesses is an inherent conflict of
measurement and data:
• Finance use currency as the key metric
• Commercial use currency and sales units
• Operations use ‘Eaches’, Time, FTE’s
Yield
• This inability to see our own data
represented differently leads to a challenge
in functional cooperation
Commercial Operations
• In £$
• By category
• By customer
• By type
• In sales units
• In eaches
• In time
• In ratios (OEE etc)
Finance
• In £$
• Aggregated
• By market
• By customer
FINIDHYN

4. • Communication, cooperation and
accuracy is further compounded by
differing stakeholder motivations.
• Often the sales forecast is optimistic
and forced to be overly optimistic by
group
• Often cost reduction is over optimistic
and made more so by group
• Unfortunately for Manufacturing;
where most of the cost and margin is
delivered the decision placed on it
means that it often becomes a
whipping post for poor P&L
performance.
Product capability, Delivered
Margin & Margin capability
Finance
Operations
Commercial
• Group requirements
• Site requirements
• Ambition & Reward
• Over forecast
• Ambition & Reward
• Targeted to meet
budget expectations
• Driven by Improvement
requirements
Unbalanced
motivators
Group
performance
Market
Balanced?
Volumes and Price point availability
Strategy, Response, Ambition, Remuneration
FINIDHYN

5. • It is the interrelatedness of data within manufacturing which allows accurate operational strategy
response and the building of new business models, margin optimisation initiatives and profit
turnaround. Without the proper data we are guessing.
FINIDHYN
Category
Product type
Customer
Sales in
currency
Sales units
Commercial
conversion
ratios data base
Eaches
Operational
Standards
database
Cost per
product break
out
Machine Time
used
Capacity by
process &
product
Materials used
- yield
Financial
Standards
database
Labour time
required
Recipe
Standards
database
!
Financial
Variance
reporting
Operational
Variance
reporting
Performance by
process &
product
!
!
So often we do not have
accurate operational ratios by
product as a total of the whole
process, this means we cannot
reconcile back to the budgeted
costs and see where
improvements can be made.
Much of the time standard costings and
standard margins are disconnected from
reality and these numbers are used to run
the business. This generates many
variances which are usually aggregated
which prevents comparisons with
operational data and leads to inaccurate
financial and commercial responses.
Commercial need to maintain numbers and
forecasts from the bottom up, but because
they almost always work either in sales
units of currency they rely on a top down
method for establishing annual objectives
and often make the categories or sub
categories meet the expectations. There is
a lack of guidance from Operations and
Finance which would allow a SKU level
bottom up REAL GM approach which
would be able to be cross checked with
operational capability.
Very few businesses have accurate standards databases
and the inability of finance functions to create adequate
financial bridges means that standard changes and
improvements at a systems level are not encouraged.
Recipe standards are often based on best case to ensure
the lowest cost in a bid and so are unreliable without
factory trials and therefore skew margins if the tender is
won.
With the advent of ERP, many
manufacturing businesses have
moved away from short interval
control and data collection from
the shop floor and fall back of
variance accounting. This
inevitably leads to a negative
feedback loop and a slackening of
standards and poorer
manufacturing performance.
Quite often this
conversion table is
missing altogether in
businesses due to the
regular changeable
nature of the data in
the commercial space.
This makes
conversions to eaches
impossible, storage
space, palletisation,
transport, space
calculations impossible
for the business.
Productivity and Efficiency calculations are not generally possible
in ERP due to the non linear mathematics governing their
relationship not being a function in the software, making
optimisation from variance accounting impossible.

6. Revised Quarterly
Forecast
MANUFACTURING SYSTEMS ARCHITECTURE - MINIMUM REQUIREMENT
Commercial
Procurement
Planning
Engineering
Production
HR
Finance
Standard database,
Bill of Materials,
Standard Routings
table
New product bidding
Product viability
analysis
Costings database
NPD design criteria
Raw Material
requirement
RMU rolling forecast
Supplier Management
Daily plan by area by
line
Weekly plan by area
by line
HR development plan
CAPEX justification
Skills & Flexibility /
Training plan
Downtime / Lost time
accounting report
Engineering PPM
schedule
Works Order
Management System 4 week/campaign
rolling average
efficiencies
Yield reporting & Raw
material consumption
4 week/campaign
rolling average waste
and yield
Tool Operating Data
Annual volume forecast
Master production
schedule
Plant capacity plan
Labour requirement
plan
Daily / Weekly
operating report
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Business scorecard
DWOR
T&A reporting
Labour control
Priorities List
Financial Variance
Analysis
Supply Chain Rules
Inventory requirements
Planning
Rapid Prototyping
DFM Rules
Voice of the Customer
Plant Production
Rules
SPC
FINIDHYN

7. FINIDHYN
• Delivering new business models in
manufacturing and optimising old
ones requires an intricate
knowledge of the following:
• Process and performance metrics
and behaviours
• Financial budgeting and forecasting
• Commercial forecasting and
category management
• NPD, DFM, Supplychain modelling,
Business modelling, Scenario
planning, Project planning, CAPEX
proposal writing, Stakeholder
engagement.