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Powerful forecasting for a good planningOrdina Customer Day 2013

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Contents

Forecasting and planning – a perfect interplay

What to forecast and how to forecast it

Forecasting with Ordina and Quintiq

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Forecasting and planning – a perfect interplay

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What is forecasting?

From businessdictionary.com:

- A planning tool that helps management in its attempts to cope with the

uncertainty of the future, relying mainly on data from the past and present

and analysis of trends.

Data from the past

Trends

Data from the present Certainty of the future?

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Forecasting for planning ends

Forecasting becomes useful in a planning context as soon as the important

planning decisions must be based on

- Need for a certain product, e.g. the need for certain consumer goods such as beer,

canned goods, …

- Need for a certain service such as airport security, roadside assistance, shipment

transportation, ...

An accurate forecast leads to a good mid term and long term (capacity)

planning.

A good mid term and long term planning leads to a good short term planning.

This leads to cost reduction as well as customer satisfaction:

- No external parties need to be used to reach SLA

- Capacity is available to ensure in time delivery

- Stocks can be maintained at optimal levels

- …

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What to forecast and how to forecast it

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Before deciding to use forecasting.

When considering forecasting to have a substantiated basis for long term

planning, we need to answer several questions.

1. What planning decisions do we want to make and what do we base these

decisions on?

2. What are the main factors that influence the basis for these decisions?

3. At what level of detail can we make a prediction?

4. Can we refine the prediction as we process in time?

An answer to these questions will

- not only tell us what to forecast,

- but also what techniques we should use to create this forecast.

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What are the main factors that influence the basis of these decisions?

- Historical trends of incidents and B2B agreements.

- Historical trends of visitors, B2B agreements and commercial campaigns,

new product and service launch, …

- Historical trends and customer announcements.

What planning decisions do we want to make?

- E.g. roadside assistance: we want to minimize the use of external parties

needed to maintain our customer service levels.

- E.g. airport services: we want to optimize our time to service and minimize

our personnel cost while maintaining our customer service levels.

- E.g. postal services: we want to optimize machine utilization and minimize

personnel cost while maintaining our target throughput times.

Some examples

Based on the number of incidents on the road.

Based on the number of visitors and passengers at the airport.

Based on the postal volumes received each day.

Information and

knowledge from

other divisions

Historical trends Short term

operational

information

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Different forecasting methodologies

Consensus forecasting

- Several parties each make a separate forecast, based on their experience

and knowledge.

- These separate forecasts are combined together to form a final forecast.

Statistical forecasting

- Mathematical techniques are used to extrapolate historical data to the

future to form a final forecast.

Combining forecasts

- Forecasts created using different techniques are combined to form a final

forecast.

- Typically, a statistical forecast serves as the basis for the forecast. It is

subsequently enriched with information received from other channels to

form a final forecast.

Gartner (september 2012)

Defining the balance between statistical modelling and collaborative forecasting

improves accountability for the forecast, and enables continuous improvement

across the organizationCompanies can benefit from clearly defining the balance between statistical modelling and

collaborative forecasting methods to improve accountability for the forecast and put in place

continuous improvement plans to improve the forecast. […]

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Good forecasting uses the best of all worlds

Advanced statistical

techniques

Relevant forecast information

from all divisions

Last minute operational

informationActuals

Weather forecast

Historical data

B2B agreements

Sales campaigns

Experience

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Forecasting with Ordina and Quintiq

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Shortcomings of traditional solutions

Traditional forecasting solutions typically focus on one specific

methodology with little possibilities to interact between methodologies.

Traditional forecasting solutions serve as a black box. Numbers go in

and numbers come out, with little or no control.

Traditional solutions have a rigid dimension management, limiting the

correct mix of statistical techniques and enrichments.

Traditional solutions typically lack dynamical graphical representations

of the forecasts.

Traditional solutions allow little or no refinement based on operational

data.

Traditional solutions provide shaky foundations to build a planning on!

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Ordina & Quintiq

- Strong statistical basis

- Enriched with relevant additional

information

- Concurrent what-if scenarios

One methodology versus best of all worlds

Traditional solutions

- Statistical forecasting with limited

override functionality

- Consensus forecasting with limited

statistical foundations

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Black box versus open information

Traditional solutions

- Limited options in algorithm creation

and maintenance

- Limited or no business rules

available

Ordina & Quintiq, with the power of R

- Statistical algorithms are available

through R.

- Expert users can create their own R

scripts and algorithms in the tool.

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Rigid dimensions versus open hierarchies

Traditional solutions

- Fixed number of dimensions

- Dimensions grouped in fixed

pyramidal hierarchies

Ordina & Quintiq

- Dimensions can be added without

limitations

- Hierarchies between dimensions can be

created dynamically

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Ordina & Quintiq

- Colours, formatting and icons can be

used to visualize extra information.

- The graph has advanced

configuration possibilities (bar, line,

dotted) and can easily be navigated

Graphical representations

Traditional solutions

- Simple spreadsheet with textual

information

- Simple graphical representation with

limited navigation

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Limited refinement versus advanced enrichment andconsumption

Ordina & Quintiq

- Forecasted volumes can be adjusted

based on actuals received.

- A number of consumption logics are

available and can of course be extended

to match any business rule needed.

Traditional solutions

- Little interaction with operational

information.

- Limited possibility to adjust using last

minute information

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Summarizing

Quintiq demand planner: a good basis for developing a forecasting solution

- Clear graphical and textual visualization of forecasts

- Multiple scenarios allow rapid simulations and lead forecast selection

- Standard statistical algorithms available through interface with R

Ordina forecasting solution: in addition to the demand planner

- Unlimited number of forecasting dimensions available

- Advanced control of breakdown hierarchies and factors (no fixed hierarchy)

- Long and short term forecast enhancement and correction based on external

input.

- Advanced parametrizable consumption logic available

- Full access to R to allow expert users to create and maintain their own

forecasting scripts.The Ordina and Quintiq forecasting solution provides a solid basis for a

good planning!

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Data from the past

Trends

Data from the present

Certainty of the future!

That is, as certain

as we can ever be…

A solid basis for…

17:00 Shift Rostering

by Kris Van Marcke

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Questions?