ECR Community Shrink & OSA Group

Welcome

Inventory Record Accuracy Webinar – November 19th 2019

Colin Peacock

1

ECR Working Group on

Retail Losses

Working Group established in 1999Create new knowledge, tools and techniques for ECR members

Benchmark and learn together at working group meetings

Build definition around best practices and good collaboration

Retail Loss - Size of Prize

Lost Sales (Profits) from Shelf Out of Stocks (0.78%)

Unknown Stock Losses (0.67%)

Food Waste in Retail (1.64% of Sales) – Markdowns & Throws

Participants

Todays Webinar

Launch the Report – Academic Team

Retailer Response – Tesco

Questions Use Tab

Send to colinmpeacock@ecr-shrink-group.com

3

- 4 -ECR webinar – November 19, 2019

Yacine Rekik, Aris A. Syntetos, Christoph H. Glock

Inventory Inaccuracy in Retailing:

Does it Matter?

- 5 -

About us

Christoph Glock

Professor atTU Darmstadt

Yacine Rekik

Professor atemlyon business school

Aris Syntetos

Professor atCardiff Business School, Cardiff University

With the participation of 7 European RetailersSupported by:

- 6 -

Background and objectives

Inventory inaccuracies are a major issue in retailing

Physical stock is (typically) less than what we think it is

Prior research found that incorrect inventory records may range between 65% - 80%

It make sense to assume that inaccuracies lead to reduced sales, or conversely,reconciling inventories may only lead to an increase in sales

We will see later that positive stock discrepancies are also possible, still leadingthough to reduced sales!

The problem has been established; we are not here to argue for itsexistence

Rather, we wish to turn a speculation into a trustworthy conclusion.

- 7 -

The problem: how inaccurate stock records may trigger stockouts

- 8 -

Objectives of this project:

1. To what extent are inventory records inaccurate in retailing?

2. How do inventory records deteriorate over time?

3. How does an improvement in inventory record accuracy affect sales?

We investigated the above research questions with the help of a test-controltype experiment.

Background and objectives

- 9 -

Experiment I

This experiment helps us to answer research questions 1 and 3.

- 10 -

This experiment helps us to answer research question 2.

Experiment II

- 11 -

The retailers

Seven retailers participated in this project:

- 12 -

% of incorrect inventory records

In 60% of the audited SKUs, the (physical) quantity on stock did not match the quantity displayed in the information system at the time of the stocktake

- 13 -

The share of SKUs affected from inaccurate inventory records per retailer

% of incorrect inventory records

- 14 -

% of incorrect inventory records by retailer category

Inaccuracy is not always a matter of shrinkage: it could be positive or negative

- 15 -

Direction of the stock record discrepancy by retailer category

Magnitude of the positive and negative inaccuracy:

- 16 -

Classification of SKUs by turover and discrepancy contribution (Grocery)

Fast Movers: few SKUs with a high contribution to both sales and discrepancies

- 17 -

Discrepancy contribution of different product categories (retailer d)

Discrepancy is strongly linked to the SKU category and number of SKUs handled by the department

- 18 -

Stock record deterioation over time

Stock Accuracy moves from 40% to 20% in 14 weeks:

- 19 -

Stock record deterioration over time per category

- 20 -

Sales increase resulting from better stock accuracy per retailer

The benefit resulting from the stocktake is positive for all retailers with an average of 6%

- 21 -

Average percentage sales increase by product class

Fast Movers benefits more from stock accuracy

- 22 -

Average percentage sales increase by discrepancy class

High Discrepancy SKUs benefits more from stock accuracy

- 23 -

Average percentage sales increase by direction of inventory discrepancy

There is a positive sales increase for SKUs subject to both positive and negative discrepancies

- 24 -

Average percentage sales increase per product category (retailer d)

- 25 -

Summary

We have found the IRI problem to be as big as previously reported

But we have shown it to be associated with different magnitudes in different sectors

This should be considered when benchmarking against average performances

If the sales opportunity is to be taken into account, the IRI problem is(much) bigger than previously thought to be

This is true across the board in the retailing industry

Positive discrepancies are as common as negative ones

It is not all about shrinkage; backroom operations may help explain the problem too

And information about this should be useful for targeting the right IRI drivers

- 26 -

Summary

Removing IRI from the stock records benefits fast movers and highdiscrepancy items the most

An immediate strategy would be to concentrate on high discrepancy fast movers

Counting these items more frequently could help avoid costly stock counting routinesthat often target the entire product portfolio

We have also found that we need to change our perception on counting

Stock takes are perceived a necessity – and they are indeed!

They are also though an opportunity to boost sales

Stock takes and their timing should be seen as a sales increasing strategy

Their cost needs to be contrasted to the potential sales increase before relevantdecisions are being made

- 27 -

Practical recommendations

Check which type of IRI (positive or negative) is bigger

If negative, look at shrinkage. If positive, look at your backroom!

Repeat the experiment described in our report and calculate the salesincrease that stocktakes can generate

Contrast that to the cost of the stocktakes and then you have a good idea about yourreturn on investment

Rethink the purpose of stocktakes

Prioritise your efforts in sorting out IRA

The ‘law of vital few’ applies here too

- 28 -

Next steps

Preventive:

Prevent errors by best operational practices; for this we need to understandthe errors’ sources

Corrective:

Correct more frequently and in a more intelligent manner the stock record byoptimising the audit policy

Predictive/Anticipatory:

By using Artificial Intelligence techniques, deduce data patterns warningmanagement that stock accuracy starts to impact sales.

- 29 -ECR webinar – November 19, 2019

Yacine Rekik, Aris A. Syntetos, Christoph H. Glock

Thank you

Todays Webinar

Launch the Report – Academic Team

Retailer Response – Tesco

Questions Use Tab

Send to colinmpeacock@ecr-shrink-group.com

30

31

Inventory Record Inaccuracy:A Retailer Perspective

Hannah NewtonLoss Prevention & Analytics ManagerSafety, Security, Shrinkage & Service DepartmentTesco PLC

32

Perception vs. Reality

60% of inventory records are inaccurate

A count can deliver a benefit, regardless of the outcome

Fast moving lines are less accurate, but deliver more sales

• Significant risk to ordering accuracy - most systems assume that inventory records are accurate!

• Should we be investing as much in improving inventory record accuracy as we do into improving ordering algorithms or forecast accuracy?

• Both positive and negative corrections can drive a sales benefit

• This challenges the perception that products only benefit from counts when there is a need to replace missing stock

• The results show that one size does not fit all - sales benefits diminish significantly on slower movers and products with smaller discrepancies

• Should we be completing more targeted counts to obtain better value for money?

33

Understandingyour root

causes

Validating your opportunity

Invest in accuracy, not just counting

What drives your inventory record inaccuracies?

Articulating why this is a problem worth fixing

How to successfully deliver a sustained benefit

3 Step Action PlanHow could you deliver these sales benefits in your own organisation?

34

1. Understand your root causesThe drivers of inventory record inaccuracies will vary from retailer to retailer, so it is important to understand your unique challenges.

Identify the contributors to inventory record inaccuracies in your retailer, for example:• How do you alter stock records?• How often do these processes happen?• How likely are they to cause inaccuracies?• What is the average size of these inaccuracies?• Are they positive or negative?

Once you have identified the major drivers then it may help categorize these:• Inaccuracies caused by upstream processes e.g. delivery accuracy, invoicing errors• Deliberate inaccuracies e.g. automated counts• Avoidable inaccuracies e.g. manual adjustment errors, poor replenishment• Unavoidable inaccuracies e.g. shrinkage

35

2. Validating your opportunityThere are many ways you could validate the size of the prize attached to improving inventory record accuracy in your organisation.

Minimum:

• Benchmarking against the retailers in the study. Use your existing inventory count data to measure your own inventory record inaccuracy, and compare with the results achieved here.

• Evaluate the cost of inventory counts in your retailer. What is the cost of these as a % of sales? What uplift would you need to achieve a return on investment?

• Does your organisation already have measures to approximate the value of missed sales? Do these align with the sales opportunity identified by the study?

Optimum:

• Repeat the experiment! If you don’t want to invest in a whole-store experiment, then consider tailoring it to the areas where you think have the most opportunity

36

3. Invest in accuracy, not just countingWhen defining a strategy to tackle inventory record inaccuracies, be clear on your long term vision, and make sure the changes are sustainable.

• Look to change the language used in your organisation: investments in inventory record accuracy are a tool to drive sales. This will help to break the perception of stock counts being a boring, repetitive and (sometimes) pointless task.

• Support this with data & insights. Instead of a one-off measurement, should inventory record inaccuracy be used as a business KPI to ensure it remains on the agenda?

• Initially consider how to tackle the biggest contributors with the minimum investment. This targets the low hanging fruit and builds confidence in your strategy.

• A count may not always be the answer – the improvement to inventory record accuracy will be temporary unless you fix the root cause. A count is the solution if the root cause if unknown, or if it is cheaper than fixing the cause!

37

Understandingyour root

causes

Validating your opportunity

Invest in accuracy, not just counting

What drives your inventory record inaccuracies?

Articulating why this is a problem worth fixing

How to successfully deliver a sustained benefit

3 Step Action PlanHow could you deliver these sales benefits in your own organisation?

38

Thank You.

Todays Webinar

Launch the Report – Academic Team

Retailer Response – Tesco

Questions Use Tab

Send to colinmpeacock@ecr-shrink-group.com

39

- 40 -

Appendices

APPENDICES

- 41 -

Todays Webinar

Launch the Report – Academic Team

Retailer Response – Tesco

Questions

Use Tab

Send to colinmpeacock@ecr-shrink-group.com

- 42 -

% of incorrect inventory records by retailer

- 43 -

Direction of the stock record discrepancy by retailer

- 44 -

Classification of SKUs by turnover and discrepancy contribution (Fashion)

- 45 -

% of high discrepancy SKUs at the retailers

- 46 -

Discrepancy contribution of different product categories (retailer c)

- 47 -

Inventory record inaccuracies and hand adjustments

- 48 -

Average percentage sales increase per product category (retailer c)