BI Suite

Owned by Camille Ripoull
Last updated: Jun 02, 2023 by Former user (Deleted)
12 min read

Introduction

OneStock has partnered with Sisense, world renowned business intelligence software solution to leverage the data managed in Onestock and extract the maximum value.

All analytics are available in the OneStock backoffice. As well, there is a number of out of the box features to help you get the best understanding of the data, as dimensions drill downs, key indicators, and much more.

 

Two types of dashboards are available :

  • The standard analytics, which offers you basic key indicators helping you monitor your daily business. Those analytics are available for everyone in the Analytics section in the backoffice.

  • The BI Suite, a set of out-of-the-box dashboards that make the most of this data. The BI Suite is a OneStock module and a specific access must be requested.

Overview

The BI Suite is a set of out-of-the-box dashboards grouped by pillars.

  • Order fulfilment

  • Stock locations

  • Items fulfilment - coming soon

  • Delivery promise - coming soon

  • Stocks - coming soon

Dashboards are accessible within OneStock backoffice, and can also be exported to multiple formats. We advise to export as an image for the whole dashboard.

 

The BI Suite dashboards aims to give a strategic vision of the business. It allows to explore various KPIs and their evolution through several axes (sales channels, order type, delivery country, fulfilment origin, etc).

 

Disclaimer:

  • New topics and dashboards will be added in the coming months.

  • The data is only refreshed daily (aims to be refreshed several time a day)

  • Administration functionnalities are not activated (custom report design, emails automation, alerts…)

Data source

Data is extracted from OneStock orders collections and represents the current situation of all orders.

After extraction, data is processed and aggregated. During processing, all order and line item custom states are mapped to standard states. This allows the generation of standard dashboards for all our clients. The custom states have be shown in some dashboards and can be used within the drill down functionality when needed.

Finally, data is imported into Sisense which stores it in a fast performing data structure called Elastic Cube.

 

Interface overview

Filters

By filtering we can reduce or broden the scope of data to be taken into account. The main filters are :

  • Site : Allows selecting one or more sites. When visualising analytics with an external account - not onestock - site selection is limited to only one.

  • Sales channel : Allows selecting one or more sales channels. When visualising analytics with an external account - not onestock - sales channel selection are limited given the users sales channel access rights.

  • Date : Allows selecting a period of time.

  • Currency : Allows changing the display currency. The conversion rate is the closing rate of the stat date, and the current rate for the current date. 

    • If viewing stats of before yesterday, yestarday and today, revenue conversion for stats of yesterday and before yesterday will be done with their corresponding closing rates and today's will be converted using the current rate. 

Example: changing currency

 

Tips: You can set any desired filter configuration as your default filters (for each report). Clicking on the ↺ restores filters to your stored default filters.

Field sub-selection

By clicking on a category name in a widget legend, you can hide the category in a graphic. It can help you to remove categories you’re not interested in or to isolate one specifically.

Drill down

All dashboard widgets support drill down by any dimension available in the source table. Main graphs have predefined suggested drill down paths.

Export

Exports can be done at two levels:

  • Widget export: By clicking on the three dots at the top of each widget, the widget can be exported. Supported formats are: csv, image and excel (only for pivot table widgets).

 

  • Dashboard export: By clicking on the three dots at the top of each dashboard the whole report can be exported.
    Supported formats are: pdf, image

Dashboards

You can find here the list of available dashboards and how they can help you leverage your business.

 

Orders & returns

Total orders

 

Global overview of the orders placed by the customers.

 

Objective: describe the order profile. Know when and what type of orders are placed on the web

  • How much revenue is generated during the period? How much has been processed? How much is left after returns?

  • What is my order trend?

  • What is my basket profile?

  • What delivery mode is preferred by my customers?

  • How are my various sales channels / countries performing?

  • What is the distribution of your orders per price range ?

 

Key KPIs: placed orders, placed revenue, processed revenue, basket profile

Repartition per date, delivery type, sales channel, delivery country

 

Date range: based on the order date. By default 30 days.

 

 

Orders in progress

 

Overview of the orders that have not yet been delivered to the customer

Objective: identify any order preparation struggling or orders remaining in a non final state

  • How much orders do I have left to prepare?

  • In how many days are my orders roughly processed?

  • Do I still have a lot of collectable orders stuck in the stores? In which ones? Do they apply the “no show” processes?

 

Key KPIs: orders to prepare, orders in progress

Repartition per date, state, delivery type, sales channel

 

Date range: based on the order date. By default, no limit.

 

Period comparison

 

Comparison tool to overlay two periods' KPIs

Objective: compare your activity during two different periods through main KPIs

  • How was our summer sales cancellation rate compare to the winter sales one?

  • How did our new orchestration rules impact our activity since their change?

 

Key KPIs: Basket profile, store contribution, cancellation rate, split rate, return rate, time to customer

 

Date range: Customisable

 

To compare two periods, select the first period to compare in the filter “Period 1” and the second one in the filter “Period 2”.

 

OIS Analysis

 

Overview of OIS orders

Objective: deep dive your OIS orders.

  • Where do I place the most orders in store?

  • What is my additionnal store to web revenue?

  • What is my basket profile compared to web?

  • Is my OIS mostly used for as endless aisle or for queue busting?

 

Key KPIs: count of orders, placed / net revenue, basket profile, immediate fulfilment versus delivery

Repartition per date, delivery type, sales channel, delivery country

 

Date range: based on the order date. By default, 30 days.

 

 

Return analysis

 

Overview of the return rate

Objective: understand when and where items are returned

  • What is my return rate? How it evolves?

  • What is the behaviour of my customers? (How many orders are partially / fully returned?)

  • Is there a difference between sales channel or delivery type?

 

Key KPIs: return rate, revenue loss, orders impacted by a return

Repartition per date, delivery type, sales channel

 

Date range: based on the order date. By default, 30 days.

 

 

 

Order fulfillment

Store contribution

 

Store contribution in the order fulfilment

Objective: understand the part of your business handled by the stores

  • What is the stores contribution in the processed revenue?

  • How does it evolve?

  • How much is involved the collection store for Click & Collect orders?

  • Who are my top stores?

 

Key KPIs: revenue, items processed

Repartition per origin (warehouse, store, withdrawal store), delivery type, sales channel

 

Date range: Based on the order date. By default, 30 days. In this dashboard the processed date is not taken into account.

 

Split analysis

 

Overview of orders split

Objective: understand how much split are done by the orchestration and how many orders require several shipped parcels

  • How performant is my orchestration? (How many orders are split between several sources?)

  • How much orders require more than 2 or 3 sources?

  • How much shipping costs will be induced by splits? (How many shipped parcel do I need per order?)

  • What is the impact of the multi-parcel option (several packages in a store / warehouse to serve an order)?

  • How many shipments do I have per order price range?

 

Key KPIs: multi-source split (several sources needed to fulfill an order), multi-shipment split (several shipping sources needed), shipped parcels per order, sources per order

Repartition per date, sales channel, delivery type

 

Date range: based on the order date. By default, 30 days.

 

Split analysis refers to three main concepts: sources, shipments and shipped parcels. Let's explain them here to better appreciate the KPIs referring to them.

A source is a stock location from which items have been fulfilled. If an order has multiple sources, it’s consider as split, for example : a warehouse and a store or two differents stores.

A shipment corresponds to an order travel between a stock location and the destination. Therefore Click & Collect items prepared in the withdrawal store have no shipment associated. The shipment only takes in consideration the travel and not the volume of parcels sent. If two parcels are sent from a stock location A to the customer because the goods volume can’t stand in a single parcel, it will result in one shipment.

A shipped parcel corresponds to the physical box that the customer receives, if it has been shipped to him. Therefore Click & Collect items prepared in the withdrawal store have no shipped parcel associated. The difference with the shipments is that if a store packs an order in several parcels, there would be one shipment and several shipped parcels.

 

Carriers

 

Overview of carriers

Objective: understand your carriers activity

  • How many parcels were shipped with each carrier last month from my stores?

  • What is the average goods price in a parcel shipped from store versus warehouse?

  • What carrier is mostly used in a country?

 

Key KPIs: parcels per carrier, items price per parcel, parcels distribution per origin type

Repartition per date, delivery type, sales channel

 

Date range: based on the order date. By default, 30 days.

 

 

Time to customer

 

Overview of fulfilment duration

Objective: have a rough estimate of the time a customer is waiting for its order (to be shipped for home delivery or collected for click & collect and reserve & collect)

  • How long does it takes to ship an order?

  • Is it faster from the warehouse or my stores?

  • How fast are my customer collecting an order when it is directly prepared in the collection store?

 

Key KPIs: Time to ship, time to customer, time per order delivery, time per fulfilment type, time per country

 

Date range: based on the order date. By default, 30 days.

 

Time notion are differents depending of the order delivery :

For home delivery, time to ship calculation is done as follow: days between the creation of the order and the shipment of the last item.

For Click & Collect and Reserve & Collect, time to collect calculation is done as follow: days between the creation of the order and the collection of the order.

 

 

Cancellations

Cancellation analysis

 

Overview of the cancellation rate

Objective:  understand how much items are cancelled

  • What is my cancellation rate? How it evolves?

  • What is the impact for my customers? (How many orders are partially / fully cancelled?)

  • Is there a difference between sales channel or delivery type?

 

Key KPIs: cancellation rate, revenue loss, orders impacted by a cancellation

Repartition per date, delivery type, sales channel

 

Date range: based on the order date. By default, 30 days.

 

Cancellation reasons

 

Deepdive the cancellation reasons

Objective:  understand why, where and when items are cancelled

  • What are my main cancellation reasons? How it evolves?

  • Where should I put my effort to decrease my revenue loss and increase my customer satisfaction?

  • How long it takes me to cancel an order? What is the impact for my customers?

  • Is there a difference between sales channel or delivery type?

 

Key KPIs: cancellation reasons, revenue loss, cancellation delay

Repartition per date, delivery type, sales channel

 

Date range: based on the order date. By default, 30 days.

 

 

Stock locations

Current stock locations configuration

 

Overview of your stock locations and the OneStock modules activated

Objective: verify the current configuration of the stock locations

  • How many stores are activated for each module? for each country?

  • Is there any odd configuration?

 

Key KPIs: Repartition per country, module, priority, localisation on a map

 

Date range: No date. The current configuration is shown.

 

Competitive allocation

 

Overview of the competitive allocation

Objective:  understand the way stores are claiming orders

  • How reliable are my stores when they have orders to claim?

  • How long it takes for an order to be claimed?

  • How many stores are competing to claim an order?

  • Who are my champions? Who is behind?

  • Do I need to review my in-store adoption processes?

 

Key KPIs: orders claimed versus candidate, time to claim, candidate duration, candidate reliability *

Overall and per store values.

 

* The candidate reliability reflects the fact that a stock location has not missed any order sitting in the claim page for a long time.

 

Date range: based on the order date. By default, 30 days.

 

Competitive allocation comparison

 

Comparison tool to overlay two groups of stock locations and two periods' KPIs

Objective: compare your competitive allocation amongst two different groups of stock locations and during two different periods through main KPIs

  • How are my French stores performing against my German ones?

  • How does my new in-store process impact my results?

 

Key KPIs: orders claimed versus candidate, time to claim, candidate duration, candidate reliability

 

Date range: Customisable

 

Performance: Ship from store

 

Overview of the ship from store process

Objective:  understand the way stores are preparing SFS orders

  • How reliable are my stores when they have orders to prepare in Ship From Store?

  • What percentage of items are packed, dispatched?

  • How often items are unclaimed / unavailable?

  • How long it takes for each step of the process?

  • Who are my champions? Who is behind?

  • Do I need to review my in-store adoption processes?

 

Key KPIs: volume and revenue claimed versus packed/dispatched/unclaimed/unavailable, time to claim/pack/dispatch

Overall and per store values.

 

Date range: based on the order candidate date in the store. By default, 30 days.

 

Performance: Ship From Store comparison

 

Comparison tool to overlay two groups of stock locations and two periods' KPIs

Objective: compare your Ship From Store process amongst two different groups of stock locations and during two different periods through main KPIs

  • How are my French stores performing against my German ones?

  • How does my new in-store process impact my results?

 

Key KPIs: volume, revenue and time per step of the process

 

Date range: Customisable

 

Performance: Click & Collect

 

Overview of the click & collect process

Objective:  understand the way stores are handling CKC orders in the pickup store

  • How reliable are my stores when they have orders to bag in Click & Collect?

  • What percentage of items are bagged? unavailable ?

  • How went the reception of items coming from the warehouse or another store? What percentage is issued?

  • How long it takes for each step of the process?

  • Who are my champions? Who is behind?

  • Do I need to review my in-store adoption processes?

 

Key KPIs: volume, revenue and time for the bag process, the reception process and the collection process

Overall and per store values.

 

Date range: based on the order candidate date in the store. By default, 30 days.

 

Performance: Click & Collect comparison

 

Comparison tool to overlay two groups of stock locations and two periods' KPIs

Objective: compare your Click & Collect process amongst two different groups of stock locations and during two different periods through main KPIs

  • How are my French stores performing against my German ones?

  • How does my new in-store process impact my results?

 

Key KPIs: volume, revenue and time per step of the process

 

Date range: Customisable

 

Performance: Reserve & Collect

 

Overview of the reserve & collect process

Objective:  understand the way stores are handling R&C orders in the pickup store

  • How reliable are my stores when they have orders to prepare in Reserve & Collect?

  • What percentage of items are reserved?

  • Why items are not reserved? Should I let more time for my store to prepare them? Are my stocks accurate?

  • What is my No Show rate?

  • How long it takes for each step of the process?

  • Who are my champions? Who is behind?

  • Do I need to review my in-store adoption processes?

 

Key KPIs: volume, revenue and time for the reserve process and the collection process, cancellation reasons

Overall and per store values.

 

Date range: based on the order candidate date in the store. By default, 30 days.

 

Performance: Reserve & Collect comparison

 

Comparison tool to overlay two groups of stock locations and two periods' KPIs

Objective: compare your Reserve & Collect process amongst two different groups of stock locations and during two different periods through main KPIs

  • How are my French stores performing against my German ones?

  • How does my new in-store process impact my results?

 

Key KPIs: volume, revenue and time per step of the process, cancellation reasons

 

Date range: Customisable

 

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