IKEA’s vision is ‘to create a better everyday life for many people’. Owned by the INGKA Group, the famed retailer has built a solid reputation for doing just that – providing beautifully designed yet practical and affordable furniture and homeware options to its 657 million customers who visit its 390 stores, across 32 countries.
However, the Group is rethinking its approach, understanding that the world is changing and so are people’s buying habits. While traditional stores in big cities still do well, INGKA is also moving into other form factors and ‘getting closer’ to its customers through digital tools.
For example, to highlight the changing times, the IKEA website had 4.3 billion visits and 23.9 million downloads of the IKEA app.
As part of this change, INGKA (IKEA) is implementing a new SAP system for its finance and purchasing functions, with the aim of standardizing its systems as much as possible. However, the company is also looking for the ‘perfect order’ and is trying to streamline its processes globally so that customers have the best possible experience when shopping at an IKEA store.
This doesn’t come without its challenges, however. And INGKA is using Celonis’ process mining platform to help with this transformation program. Speaking at a recent event for Celonis users, Tim Hills, Data and Process Insights Development Manager at INGKA Group, said:
For those of us who work with process modeling, this means that the types of processes and ways of serving customers will be very different.
One of the main contributing factors to the work we are doing now was a SAP implementation. But since we were using SAP for finance and purchasing, we still kept our legacy scenario and tried to connect it with SAP.
Bringing data from a fragmented retail landscape to something as standardized as SAP is a bit of a challenge.
A number of things lined up for INGKA to proceed with using Celonis. On the one hand, Hills took a course during the COVID-19 pandemic focused on process mining and data science, which left him wondering how this could be applied to IKEA retail. Secondly, IKEA in Spain was already using Celonis to work and trying to improve their ways of working – specifically thinking about continuous improvement and development. Hill said:
With the implementation of SAP, the challenges we thought we had came to fruition. This is where we are implementing Celonis. What we want to do is bring together global momentum, local attraction and individual energy.
What makes a perfect order?
Currently, INGKA has around 500 million events within Celonis and nearly 50 million requests, to help them better understand what is working and what is not. Hill said:
We brought the end-to-end sales order, from when the customer says what he wants, until we respond.
Why do we want to do this? We want to make every decision better. We want to leverage process and data insights into our operation to ensure that the changes we want to make are optimally made and are carried out optimally. Not just the insights, but driving those insights into operations.
In any company our size, there are an almost infinite number of ways we can become better. How do we articulate and how do we decide what the right things are next? It’s not just about who can weave the best plot, but who has the best data?
Knowing this and using Celonis to understand what makes the ‘perfect order’ will help your company standardize on SAP. Hill added:
Standardization acts as a multiplier, because whenever we’re doing change management, which comes across as a big deal — if you have 30 different markets at 30 different starting points, making that change can be quite challenging.
In turn, INGKA created a laboratory of process and data insights: a center of excellence for Celonis. This laboratory was created to generate insights and help achieve operational excellence, but also to identify the best development opportunities.
This does not mean that it is working in isolation. The lab coordinates approximately 1,000 stakeholders across the Group, including the sales and order management steering group, individual markets, subject matter experts, as well as senior global executives (eg the CFO). Hill added:
We’re in a digital world, so it’s impossible to forget all of our digital organizations – our product teams, enterprise architecture, data governance. And so the group that we want to provide feedback to is the team that’s been looking after this SAP project, to make sure that we’re enabling this in the right way.
a working laboratory
Hill explained how INGKA and IKEA in general are thinking about process mining, specifically as it relates to creating the ‘perfect order’ for customers. He said:
We start with the data, make sure we get the data from our source systems, understand it and structure it the right way. We have a myriad of homegrown systems, some that we buy off the shelf and then tinker with; therefore very few are standard connectors. So we have a lot of data discovery and exploration to do.
Next, Hill and his team focus on engagement, how they engage with markets and businesses. He said:
We go to the countries and say: what have you already committed to working on? How can we help speed this up? How can we help optimize? Because then engagement is easier. It’s all about communication.
Then we do a little homework. We have this core team within our CoE, where we have the technical team that takes care of the data side, but we also have some business experts who have a lot of experience in the business.
They engage with countries and show them the art of the possible, that’s how we can find synergies between what we have and what they need.
Part of the process also involves workshops, where INGKA aims to identify not just the big use cases, but root causes and process challenges, as well as countermeasures. It is an interactive process, which leads to proposed solutions and possible corrections. Hill added:
To get value, we need to be able to measure where we are, measure where we want to be, and figure out how to get there. The measure we’re looking at is our perfect order. And so the metric we’re looking at is our ‘perfect order’.
Perfect ordering is perfectly receiving and fulfilling the customer’s order – receiving the order correctly, allocating the inventory, delivering the product, with an accurate invoice. We have internal and external benchmarking.
An example from the UK
Hill provided an example of how IKEA stores are using Celonis to improve their order-to-pay processes. One of the first regions he focused on was the UK and Ireland, which were also two of the pilot countries for his SAP project – which allowed for “synergies”.
Analyzing the data, INGKA found that IKEA in the UK and Ireland had a very high failed charge rate when customers ordered products online for in-store pickup. While the customer pays online, he may arrive at the store and find that the product is not suitable for him, or it may never show up, or there may be a problem with the product, which means he will be refunded.
Whatever the scenario, the work of preparing the product for collection is time-consuming and, therefore, reducing waste in this area could be an opportunity for the Group. HIll said:
When we look at the various factors that contribute to this click and receive opt-out, we can see that the UK had more opportunities than all other countries combined.
But when we looked at the data further, we could see that we had some countries with similar volumes to the UK but lower churn rates.
So it’s about trying to understand the correlative and causal effects on the end-to-end flow, and then see what’s causing the problem? How can we avoid it in the first place?
Using Celonis and analyzing the data, the results were fascinating. INGKA found that by reducing the time available for customers to pick up their products, there was a causal effect on the collection rate. He said:
In the tools we have you can configure the collection window between 1 and 12 hours. One of the things we could see is a causal effect between the length of these windows and the churn rate.
We did some testing in the UK to reduce these booking windows and it showed that for every hour we reduced these booking windows, the cancellation rate decreased by 7%.