Videos
Ericsson’s strategic partnership for end-to-end integrated business planning
Insights
- Ericsson is implementing Integrated Business Planning to unify demand, supply, inventory, and S&OP on a single platform.
- AI and machine learning support forecasting, planning, and user enablement to reduce manual effort and improve decision speed.
- Combining Ericsson’s in-house models with SAP IBP improves forecast accuracy and planning quality.
- A strategic partnership with SAP and Infosys enables scalable, long-term supply chain transformation.
In this Infosys Knowledge Institute video, leaders from Ericsson and Infosys discuss Ericsson’s AI-enabled Integrated Business Planning transformation. Facing global complexity across products, markets, and regulations, Ericsson is moving from manual, fragmented planning to a unified SAP IBP platform. Through a strategic partnership with Infosys and SAP, Ericsson is improving forecast accuracy, modernizing planning processes, and laying the foundation for a more proactive and resilient supply chain.
Hans Hallgren:
I'm Hans Hallgren. I'm heading up supply chain management within Ericsson and supply at Ericsson.
Diego Moreno:
My name is Diego Moreno. I am the head of supply chain planning in Ericsson.
Kamish Mirza:
My name is Kamish Mirza. I am the for IBP transformation director on behalf of Group Supply.
Hans Hallgren:
We are operating and have customers in more than a couple of hundred countries and all the customers are unique in the way they're building their networks. That becomes a very big challenge for us to manage the complexity both from a product perspective but also from a customer perspective. And it's not only the way that they build their networks, it's also other type of regulations. And now lately we have geopolitics coming into play. It has not been there before in the scale that we see right now with tariffs coming in, countries requiring components not coming from specific countries and so on.
Diego Moreno:
The challenge for Ericsson is having an integrated view and having a very transparent view. So we are not that efficient when we are moving across the flow of business and operations planning. We have very good delivery, but it's very human driven and we are not that good on having data driven decisions with automated business rules.
Kamish Mirza:
The vision which we have for IBP transformation is essentially to integrate demand, supply, inventory, SNOP into one full-blown transformation system.
Hans Hallgren:
What I'm expecting now from us implementing integrated business planning is that we become more digitalized, more proactive rather than reactive and faster to execution.
Kamish Mirza:
When it comes to IBP, Ericsson in all honesty has been toying up with this idea for the last five years. And we have been trying to take decisions on make and buy. We decided to run our own legacy use cases, for lack of a better word. We tried to build a few use cases on AI.
Diego Moreno:
Ericsson, before going to Infosys and SAP, IBP, we develop in-house, a solution, that is using machine learning to help us to improve our demand forecasting process. It is mainly aiming to our market areas. So it is not value centrally like in my team, but is used to build the bottom up forecast. My personal expectation is that we will take the lessons learned while we and how we did in our in-house development,but we are not there yet to use machine learning as to replace this one.
Kamish Mirza:
We realized very quickly that for us to be the world leader, we need to look outside in. That's how the journey started to find the best partner for us to lead this transformation. We had two choices. to find a partner who could implement itself or find a software company and a partner who actually has capabilities in driving transformation. We chose the latter. SAP then was chosen as the choice of the software for IBP and after almost a year of thorough sourcing processes, we identified Infosys as a partner. The overall deployment was split into three phases. Phase number one, we call it as go live 1, which is focusing on demand. We just went live with demand 22nd of September.
Diego Moreno:
Go-live 1 we will have in our forecasting solution we have the input coming from our internal system and the input coming from SAP IBP. So then the people the forecaster is able to choose or to see which one is the ones that we should use. And my expectation is that SAP IBP, we will have a higher forecast accuracy than what we have done in-house.
Anna Runhellen:
We have done that as a part of this first phase. We have combined it with an in-house AI model. We are looking forward to explore the SAP AI portfolio coming. We have built machine learning in-house that we’re incorporating into IBP.
Yehia Seraj:
We're definitely using machine learning across the platform, right? We're using it in forecasting. We're also using it for the segregation of the structure keys. But we also started to look into and using assistance AI as a chatbot, which we have developed together with Infosys as well, or with the support of Infosys.
Kamish Mirza:
And now we are preparing for our second phase, which is Go-Live 2, which includes supply planning, inventory planning, essentially the main capabilities to deploy. Then the third phase, will be SNOP, SNOE, and then of course production planning and detailed scheduling.
Anna Runhellen:
So now we have deployed the first version, but that's just the first step, you know, in this long marathon that we are going to do as a company. And there is so much more to come.
