IT sourcing models are changing due to Artificial Intelligence?
When companies implement an Intelligent Automation platform which is supported with AI and ML, how will this impact the IT sourcing models?
The expectation is that the global sourcing market will change faster than expected, but in which direction? In most Western countries, the market is mature. Firms selected their preferred suppliers, they outsourced their activities and start optimizing their contracts. Recently there is a new kid on the block which is called ‘Intelligent Automation’ (IA), supported with Artificial Intelligence and Machine Learning, it’s able to give a push on the productivity improvement and quality of work. But does this impact the sourcing model?
Overview sourcing models
In the market the following models are commonly used:
Explanation of each model
In sourcing: the company will do the work by itself without support of a third party. Practice shows that there are limited service levels in place and there is no shared risk with the supplier. The knowledge, intellectual property and responsibility stays within the firm.
Body shop: several roles are back filled by one or more vendors. Also in this model (just like in sourcing) tools and processes are used and managed by the company itself. Service levels are limited and include a commitment on how fast a CV is submitted (for example). Usually no commitment on the quality of work and a limited shared risk. Companies use this as they want to staff — for example — scarce knowledge from the market and be in control on operational level.
Together: sourcing model where the company and 3rd party jointly work in the daily operation. Tools and process of 3rd party can be used together with client tools and processes. Vendor can give a commitment on cost savings and the client has a shared risk and responsibility with the vendor.
Outsource: the firm hands over the responsibility to the vendor, which will use his people, tools and processes for the execution of the work. Client is involved on tactical/ strategic level and the 3rd party will take over the risk and delivers the work according agreed service levels and savings.
Depending on the goals of the firm one of the four sourcing models which are described above will be chosen. This is usually based on one or more of the following points:
- the excepted cost reduction
- quality of the work
- flexibility of the work force
For example: a company is shifting to a new IT environment and has still some legacy applications that need to be maintained for several years. While the workforce need to focus to the new landscape, they have the risk of losing the knowledge for maintaining the legacy applications. Using the body shop model, they could hire resources from the market to mitigate this risk and get internal resources available for the new IT environment.
With the use of Artificial Intelligence companies can analyze and automate their Business and IT processes. The focus of this article is on the IT.
As explained in the beginning of the article the first two models ‘in sourcing’ and ‘body shop’ are supported with tools and processes from the client. When the productivity improvement and quality of work should need to be increased with Intelligent Automation, this will be handled by the client.
For the third and fourth model, ‘together’ and ‘outsource’, the tools and process are used from the vendor. To achieve the required automation level, it becomes even more important which vendor the firm has selected for their current work and what type of contract is signed. Has the vendor experience with the implementation and use of an Intelligent Automation platform to increase the productivity and quality of his work. When he has the capability, does he has also the incentive to implement it? When he get paid per FTE the drive to implement Intelligent Automation will be low.
The sourcing model will not change due to Artificial Intelligence; the question will be who does the execution of it, as the approach will change (less labor, more intelligent software).
Intelligent Automation will become a part of the strategy of the IT department. When they are also responsible for the processes and tools they need to implement also an intelligent automation platform to achieve a higher productivity improvement and quality. When they outsourced their IT delivery, it’s important that their vendor has a platform which can be implemented and has an incentive to execute this, otherwise both parties will not gain the benefit of it.
What might temporize the rise of Intelligent Automation in the IT domain is:
- Applicable for all sourcing models: when the team is small the scale and investment that is required to implement Intelligent Automation could be to high to earn back the investment;
- Sourcing model ‘together’ and ‘outsource’: Has the vendor experience with an Intelligent Automation platform and do both parties (client as well as vendor) benefit from the implementation, otherwise the vendor will not be eager to implement it;
- Sourcing model ‘in sourcing’ and ‘body shop’: not many companies have experience with this type of platforms, when they want to implement a platform they might need support from a Third Party Adviser for the selection and implementation of the platform. As it’s a new market this knowledge is scarce and they might have a problem to find support.