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Change management in an AI-led procurement world

By Meenakshi Nilakantan
In Change Management
Apr 28th, 2020
0 Comments
1045 Views

Change is the only constant, as they say. Hence change management has been very crucial in this AI-led procurement world.

The Artificial Intelligence (AI) is likely to impact around 47% of the American workforce by 2030s, according to an Oxford study [1].

The World Economic Forum states that though automation will displace 75 million jobs, it will also generate 133 million new ones worldwide by 2022 [1]. 

Additionally, 20% of organizations from a global survey conducted by PwC had identified AI as a critical implementation goal of 2019 [2].

What does that mean for organizations and employees? It means a great opportunity for procurement teams to concentrate on strategic tasks. 

But the journey towards a holistic AI implementation is fraught with a lot of challenges. These challenges could be in the form of people, processes, or systems. They need to be align together to reap maximum benefits. That is where change management comes into play.

The importance of change management

Change management, which promises a complete overhaul of a company’s core functioning methodology, requires changes in strategy, attitude, work culture, processes, and alignment of goals. Companies are pretty good when it comes to selecting AI as a key strategy. 

There are many struggles in getting everybody in the organization comfortable enough to use the technology to their advantage.

A well laid out change management plan will ensure the successful implementation of AI and lead to smoother operations. It will also act as a fool-proof plan of helping companies reap the maximum benefits of a given technology. A lot of the manual tasks like invoice processing, supplier evaluation, and spend classification can be automated without any hassles.

The need for change management

Imagine a scenario where the top management of your organization has decided to implement AI. That is excellent news. Take a quick pulse check, and you will realize that not everyone is so gung ho after all. 

The guy from the Finance team who processes invoices quite efficiently might be afraid of losing his job. The old-timer from the IT team might think this is a waste of time since “things have always been this way.” The lady who looks at contracts day in and day out might be scared of this “new technology beast.” 

Somebody else might be concerned about the nitty-gritty of using the technology. Fear of change, aversion to new technology, lack of skills, limited knowledge, or an inability to have a long-term view could be multiple reasons for not implementing a given technology most judiciously.

Best practices in change management

As discussed earlier, getting a sign-off for technology is one thing, and getting different team members to implement it in the best way possible is a different ball game. Below are some of the strategies you can apply to ensure a smooth transition:

Include the entire team and not just the top management: 

  • A true transformation is impossible unless everybody benefits from it. And including everyone from the team in the execution plan is critical here. Educate people and ensure that the information percolates top down. 
  • This step will also help employees prevent misconceptions, bust popular myths, and eliminate fear to a certain degree. They resolve the issues as time passes. People are also comfortable with the given technology. 
  • Use this opportunity to show benefits relevant to different groups and use examples wherever possible to make it easier to understand and absorb information. An example could be explaining how dynamic discounting can is leveraged, leaving scope for finance teams to improve supplier relations. Let them ask questions. Also, provide manuals and guides for teams to go through.

Understand and propagate the right knowledge of technology: 

  • It is a good idea to take a top-down approach. Understanding that technology is not a blanket solution for every problem under the sun would be a good starting point. 
  • Clearly listing down all the possibilities of AI will help keep everyone on the same page. This is where workshops, internal meetings, multi-way communication channels across different levels, and regular feedbacks help. 
  • It would also serve as a chance to dispel any misconceptions or fear that people might have. For instance, people dealing with day to day tasks like reviewing long contracts or processing invoices manually might fear job losses due to automation. 
  • But a quick discussion about real-life cases where automation has helped teams focus on applying data insights for better decision-making and strategies will increase team confidence.

Make good use of reality-driven scenarios:  

  • The best way to make sure everyone gets included in the AI journey is by considering everyone’s needs. This would make the larger team feel included and part of the change process and increase the number of use cases that get covered for maximum testing and minimum future errors. 
  • One good starting point could also be looking at smaller, more pertinent issues so that the basics are ironed out first before moving on to more complicated cases.
  • A large company with a more diverse set of suppliers might be able to onboard the suppliers with much more clarity by looking at a company of a similar scale. Likewise, relevant business rules and approval workflows can be set up depending on previous case studies.  

Leverage expert opinion: 

  • It would be a good idea to take help from a consultant/AI expert who can help teams of different sizes with relevant real-life examples. They create new use cases and prioritize to ensure that every issue is covered.
  • It can also help to have an internal AI champ who knows the technology a little better than the others. Also, communicating in a less tech-savvy way when talking to non-tech teams is a handy skill. 
  • For example, explaining how much time gets saved through a guided procurement system is, of course, a good point to highlight, but it would make a lot more sense also to mention the different strategic activities surrounding data-backed decision making, better negotiation tactics and improved supplier relations that can be taken up by the team now that their time will be free.

Plan transitions in a phased-out manner: 

  • Look at slower releases and have clear milestones (think onboarding suppliers in batches for smoother transitions for all stakeholders) to move successfully from one stage to the next. 
  • Creating a training plan in the form of in-person meetups, guides, workshops, etc. focusing on regular feedback would help ease out the process. People are provided with trial versions and different use cases so that testing is done comfortably.
  • Network with people to get their views and understanding, so training and transition plans can be enhanced further.

Don’t forget your customers: 

  • In the midst of all the hullabaloo, do not forget to let your customers know your plan. Since they will also benefit from the new technology via faster invoice approvals, swifter payments, smarter contracts, and better negotiations, they will be more than happy to pitch in with their ideas and views. 
  • Privacy and security concerns will abound, and questions about the actual business impact will be asked, too, so be prepared to address them collaboratively.
  • AI is a step ahead in any business game. But no technology will be impactful if different stakeholders cannot use it to their advantage. Getting employees to know the various possibilities, benefits, and limitations is a good starting point. But it is also equally essential to smoothen out the transition process so as not to overwhelm the people. 

Conclusion

Take advantage of expert opinions, best practices & real-life case studies to replicate success stories for yourself and your customers. Different people might want different things from technology. This is where collaboratively coming on the common ground makes all the difference.

Sources:

  1. Is AI Going To Be A Jobs Killer? New Reports About The Future Of Work
  2. 2019 AI Predictions

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