- October 14, 2019
- Posted by: Ramkumar
- Category: Mergers And Acquisitions
Artificial intelligence, AI, has broken information silos
Artificial Intelligence, AI, has broken information silos. Information silos are one of the major challenges in large organizations and results in major internal issues. In most of the big companies, the left hand does not know what the right hand is doing. Most of the employees would be reinventing the wheel as collaboration and sharing learnings are very rarely evident in big companies.
Information silos are not only an internal issue as silos exist externally too.Companies that work together as partners or in JV also face the same challenges.They often don’t have full visibility or clarity of their partnership.Lack of information visibility often trigger an “us versus them” mindset between companies which often results in missed opportunities. The lack of sharing information creates a trust deficit and these issues become difficult to resolve.
How Artificial intelligence, AI, has broken Information silos
- Emergence of new tools have encouraged companies to become open to using AI which can help in breaking down information silos.
- New tools powered by Artificial intelligence, Machine learning and advanced analytics can transform ways in which employees collaborate, communicate and coordinate their workflows.
- This can provide huge benefits in improving efficiency and increase synchronization between different teams and businesses.
Artificial intelligence, AI, use cases in Logistics
- Logistics companies leverage AI to improve Operational efficiency and provide better outcomes. Companies like UPS use Network Planning Tool to integrate its pickup and delivery system. A customer package is categorized by destination, zipcode, weight and volume. The package is provided with a barcode label, then scanned and loaded in the conveyor belt for delivery.
- The packages are organized by destination, type and by the time of the year.For instance, pharmaceuticals and drugs are not routed via a desert as extreme hot temperatures can affect its potency.It can also reroute packages intelligently based on potential for congestion during peak seasons.
- The uniqueness in this tool lies in the human Machine collaboration which empowers engineers to take better decisions.For instance, when packages are rerouted, the engineers receive an app notification about the revised plan.The engineer evaluates the revised plan and can either approve or reject the rerouting of the package. This decision by the engineers get updated in the app.The app learns from human oversight and get smarter about routing plans in the future. The app also has an algorithm built which checks the engineer’s choice to ensure that the choice gives the desired results.
- The above model not only improves Operational efficiency by saving time and money, but also improves customer satisfaction.
Artificial intelligence, AI, can improve Employee Coordination
- AI can also be used to improve employee coordination and communication.Companies leverage AI to improve the disconnect between their sales and marketing departments.
- Tools are built to increase engagement and cross functional communication between sales and marketing to finalize which of their marketing campaigns will or will not work. This is done by capturing real time insights on the impact of meetings and selling opportunities generated via marketing campaigns.This creates more transparency on the sales pipeline opportunities enabled by marketing and also instills accountability on the sales reps to follow up on the leads.
- This integration between sales and marketing team would help companies recover marketing pipeline that is being wasted due to lack of accountability on sales team to follow up on the marketing pipeline. This also gives business leaders a clear picture of their sales funnel, understand constraints across businesses and facilitates collaboration that can transform business culture in the long term.
Limitations of Artificial intelligence, AI,
- AI has it’s own limitations and challenges.Some of them include restricted training data, lack of understanding of data and hidden biases transferred from humans to machines.
- Nevertheless AI provides promise to help create connected and coordinated systems that fosters collaboration and sharing information both within and outside the organization.
- The ultimate responsibility for breaking down information silos lies with people.