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The greatest business value of automation is not so much in saving labour as in saving the sort of boring, repetitive and yet complicated labour that humans tend to do worst – either growing bored and rebellious or else performing the actions in a trance state where human errors multiply and often lead to long term problems. The theory is that automation should free up human resources to enable us to use our real intelligence on more important core work.
An area ripe for disruption in the space, due to advances in security and prevalence of cloud solutions, is renewals. Business schools across the world, have taught a whole generation of managers that outsourcing noncore functions to specialist providers is the correct commercial behaviour. The allure of fixing an issue by managing an external provider to fix that problem with the assurance their specialty will deliver a “sugar hit” to the business bottom line, seems intoxicating and yet the process of outsourcing renewals quoting and management has failed to deliver sustainable and significant improvement to the technology industry.
Having outsourced the problem to a dedicated provider, those external agents require training, not just in a given client’s technology and nomenclature, but also to understand their often very complex pricing logic (price discounts, partner discounts, rebate application, bundling) and this can take a long time – often weeks of dedicated training, with resources removed from productive revenue generating work – a cost that the client has to pay.
With training now complete and fully competent in quoting, understanding the pricing logic of their client, there is a ramp time to ensure maximum productivity. Putting that learned knowledge into practice typically takes these providers 90-120 days before they are taking the burden on effectively - quotes take time to get right, revisions take time to make and learn from. And then there is a human quote error issue - 7-11% of all human- generated quotes have an error – which affects revenues and takes the shine off that balance sheet “sugar hit” for the client.
2019 has seen considerable uptake of automation to solve this problem. I see this as a major trend for 2020. Added to this, as the data becomes machine learning friendly we will see the rise of automation and machine learning across the cloud. The next step in this process is Artificial Intelligence but for that to really start gaining headway, there must be enough “machine learning ready” data. Companies that adopt the best of today’s automated, smart solutions are indeed taking a significant step along the path towards real AI, and in my opinion 2020 is going to be the year of automation, and perhaps 2021 will be that of AI.
