Neil Mackin has published a thoughtful article on these important pillars of digital transformation.

To these I would add that these are not all big ticket, long lead-time, complex projects. They are also relevant in many manual processes at the front-line. The combining of human brain power and these technologies, sometimes called augmented intelligence, will make a big difference to digitise manual "black holes". 

Take the impact on insurance companies and apply this across other sectors:-

    • Immediate world class online customer service to rival the best online experience
        1. Empower customers to manage their own transactions
        2. Link every participant to a claim via one digital record
        3. Provide the ability to utilise lower cost “Specialist Crowd” services
        4. See large claims live from site to take day one decisions and actively manage suppliers
        5. Ability to switch seamlessly to a distributed working model  e.g. clients with 100’s of staff working from home via internet)
        6. No major IT spend to achieve change
      • Control/Reduction of Indemnity spend
      • See every claim thus making a better decision
      • Cycle time significantly reduced = lower claim cost
      • A compete digital strategy will add 20% to the bottom line result
      • Anti-Fraud -If customers have to show you every claim then the potential fraudsters self-select themselves out of the new process
      • Comprehensive Data/Analytics system with proven anti-fraud capability with the ability to turn all text searchable.. which has a significant effect as 90% of an Insurer’s information is locked up in text

    I like Neil Mackin's end quote:- 

    "Roll on 2017, with all the data it will bring – new streams of machine generated data from IoT and user generated data from sensors. There’s a growing shift in consumer expectations of how smart computer bases service ought to be … what do you mean you can’t predict what I want for Christmas next year?” "

    • LikeReflections on Analytics, Machine Learning and AI at Year End
    • Comment
    • ShareShare Reflections on Analytics, Machine Learning and AI at Year End