5 Steps To Let Machine Learning RECOMMEND Business Transformation

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Machine Learning Supply Chain Technology Uncategorized

When technology does what a human brain does either at the same level or better, then it almost appears magical. E.g.  Self Driving cars, Amazon Recommendation or Google search results. Now the same level of sophistication is expected in an enterprise such as yours and the technology is affordable to everyone and is here. The market is accelerating at a pace that we have not see in our 10 years of existence in the business and thanks to Cloud for this disruption. Are you ready for it?

At Pluto7, we get engaged with professional services related to some of the most complex topics on Cloud transformation, SaaS operations definition, Advanced analytics and more recently on Recommendation Engines using Machine learning. All of this is measured against one basic metric. “Did you make it easier, faster or better for our business”.  At a large enterprise, in a recent innovation project using advanced analytics, we reduced the time frame from 3 weeks to 5 minutes for complex work activity.  This appeared magical, but what we really did was followed some of the basic principles of understanding the depth of the business, data and the emerging technologies and driving innovation. Sounds obvious, but the key is the discipline. Below are the steps we recommend.

Here are some of the key steps we suggest to our customers.

Step 1: Acknowledge where you stand with analytics, people and process
  • Understanding the business process and how the Data is entered shows where the garbage originates
  • Understanding process and people behavior will reveal some surprises
  • Be realistic on the journey of transformation and not look for quick wins like asking for a good dashboard. It is like asking your doctor to give you a good health report of your body.
Step 2: Research on Advanced Analytics, Machine Learning and IoT
  • Continuous learning and seeking application of emerging technology is critical for transformation
  • Machine learning is all about letting the data define the business rules. E.g. top 10 recommended products
  • IoT now allows you to collect more inputs data to improve your KPI accuracy and drive newer insights
Step 3: Drive Digital Transformation of your most mundane manual tasks
  • Once you select the technology you want to try ( proof of Concept ), pick the low hanging fruit to test your theory.
  • The most benefit is usually seen in improving simple repetitive tasks E.g. 80% of time is spent in Data preparation for Analytics
  • Executive are looking for cost optimization or innovation and when you align that to digital transformation effort, you have a winner
Step 4: Product Recommendations with Machine Learning
  • Your Customers are now used to getting recommendations from Netflix, Amazon or Alibaba and more. They expect the same from you.
  • Machine learning is the path for recommendations  ( E.g. Product centric recommendation or customer centric ). At pluto7, we enable this in our own SaaS applications E.g. Planninginabox.comForecastinabox.com
  • Hire the right experts who understand the domain, analytics and Change management- This is not just about witting a program.
Step 5: Knowing Customer lifetime value of your existing/new customers helps to focus
  • Your customers are highly connected  ( Mobile, Social, Cloud ) and so must be your customer master data
  • Life time value of customer assessment is not just about historical data of what the customer bought but also the potential to buy in future. E.g. We solved this for a bank and it was interesting to show who their true high profit generating customers vs. traditional belief
  • Blend your sales and operations process and data to find the customer life time value.

 

CONCLUSION:

Bottom line with business transformation is that it is a journey.  Start the journey with the right set of skill sets, tools/platforms to support the skill to generate the business outcomes that take your company to the next level. There is no magic in data, but it is what you tell the machines and systems to do for you. The key is having the right method and approach to get the value out of all your investments. We have conducted over 50 workshops and always start with the bad news to give audience a reality check on any of the technologies and then show them the path to get to the good news.  What we will see in 2017 will be nothing close to the level of change we have seen since 2000 ( year when we saw mass adoption of internet ) and this will be led by Cloud  at a overall level and Machine Learning in specific cases.

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