Cloud Data Value Chain for a Resilient Supply Chain
Published on : Saturday 16-10-2021
When done right, data and analytics can become your competitive advantage, could be the differentiator, says Reena Sethy.
For many years, we have been hearing data is the new oil, data is like having a gold mine, et al; however very few organisations are able to empower all their users with the insights from data in these volatile times.
For instance, do you have a full view of your inventory, more importantly, the risks that could impact your supply chain – single sourced product, product sourced from pandemic hit regions, sustainable materials, etc? Are you able to visualise potential risks and do simulations with what if a risk does become a reality in your supply chain? Recently, we did see many disruptions such as Covid, the ship that was stuck in the middle of the Suez Canal for days, or the current global chip shortage, to name just a few.
So how do you make your supply chain resilient? The answer lies much beneath – you need to build your data value chain in such a way that there are proactive insights across your supply chain, helping you take swift actions.
Hence, it’s imperative that you relook at your data and analytics landscape and prepare for the changed times. There are three ingredients for the foundation of your analytics strategy – Ample, Accurate and Accessible.
Foundation of your analytics strategy:
a. Ample – First and foremost, there is no value, if there is not enough data for users to derive any useful insights.
b. Accurate – According to Andrew Ng, it’s not so much about Big Data, it’s more about Good Data
c. Accessible – And what use is it, even though there is ample quality data, if business users can’t access it with ease and understand it to have the insights in a timely manner!
Bottomline: as CIOs/CTOs, your data and analytics strategy should be able to address these 3 aspects together, so your end users are able to tell stories with their data in their daily work.
In the past one year, more and more businesses are pushed into operating in remote ‘everything online’ mode, whereas their data infrastructure was probably designed long back. This is no longer sufficient, and if continued for even longer could be a sure recipe to go out of business.
And such remote and mostly online set up is also generating very diverse and unstructured data from different sources than before.
Hence, you have to set up your data in such a way that the end users can perform self-service analysis and derive insights themselves. The platform should be modern and use technology such as Artificial Intelligence/Machine Learning and have the ability to alert the end users on their mobile devices, so they can act quickly.
So, what can you do to provide such quick actionable intelligence to your information workers?
If you haven’t started the cloud journey, think of everything that can go on cloud. With cloud you can start small, fail earlier, and get to experiment.
Many organisations have started having the application layer on cloud since it’s probably more modular and independent; however it’s important to move your complete data management platform including your data warehousing, data lake on the cloud, so the analytical tools can be fed with ample, accurate data. This also means data preparation and cleansing can happen in one place with advanced machine learning techniques. Having all the semantics in one place would provide faster access to quality data, and overall cost is also reduced.
It will be able to support cross application analytics and provide insights, which are relevant to the user reducing the total time to value. The platform with the help of modern tools and techniques can provide intelligence at scale, which wasn’t possible earlier, hence building the foundation for innovation.
Having data organised per role or use case in data catalogues are also becoming quite important for better data discovery.
However, the various parts should be more than the sum of individual pieces, hence it may be a good idea to stay with a vendor who can provide such end to end solutions, than doing piece meal approach.
What to look for in that cloud vendor?
Clearly going on cloud provides the much needed agility and flexibility, however it’s critical that the vendor you choose to go with, is able to support you in your journey. Few important things to note are as below:
1. The vendor should be able to support ‘Distributed cloud’, so it can support different physical locations (this may not be in your immediate business need, however something to plan for)
2. Must have security measures for data in transit and at store
3. Must meet legal and government regulations around personal data
4. Should support third party tools and extensions, and
5. Should have a solid partner ecosystem.
Asking the right questions
A simple way to find out if you are on the right track, is to ask the questions mentioned below:
1. Do you have a way to connect data from a variety of sources, both structured/unstructured?
2. Is the stored data up to date and goes back to a reasonable amount of time?
3. Are you able to use technologies such as ML/AI algorithms to forecast and predict with confidence?
4. Can the business users use natural language to interact with the data or have the provision to do so in the near future?
5. Last but not least, are your executives and end users able to find what they are looking for easily and within a few seconds?
Hence, when done right, your data and analytics can become your competitive advantage, could be the differentiator, powering every end user with the right data at the right time without the complexity.
Reena Sethy works as a Director Product Management at SAP. She is the lead product manager for all the mobile applications as part of SAP Analytics portfolio. She has been associated with SAP Analytics team for 10 years now, with an overall 19+ years of software industry experience. She was a Global Product Manager at HP prior to joining SAP. Reena has an MBA from Indian Institute of Management Kozhikode. She is passionate about Analytics, working with customers and helping them in their data journey.
