Unlocking the true value of Data - Lessons from the journey

Unlocking the true value of Data - Lessons from the journey

Smart Manufacturing, Industry 4.0, digital transformation, artificial intelligence – probably are phrases that one can hear in every semiconductor company board rooms and read in strategy documents in 2022. Our Sectoral leaders have found value in these already in last decade and some have increasing efforts and focus post 2020 Covid era. Today businesses are increasingly focusing on the elusive and difficult to achieve value on a transformative basis in these themes. Through one-off, us-case based adaptions so far a good value has already been gained. These use-case based adaptions already prove the massive potential of these themes in our industry. 

This article covers 3 main aspects of data driven value generation approach that we believe is essential for data driven enterprise transformation.

First , it is important to understand what is transformation and transformative value. Many tools aid in better , efficient business flow, like a normal application that replaces many excel sheets, brings structure to a process. However Artificial intelligence, machine learning are tools that are truly disruptive.  . Most companies try to adopt them by defining some use cases where they can be used. This method is valuable but only should serve the purpose of creating a sense of understanding within the company.  Goal is to make them part of every decision made in the business on a daily basis.  If we were to look at history of truly successful disruptive technology for every company large or small on earth  ,it would be  tools like Microsoft Excel / PowerPoint. Sorry, this may not be an example you expected, but if you would imagine a day without it in the office, you will know what I mean.. 

Excel has replaced painstaking collection of data on paper, hand drawing graphs, analyzing business problems - across companies, across globe like no other Software ever has. Today you won’t find a company trying to analyze data by collecting data points on paper, nor making old style projector slide shows. Its also a futile exercise to figure out true value Microsoft Excel has added to business!!!

If you look at this transformation, a massive value creator of the past – at some point in time,

a. Companies trained all of the workforce on Microsoft Excel / PowerPoint.

b. Companies added this as Must have skill in the job description for hiring.

c. People with this skill were probably paid more than others until it became all too common.

d. Early adapter to Excel had definite competitive edge over others.

e. And lastly, there were people who feared their jobs will be replaced by Excel or even wrote this off as a one-time thing.

f. I believe Data analysis as a skill needs to be a foundational skill for everyone in the company if we would like to get the transformational gain. Particularly covering how to define a problem, explorative data analysis, hypothesis building and testing & basic statistics. This is our first aspect- People & skillset to know how to get value from data.

Second aspect is an easier one – to establish a technology framework, set of tools that can truly be Microsoft Excel’s of the future for AI/ML.  I say this as easy, because I feel there is a lot of option out there today that can help. Personally, I feel business intelligence is fist step towards diagnostic models which can further become predictive or even prescriptive models. I believe true transformation can only come when we do not look at use cases but slow progression from BI to AI.  Hence a key selection is to believe in this process and select a tool platform that can help a person to go from BI to AI , providing excel like easy interface and workability , transparency and freedom to a user.  One must consider that different part of organizations would have different speeds at adapting. Its also essential to consider this in the tool selection.. Selecting tools that are built for Self Service AI/BI, that are open for rapidly developing space of AI and can change is a must.

Last aspect is probably as big and as important and most difficult as the challenge of people, skill sets and mind set i.e. of Data. Technology partners might trivialize this with promise of data lake’s, data mesh, data fabric , streaming analytics, bigdata etc. but transformational gain is much more cultural change than anything else. Let me give an example – if as a company we wrote our quality specs in word/excel documents with tables of data – a true BI system can not process the same. (Unless we do a hard work to digitize this unstructured data). Each department in the company need to figure out what’s the most valuable data asset for them and focus on getting that digitized – change processes, tools, mind set etc.  Key thing is to also have a proper governance setup for collecting, storing, consuming, purging, archiving, securing data. As this is a massive enterprise, best would be to establish most valued data assets and start journey from there. If data is to be an asset, it needs to be treated as one.

Final part of the puzzle is organizing ourselves for success. I believe that each department must invest in an analytics team to catalyze the journey and to find out most valuable data, building governance together with core set of talent in IT. Our strategic programs like that of margin improvement, cost reduction, revenue growth, factory OEE/ Yield etc must have embedded data analysis teams to unearth hidden avenues.

Unlike other industries, semiconductor has always been known for its business complexity. We are hence, never early adapters of technology hype cycles. Our leadership don’t give into euphoria, rather focus on something that we can achieve now. I believe the moment for data has arrived. Its time to take this seriously and unlock its potential. Bon voyage for this journey!!!

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