Importance of R&D for Digital companies

At Innoplexus, being an AI and data first company, we have been investing heavily in R&D and there has been an ongoing debate on how much is enough. I keep reading on the the topic and today I came across this excellent article in HBR which makes the case clear for higher R&D investment for Digital companies. Here is the link – https://hbr.org/2019/01/its-time-to-stop-treating-rd-as-a-discretionary-expenditure

Here are the key insights:

  1. R&D is an economically significant expense for digital companies, much larger than for physical product companies.
  2. A large component of R&D costs for digital companies consists of employee costs for engineering, product management, and information technology personnel.
  3. Digital companies consider product development as a necessary activity to survive. Digital companies must invest in product development to keep pace with the technological progress, competitive offerings, and ever-increasing customer expectations, or fear becoming obsolete in no time.
  4. Digital companies routinely rely on third-party software, algorithms, development tools, cloud services, security and data integrity systems, client monitoring, customer databases, and cross-selling platforms for their day-to-day operations.
  5. Digital companies continuously scout for acquisition targets to obtain readymade R&D and talent teams.

Thanks alot to the authors – Vijay Govindarajan, Shivaram Rajgopal, Anup Srivastava, Luminita Enache – for conducting this investigation and sharing the insights.

 

 

New job – training eagles to bring down drones!

We already are witnessing the adoption of drones in all kinds of tasks across industries. I have been wondering about the jobs that this is going to create in future. And this I have been wondering about quite a few kind of jobs which do not exist today or atleast people do not even imagine but they are every much going to be there in very near future – reason why I think this is something I should start posting about.

Today I came across this post which talks about how Eagles are destroying drones because they see them invading their territories. Here is the link to article: Birds are fighting back for their territory already

Just one example quoted in above article talks about how a wedge-taled eagle destroyed a $80,000 drone in a matter of seconds!

And it ends with how French are using golden eagles to destroy the drones operated by terrorists.

Which opens up a whole new job category – people who will be able to train eagles (or maybe other birds) in messing up with or destroying the drones. Going further I can even imagine that one trains another bird to launch a counter attack on the destructive bird to protect the drone. The job definitely looks interesting and will require people who can really ‘tame’ and train these birds to achieve the defined ‘goals’.

#JobsOfTheFuture

Innovation eats data for breakfast

I read this amazing article from Prof. Viktor Mayer-Schönberger and Thomas Ramge on Harvard Business Review. Follow the link here – https://hbr.org/2018/02/are-the-most-innovative-companies-just-the-ones-with-the-most-data

They have made an excellent case for a data driven innovation. Citing examples of how Google, Apple and Amazon are using data to further innovation and outsmarting not just their existing competitors but also the startups, they have made it very clear that the future innovation will be owned by enterprises which are able to leverage AI in generating insights from the data and not just rely purely on human ingenuity.

I am sharing here the two adjustments, they mentioned about, that enterprises need to make:

First, they need to reposition themselves in the data value chain to gain and secure data access. Second, as innovation moves from human insight to data-driven machine learning, firms need to reorganize their internal innovation culture, emphasizing machine learning opportunities and putting in place data exploitation processes.

Now, one interesting point to ponder about is – what do we mean by data really ? In all of their examples it means the data generated by users which is being used by large corporations to generate insights for improving their products or services.

What does it mean for companies whose product or services are not consumed or delivered online ? eg. Pharmaceuticals

In that case they need to look at the data that is publicly available. Thankfully, there is a lot of data that is available publicly eg. information on clinical trials, research publications, disclosures to regulatory bodies, reviews from regulatory bodies, data from different scientific congresses across the world, theses from universities, patents from major patent bodies globally, data from major global regulatory bodies etc.

In the context of the second adjustment above, enterprises need to leverage AI to automate not just the collection and curation of data but also the generation of insights, specific to key processes, from the data. Entire Drug Development process is very long and complex, with a lot of tasks / processes which are repetitive in nature or involve a lot of manual content reviews at each step. It is up to the enterprises to empower their teams to step up the value chain from doing manual analysis of data to being the domain specialists who can partner with Data Scientists to come up with good training data sets, to validate the output of these algorithms and to be the data quality supervisors.

In the end, it will only improve the overall satisfaction of employees as they will free to solve real problems instead of clerical tasks, which ultimately leads to happier and more productive workplace.

P.S. The title (Innovation eats data for breakfast) is just a pun on the famous “Culture eats strategy for breakfast”, a phrase coined by the legendary Peter Drucker.