API and Data Analytics

We've seen this trend before -- at IBM, we talked of business automation and business optimization.  First the enteprises set an "application agenda" to get their business processes and apps standardized and consolidated.  And then, in a serious way, they got into business optimization using data and analytics.  At IBM, we called it "information agenda."  It is not just about getting visibility into processes and applications, or reports (which is important, but nowadays is more or less the cost of doing business). Enterprises that master the Information Agenda are getting a handle on information and leveraging it to optimize the business using analytics.

I am seeing the same thing around API's.  {I am assuming that most of you grock the concept that API's connect backend and enterprise systems to (primarily) front-end and mobile developers, and need to be managed and tracked as a valuable asset.}  The current spend is around the transactions that flow through the API's (*, see below) . And of course key clients (**, see below) want visibility into APIs - who is calling what, when is it happening, what error reports etc.  I call this IT and API metrics.

However, as I talk to customers, it is also clear that they want analytics at the business level -- what products are being bought, what money is being spent on games, what is being tagged most frequently?  I call this business metrics.

So the API team, the lines of businesses and the developers of the apps using APIs want analytics on IT and business metrics.  So far, that is natural.  After all, if something is being used, it must be tracked and monitored.

However, the real game changer is when the metrics are used to do prediction and to take action.  Analysis of an IT level metric might automatically lead to a policy change for caching during peak hours/months. Analysis of a business level metric might allow a game platform provider to make the games more sticky by predicting abandonment and automatic triggers of some offers.  APIs are going to be central to any future enterprise.  And predictive analytics on APIs, in my mind, is going to be central to those enterprises (hopefully 100%) that are trying to optimize, not just automate, their business.

There are two other trends that need highlighting.  One, of course, is cloud.  Can such analytics be delivered in a simple but gorgeous way through the cloud?  And second is data, with so much data out there that is external to an enterprise, can that be brought to bear to deliver some wonderful added value to analytics?

So this is what I will be helping Apigee do.  If you are an Apigee customer, then I will be spending time with you.  If you are not, then I hope that our data and analytics technology will convince you to give Apigee a try.

But most importantly, I will always engage in an open and honest dialog with the blogosphere so that we can collectively "rise all boats".

* I am so used to writing API's (note the apostrophe), but at apigee they will convert me into writing APIs, I am not sure whether I will ever master that :) and maybe I will convert the rest of my colleagues to my way!)

** oops, at apigee, it is customers, so another thing I will have to retrain myself on

Comments

[Roque Versace]

Hey Anand,

Good post, glad there's someone else out there pitching the importance measuring api's (i'm with you on the apostrophe).

You'll up the game quite a bit over there and I look forward to a few years running into each other in the market.

roque versace
vp, mashery

[Shivkumar Vaithyanathan]

Love it :-)

[Anant Jhingran]

Is that you Shiv? I got confused because your name says Shivkumar not Shivakumar.
How are you?

[Ramesh Venugopal]

Hello Anant, I liked your style of writing and expressing your views.

While I agree with your views broadly, I think the importance of IT & Biz analytics have been long understood in most cases, but with limited action by the enterprises in the past. Having said that, their focus on predictive analytics has increased in the recent past, owing to the challenges faced by the industries. As most of us have seen, when the market is upbeat and there is potential to attract new-new (I mean not the churn) business, the focus tends to attract them with suitable propositions (products). But once there is some amount of saturation in the market place, the focus tends to attracting new customers from the competition. At the same time, they need to ensure their customer base is not eroded. The classic example is the telecom industry in India, which has now gone from pre-dominantly customer-acquisition mode to that of customer-retention, which they seem to be struggling with. This is when the enterprises are forced to acting on the notion of ‘Data as an Asset’ by focusing on predictive analytics to improve customer retention, customer advocacy, up/cross sell, etc.

Let me share my personal views on both IT & Business analytics. While IT analytics is important, I see it more as a hygiene exercise, something that the CIO/CTO should be delivering anyways, resulting in lower priority when their change portfolio is drawn.

On the other hand, based on the market scenario, the business analytics gets direct sponsorship from the likes of CEO/COO. I see business analytics being extremely domain centric and confined mostly within an enterprise (and hence APIs role gets limited), due to the sensitivity around the data or regulation or threats from competition or for other reasons. For the same reasons, it gets difficult to push this data on to a public cloud (an idea you were mounting). Hence i am not able to understand your point on analytics of APIs in the context of business analytics.

Hence to conclude, the way I see is business analytics happens more around the backend data store/data marts (at times at the workflow / process orchestration layer to respond to triggers or events which arise) with a view to predict an event. Hence the role of analytics on APIs is very limited when it comes to business analytics. Having said that IT analytics is indeed relevant to the APIs, since it helps optimise the way in which interfaces respond at run-time to match dynamic nature of business volume.

Sorry if this sounds like a long rant. I will be glad to know your views. Thanks.