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December 20, 2013

Who wants to pay for an analyst report?

Other day, I wanted to have some specific information on a certain market segment. Tried various sources and finally stumbled upon a link to a leading analyst's report on the topic- only to be put off by its astronomical cost. While I badly wanted that information, at the same time did not think it is worth that kind of money they are charging. More so since the actual information that I am seeking is only a small portion of the report. I am sure there are many more who share my perspective. This made me wonder how many customers would be prepared to part with such a huge amount for these reports. Are these reports priced at the right levels? Do these analysts who churn out reports on marketing / pricing strategies for other companies, themselves need a lecture of pricing and packaging their own product?

There was a time- some years back-when we used to have too little sources of such information. Those days these analyst firms were the only place you could go to get reliable answers. Now we have too many information sources and these reports is just one of them- that too which are voluminous ones containing 90% stuff which we don't need at the given point in time. Why should I pay for all of that in these times of blogging and micro-blogging? Can't they change their business model to customized solutions for specific context? Instead on bringing out huge, bulky reports in a templatized manner? 

Who is the customer for these reports? Let's specifically focus on IT world.  As I had mentioned in one of my previous blogs, the real decision makers are now the business or end-users. IT department's role is that of enabler.  Do they really care for or for that matter; even understand the numbers these reports are churning out? Can they relate to heavy terms like "value constellation", "value stream analysis" etc.? I am also seeing problem with analyst report being "sponsored" by product vendors- what happens to the neutrality? Isn't it that consultants like me selectively quote from analyst reports if it suits us.

To sum it up- its high time analyst take note of the current market realities and customer preferences and repackage their offerings. They need to focus more on delivering value-added, customized solutions to the customers which would help them do their job better. That's the only way they justify their big price tag.

Fodder for Breeding Cloud Adaption

Around two years back, I wrote this blog which talked about how and why supply chain enterprise applications are the right breeding ground for cloud based SaaS applications.  If we look back now, you will notice that most of the projections in the blog have turned out to be right. Cloud enablement did happen in all facets of supply chain management- be it procurement, planning or execution. However it is also noteworthy that it did not see same extent of adaption in all areas. One specific trend we are seeing is that the maximum SaaS growth and adaption is happening in CRM, HCM kind of "external facing", mostly standard business process. One common attribute of all such applications, which are so called "early adapters" of cloud, is that they all have an inherent need to rapidly scale up or scale down based on market conditions. Whereas we can see that the adaption has not been as much in inward facing business processes like PLM. I am attempting to figure out what is the fodder that is resulting in this uneven breeding of the SaaS in this blog...


SaaS thrives wherever the business process is not perceived to be a strategic differentiator. Companies innovate to survive, especially in their processes and systems. They need to be unique. If everyone has the same systems how do they support their innovation? The underlying philosophy of SaaS is "one size fits all". As we all know, in the enterprise application - especially in ERP world the current trend is towards micro-verticalization.  That makes it less suitable for cloud enablement. Whereas in applications like CRM, I believe, the processes are more or less standardized and there is not much process variation from one industry to another. The need for such products is to rapidly scale up (or scale down) based on market dynamics. In such cases cloud enablement helps in a big way. However if you see the ERP usage in SME segment, for them the cost consideration over-rides the process-driven differentiators. Therefore we can see a higher degree of adaption. 

SaaS will be more effective in such business processes where the change management is easier to achieve. End of the day, when introducing change into business, technology is only a small part. The user adaption is the biggest challenge. Just to give a personal example- I have a Gmail account. One fine day they just changed UI of this cloud based SaaS product- ostensibly to improve the end -user experience.  For all their good intentions, I still haven't quiet understood how the new UI works- leave alone how it making my life easier. May be it's only for me- but I did not like the new interface. But there is nothing much I can do about it. Reason, again is- it's a SaaS- one size fit all! If this is the case for a simple email application, one can imagine what impact this kind of unilateral changes can have on users of big, complex enterprise applications. Moreover SaaS tend to support incremental upgrades better than dramatic platform or UX or architecture updates. That raises the next question- can all change forever be handled incrementally? What will happen when there is significant or more fundamental change in technology - akin to transformation from client-server to web based architecture? Does the SaaS providers all will need to start a second platform, throw away the first, and migrate people over?

SaaS will be more acceptable in relatively younger business processes. By younger, I mean, more recent additions to enterprise IT landscape. If you see the evolution of enterprise application, all the non-core modules or applications are all relatively recent additions.  This include CRM, SRM, Planning Engine, and HCM....etc. If you trace back the origin and evolution of enterprise applications, it all started with basic Data Processing function. When the architecture was conceptualized those days, enterprise apps didn't have to worry about space and time - there was no mobile or instant communications. The data was assumed to be static in nature. So was the user base. Modern day systems need to be based on processes which cater for time (between actions) and location (where each action takes place.) variability. SaaS offers a better solution in such cases.

One another consideration that determines the SaaS adaption is regulatory compliance. SOX compliance mandates the change management in the form of user acceptance testing for the finance-impacting core ERP systems. Cloud or no cloud- the customer company leadership is responsible for effectiveness and efficacy of such a testing. In a SaaS arrangement, the exact mechanism of this participation of the customer organization in managing such changes being implemented by the vendor is still evolving. Till process matures and finds acceptability, there could be some hesitation in moving such critical, core applications to cloud.

They say SaaS is the best thing to happen to enterprise application world in the recent times- something which liberates the IT managers from the strangle holds of highly disruptive product releases, which brings down the exit barriers in switching from one service provider to another. If you add up the software maintenance fees - necessitated by frequent product upgrades by vendor, hardware purchase and upgrades, power and other hard and soft costs associated with on premise solution, the SaaS model is clearly an attractive option in the long run. Notwithstanding all these favorable factors, as described in this blog, SaaS is not a magic band-wagon everyone is waiting to jump on to.


December 17, 2013

Sentiment analytics - are we ready to move from text to multimode?

Today it is easy to give an opinion and there is no stopping us. Nearly one in every four people use social media and in some of the developing and developed countries, around 70% of the adult population spends more than 2 hours per day on the same. That's a lot of time to say a lot of things, things which matter to marketers. Hence companies are investing a lot into mining this huge amount of information on networking sites, blogs, and discussion forums to gain insights into underlying customer sentiment about their brand, customer service, new products, customer behavior and underlying needs. 

Very often sentiment analytics is either considered as a topic within text analytics or text analytics is considered as the approach to sentiment analytics.This may be because, today, a large source of social online data is considered as text. But, the definition could be quite restrictive. More than 65000 videos are uploaded to YouTube alone per day and 6 billion hours of video are watched on it each month. More than 25000 photos are uploaded to Flickr every minute. With this huge number of videos and photos being shared and watched online, companies and analysts can no longer afford to ignore this data and stick to text alone.

If not statistics, we can also look to intuitive logic to build the case for looking beyond text. Sentiment to a layman would be polarity of an opinion. To judge the polarity, words are not enough, the emotion behind the words matter. And emotions are better reflected through tone and gesture. Remember what we learnt at college? "We communicate more effectively through body language than words" and that "a picture is worth a thousand words". Now, which is a better measure of sentiment - "how long a person smiled" in a video or "the number of smileys" in a transcript?

The time has come to move from a traditional single mode (text) approach to a multimode approach. But, are we ready for it? While, there is a lot of research done in labs/institutions to prove the feasibility and superiority of multimode approach, there is hardly any example in real life. One of the main challenges in non-textual data is the variation in representing the same meaning as against words, thus making it almost impossible to model. The other hurdle is that, even though a model is designed (example: Face detection), its applicability also depends upon the quality of the image. In real life people use home web cameras to upload videos or photos and there is an inherent lack of clarity in them. The third challenge is the size of the data, which would be many times more than a text scenario.

It seems we are far from ready, and the challenges are overwhelming. In order to progress on this, we need to take baby steps:

1.      Focus on specific areas where a multimode approach can be a differentiator over text and bring in a lot more value, for e.g. lie detection, sarcasm identification, and real time voice analytics and demonstrate its usage in real life context.

2.      Research on managing the huge size of data needs to continue.

3.      While the ideal state is "reliable automated sentiment analytics on multimode data", we should look into innovative manual ways to do the same to enjoy the benefits now.

For example we could use crowdsourcing to distribute and manually categorize sentiment on a huge set of photos from Flickr or videos from you-tube or audio files from a call center over the internet. After all the quality of sentiment scoring a human being can do is likely to be superior to any algorithm based logic.

What do you think should be our way ahead?

December 13, 2013

Unravelling Social Commerce Age: The Dawn of the Social Consumer

Here a few interesting observations, check them out:

Globally, almost half of those with online access use social media to enable purchase decisions 

Almost one third of the consumers do tend to act on a promotional message on a company's social media pages

More than half of the US online consumers use YouTube and other social media channels to browse and research an organization

Facebook influences the way people made purchase decisions based on their exposure to ads and comments

Still think social consumer can be ignored? Companies who are investing in creating better social experiences for their customers are going to reap rich dividends in the long run as more and more customers are on social websites and conversations are happening in real time about the experiences (good/bad) they went through during purchase or post purchase process. Business cannot control the conversations but can manage it much more effectively by proactive participation!


Social commerce has brought with itself a new breed of user who likes to talk about the products she purchased, liked or disliked. Today's user is very passionate in supporting the brands she love and at the same time does not leave any stone unturned to trash the brand where the experience has not been satisfactory. This presents an unusual opportunity for the business to tap into these 'Brand advocates' but at the same time it is a big risk and a perennial threat to brands if they goof up.

There is so much happening on the web and while we are reading this so much would have been posted on Facebook, Twitter, Pinterest etc. It is very difficult for the organizations to control all these discussions but at the same time it presents an unprecedented opportunity for them to engage users at a deeper level.


All this has started to interest the B2B commerce sites as well because it is just not an option to ignore whatever is being written about your organization and business has to proactively engage with customers in these discussions and provide solution and redress the grievances faced by the user as swiftly as possible. This will be the key in these ever-changing times!


Ways to Engage Your Target Audience:


social commerce2.png
All these are only a few ways in which we can drive a better engagement with the social consumers and help the business grow faster & better. So let your social teams go creative and see what impact that has on your sales in the long term!


It is a bit tricky to predict what lies ahead in this space, but one thing which is quite certain is that more and more users will expect better social integration for their commerce sites and this will drive the next level of customer engagement!
So are you up for the challenge? 

December 12, 2013

Can we avoid driver distraction in connected cars?

The other day I had a friend car pool with me to office from home. We were having a lively discussion on a common interest subject and out of habit I had the FM radio turned on as well. The incessant honking by the motorists on the road only added to the audio decibels around us and it was all getting extremely noisy and insufferably loud. I noticed that all these events were causing a distraction and actually causing a slight dip in my attention to driving the car. This made me very worried.

We are all getting increasingly surrounded by technology in our ecosystem and there is still a hungry demand for further ubiquitous and seamless connectivity within vehicles from consumers. Decidedly so, auto OEMs are being continuously pushed to find a balance between providing 'relevant, important and critical' applications within the car vis-à-vis controlling driver distractions. However, driver distraction is now at the center of all connected car woes and is the most talked about topic at conferences, events and client interactions. More and more people are opposing (or at least voicing concern) to any technology that is going to add to the distraction strain on the driver while driving; which takes me to the moot point of this blog - Can we avoid driver distraction in connected cars?

Undoubtedly, this is the elephant in the room and we cannot avoid embracing new technology and applications within cars and other vehicles. What we could do is devise innovative ideas on how to minimize driver distraction. One way to do this is by classifying what is 'relevant, important and critical' for the car-on-the-road ecosystem. Having prognostic ability built in the car to avoid a mid-drive break down can be termed as relevant to the driver whereas an emergency call (eCall) may be critical for sending EMS to the site. From a consumer perspective, being seamlessly connected to Facebook or Twitter within the car could be important. Hence a matrix should be formed with weighted average taken for all the applications and features that can have an impact on driver distraction. Once this is done, we could then decide what takes priority over the other and then use technology to regulate the communication. For example, an eCall will take precedence over the audio navigation instruction. Route navigation can take precedence over FM radio. A reminder alert can be timed to be broadcast within 5 seconds of engine start and so on. The whole experience within the car will have to be re-analyzed taking situational events into consideration before adopting new features.

Hence, prioritization is going to be critical to decide on which technology or application takes precedence over the other. This will definitely help minimize distraction and allow drivers to handle and manage the seamless connectivity within the connected car. Do you agree?

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