Do Business cards still make sense?

A business card from 1895. Surprisingly, they haven't evolved much

The past week I was in the Hyderabad Startup Saturday meetup, a monthly gathering organized by HeadStart. Bumping into some interesting folks, I was networking and exchanging business cards. But all through, I had this awkward feeling of practicing an anachronistic custom, not very different from dispatching a snail mail postcard in the internet age. That made we wonder whether business cards had outlived their once-useful lifespan?

Let's face it. We use cards to exchange contact details, and what do they generally contain? Name, role, phone, email, website and maybe a couple of social profile handles. But, when was the last time you wrote down a mobile number from a friend and keyed it into your phone manually? How much more awkward it can get to key in a twitter handle from the card?

Agreed, cards help register one's name and role, as a supplement to the spoken word. In some occasions, they can be useful icebreakers to strike up conversations. And, there is always the possibility to impress with an unconventional design. 

But these aren't reasons enough to keep business cards, which are actually vestiges of the erstwhile corporate era, on ventilator-support. Yes, there have been barcode incorporated cards and other digital embellishments on a physical card, but these solutions are akin to taping a brick-phone from the 90s with a GPS navigator device, on its rear.

Lets think up some alternate possibilities. What if we can enable digital-handshake by letting people wave off their mobile phones, to automatically exchange a profile brief and all their social handles (perhaps even contextually deciding whether to share Linkedin/Twitter handle with a professional contact or Facebook/Instagram profile with a friend). The person can then choose to glance at the profile brief on mobile and then with a single click add the shared contacts to all relevant platforms.

Atleast, this would help save the hassle of printing and maintaining currency of a physical business card. And it will definitely do away the awkwardness of reaching out into one's pocket to pull out a piece of paper for networking.

PS: At the time of posting, I did a quick check on prevalent apps that address this problem. There seem to be some action over the past few years, and a few of them seem to be catching up. But, the final word from several experts is that physical cards are giving a tough fight, and they just refuse to roll up and die!

Staying on top of your online reads

About 5 years back, I had first set up RSS feeds of my favourite news sites and blogs on Google Reader. It was a nice and simple interface to consume content. That was until Google decided to shut it down, amidst huge uproar from loyal users. After evaluating options, I settled on Feedly, which seemed promising and importantly offered one-click migration, by pulling in all feeds from the Reader. It has served me well the past couple of years, and this post is about how I've organized my Feedly account over time to stay on top of content.

With a limited set of feeds, organizing and reading stuff doesn't need much of thought. As you keep continually adding feeds, things start getting a bit muddled with diverse categories of interest, variety of sources (self-hosted websites, medium, blogger, news sites) and a varying velocity of feed generation - ranging from hundreds every week to an occasional gem-of-a-post.

I started simple with just 2 categories to group all feeds or article sources - 'Headlines' or the not-to-be-missed articles and 'Others', that had everything else. Eventually, my sources grew to over 100 feeds, and 'Headlines' ballooned to over 50. Overwhelmed by this torrent of information, I did some minor re-categorisation which didn't seem to help. I was looking for an optimal mix of categories, while also being able to flag off the 'hot sources' across categories.

Preview of my Feedly panel

Eventually I settled on 7 categories (as shown in the image) to organize the feeds, with each having not more than 15 to 20 feeds each. To maintain sanity, I keep purging sources that doesn't match up with consistent content. Feedly has a super-useful feature of flagging of favourite sources by them as 'promote to Must read', which essentially mirrors the same feeds onto a separate list called 'Must reads'.  This list is again kept at around 15 to 20 feeds and any new additions are always after some removals, to keep it manageable. This workflow has been working well for me, and here are things I like most about Feedly:

1. Good UI with a easy procedure to add & organize content. The feed recommendations are quite relevant too.
2. Clean reading interface with 5 presentation layouts ranging from a mailbox view, cards or an online magazine layout to fast-read stuff. I generally use the 'magazine' layout.
3. Features in the free version are good enough for basic usage, with unlimited feeds & social sharing options bundled.
4. Maintains a 30-day window for articles, after which they get cleared. As opposed to storing content over months or years and getting inundated with scary notifications of thousands of unread articles, I've realized that this time-bounded expiry brings in some reading discipline.

Mission Inbox Zero, and how Google Inbox got me there

Inbox Zero has been the holy grail for email users, more so for technology professionals. Email services have been getting better at cutting clutter over time, starting with showing you the right emails (minus spam), then relevant ones (minus newsletters/updates) and most recently important ones (minus low-priority). These continuous advances notwithstanding, maintaining an uncluttered inbox, leave alone inbox zero, has been a rarity.

I've been following a simple email workflow, that has been reasonably effective to get things done at work. Starting with priority emails, I read and action them, which then becomes 'read'. If I need more time to read or action it later, I keep it 'unread'.  Likewise, if I'm awaiting response or action from others to close loop on an email, I keep those 'unread' too. Several times in a day, I scan the low-priority emails or notifications and keep clearing it. Though this approach has been working for me, it means a *lot* of unread emails and a daily struggle to avoid wasting time on re-scanning known pending actions or not-yet-mature threads.

I have tried some popular email productivity apps such as boxni, gmailmeter, sanebox, followupthen all promising you with tickets to the holy land of 'inbox zero'. However, I found them to be incremental improvements which only take you ahead a couple of steps. Having heard rave reviews about Inbox by Gmail for the past 6 months, I took a look, but was surprised to find it designed against 'time-ingrained, conventional approaches'. Though I didn't drop it completely, I kept avoiding it, until last week when Anand made a gentle but firm push in this direction.

Giving it some serious thought, I've been exploring & trying out this alternative and surprisingly, this seems to solve many of the clutter problems. 

• Inbox doesn't make a major distinction of 'read' vs 'unread' (my fundamental grouse for avoiding it)
• Instead you mark actioned emails as 'done' which get archived (another reason for panic, since I've never archived a single email earlier)
• Any email that you need to read or act later, can be 'snoozed' until then. Similarly, actions pending from others could also be 'snoozed' until you reach a future time or place
• Labels have gotten smarter with 'bundles' where auto-categorised emails are bundled for quicker and bulk action
• Add to that, gamification and smart gestures to swipe and mark 'done', 'snooze' or 'set reminders'.

Inbox, thus forces you to transform your mailbox into a to-do list rather than a carefully curated journal. The past week, I've been on a cleanup mission to do something about the 1000 odd unread emails (300+ high priority!) in my mailbox. Before migrating to Inbox, I had to do a 'purge act' and bring it down to a manageable list to start with. Firstly I archived all my 'read' emails. Considering I had over 20,000 emails in 'actioned' state over the past 5 years, I archived them in bulk, though it took a couple of attempts to get it done.  

I've then been cutting, slashing and burning to bring down the 'unread' count over the past few days. The first 500 was a breeze with easy-to-discard calendar notifications, updates and emails that I shouldn't have really been in. The next 300 started getting slow, with FYI emails and interesting reads, some really dated. The final 200 were the ones that needed real action and hence took a bulk of time. I'm sure quite a few brows would have been raised to hear back from me on long forgotten threads, after months or even years, in a couple of cases. Reaching sub-100 emails, I switched over to Inbox and happily snoozed the future actions and follow-up emails. I quickly setup bundles to improve categorization and added some helpful reminders.

Seeing an inbox with under 30 emails was extremely cathartic, something I haven't achieved in years! Migration to Inbox acted as a good push to get to this state, however staying here needs much more than its cool features. After all, Inbox zero is not exactly about having zero emails, but an ongoing sensible philosophy of email management, to ensure that emails which are just a means to get work done don't eat up too much of your time. Instead, you must be able to reserve a bulk of your time & attention for getting creative and productive work done.

Sandhill Article: Building a team to deliver Big Data's promises

A whitepaper I had written on building and scaling Data Science teams was published by the Business Strategy online magazine, Sandhill in the past week. As a coincidence, we celebrated Gramener's 6th founding anniversary this week, hence its been great timing. Here's the full article:

How to Build a Team to Deliver on Big Data’s Promises

• Ganes Kesari, Vice President
  Gramener

Big data, which has caught the fancy of people worldwide, across disciplines, seems to be maturing from the ”next big thing” to providing business value for enterprises. As a key trend shaping the market, it continues to hold sway over all stakeholders in this ecosystem, whether it is the millions looking to make a career out of it, thousands of enterprises wanting to leverage data for business gains or the rapidly mushrooming set of new and established players who intend to provide solutions in this space. However, one question that baffles the big data world is “How does one build and scale data science teams to deliver consistent business value from data?” 

Relying on the adage “experience is the best teacher,” I draw upon the experiences of building a delivery organization to provide customer value from the big data promises. Need for multi-disciplinary skills, dearth of talent, intense competition to hire talent, limited hiring dollars and a fledgling brand all made the task tougher. Hence, this article discusses the realistic action in the trenches rather than a few concepts. 

Setting up a data science team 

For enterprises aspiring to put big data to use, the broad approach to a sound solution is a three-step process:

1. Consultative solutioning to identify the business problems, define and scope out the right perspectives
2. Pertinent analytics to derive insights and hidden patterns from data
3. Data visualization to bridge the last-mile disconnect by converting numbers into visuals, to present the information and insights from data. 

Let’s now look at the key challenges that an organization would face in building and scaling such a big data solution and how to address these challenges. 

1. What mix of skills can deliver value? 

Delivering a robust data science solution calls for a multi-disciplinary skillset across four broad areas:

1. Domain skills to identify the right business challenges and come up with solutions
2. Quantitative skills needed to apply math and statistics for extracting insights from data
3. Design skills to present information in a creative, aesthetic and usable manner
4. Technology skills to leverage deep programming and data technologies for scripting this end-to-end analytics and visualization solution. 

2. How to hire the right skills 

With companies struggling to hire talent with good skills in most of the above areas, it is next to impossible to get a combination of all skillsets in one person. One solution is to carve out new roles in data science along functional and technical lines by bundling a set of related skills that is closest to the solution offered. 

The intent is to hire people with complementary skills, who would come together as a multi-functional team to deliver an engagement. For a bootstrapped startup, it’s a sound strategy to start with talent in known circles and through direct referrals, wherein the initial hires can be trained on the job and supported on existing skill gaps by the senior members or founding team pitching in. 

3. How to attract the right people 

The war for talent is a perpetual problem for most companies, and new-age startups take a different approach to address this issue of hiring great talent. These companies consciously invest a good amount of time speaking and participating at relevant big data conferences, public forums and partnering with educational institutions offering data science courses. While this aids with branding and creating a buzz in the industry, it also helps get closer to qualified talent and attract them from relevant circles. 

As a side benefit, this could also have an indirect fallout on sales lead generation by helping add qualified client leads to the sales pipeline. 

Additionally, targeting the key movers in online technology forums like Github, Stackoverflow and the like can be very beneficial for companies in identifying lead and senior profiles. The focus at this stage should be to make the hiring process efficient by pre-qualifying candidates and helping preclude the inordinately long cycle times and low success rates associated with the traditional hiring process. 

4. How to train the team across multi-disciplinary skills to deliver sound solutions 

With a growing team, it’s imperative to address the problem of repeatable delivery early on by putting together a sound delivery framework with clearly defined processes, roles and responsibilities, and deliverable templates and artifacts. One must keep a continuous focus on training and upskilling the team across roles by creating or sourcing content to run internal training programs. This can be supplemented by online courses and guest lectures by experts from the industry. 

All through this stage of growth, one must retain a laser sharp focus on clients and ensure that there is consistent and considerable value-add to the business stakeholders by leveraging data to smartly solve the business challenges. 

Adjusting sails for the next wave of growth 

5. How to correct chinks in the armor that impede scale and decentralization 

As organizations scale, it is imperative to reexamine the systems and processes to identify the need to adapt to changed market needs and internal dynamics. Often when companies breach the golden team size mark of 100 employees, they run into typical scaling issues around employees, processes and the quality of client-facing solutions. 

This can be tackled through a critical review and reorganization of existing processes in order to overhaul all those practices that don’t fit well with the theme of rapid upscaling. At this stage, organizations need to be open about decentralization and empower the second line of leaders who can carry the organization forward. 

Also, the convenient and comfortable practices would have to be given up in favor of more objective and standardized processes that can be rolled out across a larger team. 

6. How to improve the skills-mix by growing breadth while also achieving depth in focus areas 

Organizations at this stage need to focus on deepening the skills and knowledge areas to improve the quality of their solutions. A relook and expansion of roles by unbundling responsibility areas to allow for deepening of skills and knowledge areas can prove beneficial. At the same time, one needs to look at broadening the portfolio with complementary offerings to provide a well-rounded solution. 

Towards this effect, Centers of Excellence (CoE) or “horizontals” can be carved out within the organization in the core areas of data science, information design and technology to help achieve the needed depth in big data skills. These horizontals can take on the mantle of expanding and providing specialized training to the teams for all up-skilling needs in the organization while also taking a lead role in the complex, specialized implementations for clients. 

7. How to adopt practices in hiring for scale 

With requirements calling for greater numbers in hiring at this phase, the channels can be expanded by signing up with selected strategic hiring partners, apart from leveraging innovative techniques in data analytics through online channels for hiring qualified talent. It is also a sound practice to run hiring hackathons and data science contests on sites like Kaggle to get the right level of attention from prospective candidates while also opening up the possibility of hiring in bigger numbers. Employee-driven referrals can start yielding fruitful results at this stage. 

8. How to move up on process and solutions maturity 

At this next stage of evolution, it is critical to deepen the relationship with the client by taking on an advisory role and hand-hold the enterprise in chalking out a comprehensive data analytics road map. The maturity levels in solutions offered moves upstream, from delivering business value in chosen areas to looking at the enterprise end to end and advising on the set of strategic initiatives and moving clients up the data leadership hierarchy. 

In conjunction with this, the organization and delivery process must be re-bolstered by focusing on scalable processes and delivery excellence to support the growth needs. By weaving in the expanded roles and responsibilities of all individuals in the organization, a robust performance review process can be established to enable continuous career focus and growth for the team. 

Summary 

Building and scaling a big data organization is a continuous and challenging process. One has to continue work methodically on the above-mentioned spectrum of areas, coupled with reviewing and reorganizing at the right intervals throughout the growth stages of the organization. 

In spite of a constantly shifting base along with the many moving parts within and outside the organization, it is critical to retain an open mind-set and nurture the core ethos that is the lifeblood of an open, startup organization: innovation, technology-focus, client-centricity combined with an open culture and fun at work. By retaining the focus on these critical growth factors and addressing the scaling challenges, this cycle of conceiving, scaling and maturing of an analytics delivery organization can indeed be made a reality. 

We continue to unlearn, relearn and scale to the next level in our journey towards becoming a mature big data product and solution provider. As more and more customers commence their nascent big data journeys or look at moving up the maturity value chain, organizations like us that offer solutions in this space have a critical responsibility to not just merely aid them, but transform constantly to deliver concrete and lasting return on investment throughout the journey. 

Ganes Kesari is the VP of products and consulting at Gramener, a data visualization and analytics company. He tweets from @kesaritweets and can be reached at ganes.kesari@gramener.com. 

Serving delicacies on the go: your neighbourhood Superman food truck

Food trucks are the latest rage to have burst onto the Hyderabad food scene. One can find them in the evenings, in several parts of the city, quite noticeably in the areas around Hitech City and Gachibowli. Its practically a night-time 'mela' with all kinds of food trucks dotting the length of the road serving a variety of cuisine, snacks & other assortments. The rates charged though are tantamount to the QSRs (Quick Service Restaurant), and not very different. They are doing brisk business and people from all walks have taken to it with full vigour. You can find Zomato listings of food trucks and even startup apps that are built around locating food trucks in your area. 

A food truck (source:Hindu)	the busy 'eat street' in Madhapur

This has not always been the case, atleast in the southern parts of the country where, unlike Mumbai or Delhi, 'street food' was never celebrated. Food trucks used to be a 'cheaper' & 'quicker' option, but not a palatable one for most people. People had their qualms about standing and savouring these options, or atleast a stigma attached to being seen eating out in the open. Ofcourse, there have been noticeable exceptions, like the famous 'ram-ki-bandi' in Nampally area of Hyderabad, which boasts of a celebrity clientele. However, these have been few and far between and acceptance was generally low. Its nice to see this change now, for the good.

My experience with food trucks started during my Engineering days in Karaikudi, where a Chinese-cuisine serving truck aptly named 'Huang Suang' was a rage in the campus. Located in the middle of the city, this was frequented on a daily basis by the students & 'masses', but the other locals and 'classes' generally stayed away. I've continued eating 'out' through my stints in Delhi and during my travel, so we recently checked out one of these food trucks in Hyderabad. The 'Superman Dosa' truck served piping hot 'pizza dosa' and 'schezwan fry idli', while the kids enjoyed the experience!

Mac transition: a 'reailty' check

Its been over a month since my transition to Mac, and I had set myself a review touchpoint at around this time to reflect on the migration, and had perhaps hoped to feel good about the smooth transition and cool productivity hacks learnt. Unfortunately, its not been a happy ending, atleast not just yet! I continue to struggle with the new machine and the transition is far from complete. 

Here is an update on what has worked and where I need urgent attention. Firstly the good:

• Hardware: I'm thoroughly enjoying all aspects of the hardware performance, whether its the gorgeous display that makes almost anything look great, or the blazing-fast performance with the i7 processor, 16 GB RAM and SSD HD. The machine is truly mobile, with a battery life of 4 to 5 hours (perhaps it might last the supposed 8 hours, with energy saver on)
• Apps compatibility: The machine has worked fine with most apps I use and I haven't had any platform specific issues, apart from an instance where it was unable to write back to my External HD that was setup on Windows.
• Settling down with Safari: There is some new-found familiarity with Safari, and its a good thing since 90% of my time is spent on the browser. Features like pinned tabs, easier navigation and some shortcuts at browser & gmail level have made life easier.

.. and the niggles:

• Mac Office: Powerpoint, Word & Excel would rank amongst my top used applications of all-time & I used to have a reasonably efficient way of getting stuff done. I'm at a loss of words on the extent to which I'm struggling on this now. Perhaps its got to do with the version (MS Office for Mac 2011 v14.4) which feels like a poorly built office with badly designed shortcuts, and I really hope an upgrade will sort this out.
• Managing files: Yes, I did manage to find my Hard Disk eventually! But I still suck at accessing and moving files through the 'Finder'.
• Mac native features & apps: I'm yet to figure out efficient ways of working with in-built apps like iTunes, iBooks, Pages, nor have I explored any new useful Appstore application. There is scope to improve on usage of cool features like the multi-touch gestures, or even try out basic customisations & system preferences. 
• Shortcuts & efficient ways of working: Inspite of the early ground covered, I've lagged in learning shortcuts across applications, for instance I still don't know how to 'lock' or 'put to sleep' with keystrokes. 

I'm working on these, and hope to publish a 'happy-ending' to this migration story sometime soon.

A 'Good Dinosaur' themed party

Recently, we were hunting for a theme for our kid's birthday party. With a boy and girl to cater to, gender-specific themes such as 'Princess', 'Dora' or 'Cars' weren't appropriate. 'Mickey mouse & clubhouse' was an option, but it seemed old & cliched, atleast to us even if not for the kids!

Thats when the kid's growing interest in Dinosaurs and they getting besotted with the 'Good Dinosaur' movie provided an option. Apart from the interest, they emulated the characters as well: Arlo, big but a tad timid dinosaur, and Spot is the other extreme, a tiny baby with temerity to fight bigger things, while both are extremely protective of each other. After looking at other themes like the popular Chhota bheem-Chutki, we finalised this one.

However, since this theme was relatively new, no preset templates were readily available for the invitation cards, cake design or the stage decorations. With a couple of days left to prepare, we decided to customise and get the templates created. Picking up images from the various sites and the movie's posters as the base, we did some quick edits. Here is the collection of themes and templates we finally created on Sketch, and handed over to the respective vendors.

Invitation Card:

Cake:

Stage Decoration:

Please drop me a note if you'd like any of these templates shared.