13 #MachineLearning Data Set Collections by @DataScienceCtrl https://t.co/7CnO202dPR #datascience #DataScientists pic.twitter.com/lDdy22n9Rh
— Roberto A. González (@robertoglezcano) November 29, 2015
Machine Learning?
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Guess you’ve all seen the sudden explosion of articles about big data recently – you can hardly load a webpage without seeing it mentioned – and a number of questions may have come to mind. Things like
I’m going to look at each of these questions – and probably some others – over the next few weeks, and share what I believe to be useful and how data can be leveraged for you and your clients. I say data in general because from a business perspective it doesn’t really matter if your data is big or small – it’s part of a total approach.
Let’s look at the last question first – is big data really a big deal? To start to answer this question, let’s look at understanding some things about data generally.
Think of data like water. Water is a resource that can be scarce or abundant and historically, we didn’t know what it was made of. We didn’t know its chemical makeup, what properties it held, how pure or impure it was. We only knew it was water. When it was scarce, we moved in deserts from oasis to oasis, getting small amounts out of the ground with great difficulty. In abundance, we crossed oceans made of it, not seeing into its depths and understanding what secrets it held. In essence we held neither a micro nor a macro view – we were at the same level.
Nowadays, we understand water differently. We know what it’s made of chemically and we know that it may contain various different substances while still maintaining the same appearance. We have better ways of detecting it in environments where it’s scarce and better ways of getting it out of the ground. We no longer only float on top of oceans – we build pictures of what lies underneath and detect currents and patterns across large areas.
At one time, a cup of water only quenched a thirst. Now, it holds the answers to many other questions.
With data – particularly big data – we’ve followed a similar path to a greater understanding. In the past for organizations and for society at large, information could be scarce. We’ve known that events have occurred but we haven’t known all of the details about them. Analysts traipse from system to system, copying information from one Excel sheet to another trying to get a picture of what’s happening. We’ve floated on top of information that is unknown, un-described, or both; a bit like old-time mariners, sometimes feeling there’s a storm coming with no way to see the currents that really tell the story, not seeing the shark until it attacks.
Now, information generally has become more abundant and available to both individuals and organizations. We can identify and describe each element of a particular event and save that information for later. We have better ways of discovering and aggregating data, saving the time and effort involved in pulling information together into one place. Now we can choose to float on top of the data, look at its currents and patterns from different perspectives, or we can look at the data itself and understand what parts are needed to answer a particular question and what is not.
So is big data a big deal? Fundamentally yes, but this new abundance has its own challenges. Data now comes out of a fire hose and we have to figure out not just how to sip from it, but how to siphon only what we need. How do we know what we need? This is the next question I’ll be looking into.
I’m seeing more and more ads in the US for “Customer Success Managers” at technology companies such as Salesforce.com, Birst and Citrix, to name only a few. This is partly just a change in nomenclature as I’m pretty sure these companies all used to have account managers, but there a different flavour to these ads. They’re less sales-orientated and more about the longer-term success for the client in their use of technology. This is an excellent development in the marketplace and a trend that will hopefully continue.
Why? Because technology companies used to be a little bit lazy about customer care. They could sell products that would support a client’s business for a couple of years at a time. The sales team would make a sale and think that they could rest easy, touching base with the client executives at infrequent intervals with the Support team interacting more regularly at the lower levels. Now, as the pace of change increases and every business adapts to its market at ever-faster rates, no product remains static. New features and functionality are demanded on a daily basis and new metrics are available through which a client can understand whether or not anyone is using the solution they’ve paid for. The client is more engaged than ever in their technology solution and as a result the solution provider has to stay in every conversation. It’s the only way to help clients adopt new ways of working and understand what they may need next.
This is the focus of these types of roles – not just selling but engaging, listening and advising at several different levels to prevent valuable clients from churning out of the business. If you’re not following this approach, you may keep the top of the sales funnel full but find that clients end up dropping out downstream.
Going with your first instinct is fine as long as it really is yours.
Awhile ago I went with some friends to Canada’s Wonderland. It was the first time I’d been back in years and while I can’t go on rides that go around in circles, I love rollercoasters. Wonderland has LOTS of rollercoasters and I’m pretty sure we hit all of them.
One in particular was pretty scary as there was no floor. You got into your seat, the safety bar came down and as you rolled out, the ground dropped away below you and you realized that you felt kind of naked. I was sitting next to my friend Ken and as we pulled to a stop at the end of the ride, my two friends in the row behind us said, “Let’s go again – we can just stay on!”
Ken said, “Yeah – ok! I’m going again!” but I was done. It was a good ride but once was enough for me. I waited for them at the exit and on their return Ken looked a little shaken up.
I asked him what was up and it turns out that after I got off the ride there was a short wait, then the safety bar came down, and then he realized that he didn’t want to go again. The attendant came by to perform the final check and Ken, slightly panicked, said, “I don’t want to go.” The attendant looked deep into his eyes and said, “It’s too late,” and the coaster pulled out again.
Ken admitted, “I got carried away by their enthusiasm – I didn’t really know what I was doing.”
“I feel kind of sick now.”
We laughed a lot but it made me think.
Going with your gut can be perfectly legitimate. Just make sure it’s your gut you’re going with, not somebody else’s.
Anyone who thinks that enterprise sales/account management means agreeing with the client all the time is wrong. People develop wacky ideas about their own business all the time, often because they are either stuck in silos or they are too close to the issues. This does not mean it’s a good idea to implement them.
For me, the really interesting part of working with a client is understanding how their whole business works and serving that best interest, not just the interest of whoever is in charge of the RFP this week. This is the only way you become a proper advisor and someone the client will trust no matter what they’re looking for. It doesn’t mean you’ll always conclude a sale, but it does make it much more likely they will always make sure you’re at the table.
In no particular order then, here are my top reasons to say “no” to a prospective or existing client:
i. You/your company does not provide the product/service they need
ii. The client is seeking to support a business process that is sub-optimal
iii. The requirements are not clear – and neither is the expected outcome
iv. You don’t believe what the client wants – or says they want – is good for their business
Are there others you can think of, or does this list cover most reasons?