Let’s talk about BIG DATA! My name is Anthony Reardon and I am a modern business consultant who you might catch talking about emerging trends in technology, business, and so on. I also host this series called Nor Cal Explorer to showcase interesting people and companies that make Northern California great.
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Since my niche happens to include Silicon Valley, you can imagine who I come across, but one thing I will almost never talk about is BIG DATA! I tend to avoid the subject and companies associated with it because I flat out disagree. This is not for lack of engaging people on the subject, just that those conversations are usually not pretty. People putting out the propaganda on the “machine learning” field tend to prefer associating closely with the hype (and distancing themselves from the critics). Today is going to be somewhat of an exception or outlier case study.
You could say the philosophical difference comes down to qualitative vs. quantitative. I am personally a champion of qualitative, and it’s only natural for a lot of data people to try to upsell themselves at the expense of my kind of thinking.
I was reading an article this month on someone talking about Human Resources and retention strategies – really making a case for
- directly relating to people, and
- asking them better questions.
Then this data guy steps in and says he totally agrees. So I thought to myself, “What’s this?” because it’s rather unusual to see someone switch camps like that. What this guy was actually saying was this same qualitative logic is aligned with what he is seeing in the quantitative HR sector – I guess
- data relating insights more specific to key personnel, and
- better information about what will influence their decision to stay or go.
It was just a little too irresistible for me. I had to reach out to the guy and call his bluff – you can’t use a qualitative argument to support your quantitative solution, lol! To my surprise, this individual actually took the time to discuss the issue with me. He clarified what he meant to say, explaining to me his very rational understanding of the roles and benefits of quantitative and qualitative – especially how they can and should be mutually supportive rather than mutually exclusive.
This was one of my first conversations with a data company where I have to say I was actually impressed. It isn’t that I am fundamentally opposed to machine learning, it’s that my views on the subject are actually very sophisticated – you could say more rigorous. See my comments to the following Fast Company piece last year.
There is a phenomenon I have observed unfold in the digital strategy space where you’ve seen creative firms within the traditional media marketing space crossing over to web, tech firms trying to cross over into advertising, and so on. I’ve found most of these efforts to be very speculative, reaching beyond the scope of what they were actually capable of being good at, and jumping on the trendiness of “new” business solutions. Much of what I have seen as a result is seriously inferior work in one or another area these companies try to branch out in with the hope of maintaining their market viability.
I suppose you might say I have been especially sensitive to this phenomenon because my digital strategy thought-leadership stands alone without the technology. It’s not that I am a purely creative or imaginary philosopher, but that my background comes from systems engineering disciplines for industrial production, performance optimization, organizational transformation, process improvement, etc. If anyone actually understood what I am talking about, they would be more accurate to accuse me of being analytical, lol! It is almost a coincidence how this evolution has brought me around to digital strategy, but I can argue it’s all the same thing. A great thing about it is I usually have something of a unique perspective on things.
I enjoy researching similar services out there, and honestly it’s somewhat frustrating to see the same values I have to offer becoming the rallying points of technology solutions providers. I will occasionally reach out to these agencies with a genuine interest in connecting, but they will often disregard me for not being a true-believer in the tech solutions, or avoid me under the assumption I am a competitor out to steal their knowledge and book of business.
A common way these businesses have gone about explaining what they do is to describe themselves as “left brain/ right brain” balanced. That is to say they understand the value of aesthetic web design on customer facing applications for instance, but are also able to build in the analytic tools for the people serious about running an effective business. Did I mention that I find this kind of proposal extremely annoying and that it instantly raises my bullshit flag every time?!
I mean, it sounds great, makes the agency feel good about itself, gives prospective clients an easy to understand organizing idea- but most of the time it strikes me as a kind of bluff. You don’t know what you are talking about so you cover all your bases, or you want to force your solutions, maybe covering up some deficiency, that perhaps if you say something then it will be true… I get real critical when I hear that value proposition.
If something you claim draws out my scrutiny, I will usually call you out on it, but I mean this in the most sincere and respectful way. The appropriate response is to answer the challenge, qualify your logic, explain yourself. If it’s good, I will credit you where credit is due. If not, then I can help you. However, if you decline the challenge, I just might make an example out of you. If you are too good to talk to people, then I think you are probably not going to go far in this emerging social landscape. “Social” – It means “People”, and it is easy to test. Just reach out to a company with something intelligent, and see if they come back at you with some kind of intelligent response.
I guess my point is you can only get so far telling people what they want to hear. As far as I am concerned, what “really matters” is if it works. Now you can actually get some progress by giving people what they want, even if that is just the appearance of what they want. You can even get some progress by getting creative in how you define and measure progress, even if you are really not getting anywhere. So my concern extends even further to whether or not something “really works”, and how you could “really know” it works. For me this comes down to immediately evident results – just like testing some company that offers social intelligence solutions to see if they have any social intelligence. All you need do is try talking to them and you should know pretty much right away.
You see, you can “qualify” this kind of thing without BIG DATA all day. There’s no left brain / right brain about it. If it works, you will be the first to know. If your goal is to increase the sales of something, then you will know because that something will be flying off the shelf. It doesn’t take a rocket scientist to know if a rocket works or not. It either gets there or it doesn’t. So there is a flipside to the more popular BIG DATA arguments, but if you are discerning enough to let new information or insight on some subject change your mind (if presented with a superior argument), well then you have just as much of an opportunity to prove the value of data solutions.
Yep, and space travel isn't new either (for you millenials without a clue on anything that happened over 20 years ago). It really wasn't that long ago we were shooting monkeys up in to space - just to prove we could do it, lol! The question is not whether or not data has anything to prove. I always tell people you only have to go back a couple decades to when people were using flipcharts and graphs in board room meetings. There is nothing new about the concept of data in that sense, even with the advent of technology – it’s a way of packaging business information in a way decision makers are already accustomed to and prefer. If you really want to see a challenge, try presenting these same people with qualitative solutions with no data whatsoever to support. For some extra fun try presenting solutions that contradict their data, especially if they really like what their data is telling them.
I used to be heavily involved in process engineering and continuous improvement. These represented areas where companies had an opportunity to improve by doing things differently, however, that necessarily implied breaking the pattern of data-based decision making they were accustomed to. There simply was no way at the time to quantify intangible improvements involving incremental steps over a period of time spanning years- from a data perspective the business leader might be looking at an expense invested and expecting a return on that investment in a short quarterly time frame.
Along that same line of thought, data gathering implies a passive activity where a decision-maker might have no other role than to make a decision on the information that comes in. However, for continuous improvement programs, we realized you needed to get senior leadership buy-in and proactive involvement – in other words, to effect change we literally had to take business leaders and disrupt their comfort zones. There were no plug and play solutions.
Now my contemporaries all seemed to arrive at a consensus of understanding that to implement these kinds of organizational transformations, you had to install a cultural transformation- teaching people a bunch of abstract ideas, getting them to apply judgment in the new context of principle aims, and overall looking to bypass the more difficult root problems- instead going for low hanging fruit to help build confidence. I have always disagreed with this too. If you are going to do something, then why can’t you see that in terms of immediate impact, results, profitability, etc.?
You see what I am saying here - I am not arguing against data, but rather have been calling for it to catch up. We need better ways of gathering data, pulling meaningful information from outside parameters we are used to, new vocabulary for discussion of new unprecedented processes, and ultimately I think we’re talking about some serious advancements needed in the sciences of communication and decision-making.
I’ve been watching the data field from a distance for some years now, and can generally say that most concepts are heading in the wrong direction. Like I said, sometimes I wish there were a way to “quantify” that! However, I may be able to “qualify” it anyway. In the video above you have a recent market positioning piece where IBM promotes itself as a leader in BIG DATA and analytics. This is clearly targeted at “corporate grade” solutions, and that is a commitment that has always defined IBM. I would call that a quantitative approach. In fact, in the video below, you can see where Apple made a point of differentiating itself to “personal grade” solutions- personal computers right? I would say that strategic decision was qualitative in nature. Think about it.
I can qualify it by what I am putting my focus into as a business consultant. That is, where BIG DATA might seem to address a demand by companies for economies of scale – whether that be part of automation to reduce costs or market growth to increase revenues - I advise companies to do the opposite! Yep, I say invest in personal service and put in the effort to make your relationships count. It’s not what a lot of companies want to hear, and certainly it’s not what people are using as the selling point for BIG DATA solutions, but I will challenge that all day by saying it’s precisely what the customer wants to hear. Customers don’t necessarily want to be “a number”. Today they are more likely to want to be “the one”.
This is probably where my intuition started ringing about hiQ Labs. They are using data to “scale down” to individual people that matter and deserve special attention. Yes, they talk about attrition vs. retention, and I understand the corporate angle for that pitch, but there is something much bigger underlying this- and I just know it, lol! You might take for granted their tagline as so many companies throw out things that sound good – talking a talk but walking another walk. They say “People Analytics”. YES! Now that’s what I’m talkin about! Walk with me…
First of all, I always say “It’s not so much about the technology, but rather about the people that use it”. I’m way ahead of my time on this. I might get criticized for being purely qualitative here, but I truly believe this is the key to results, and I arrived at my conclusions from a systems engineering approach to problem solving. I will just jump here to one aspect which is the psychology of decision-making – how people deal with challenge, choice, and conflict. There’s actually a book on the subject, but I mention this to draw out the importance of how people make “significant decisions” like purchasing a car, getting married, buying a house, choosing a company to work for, maybe deciding to start their own business. At this level you can deal with a problem like who in a company is likely to quit, how you can have an idea of who they are sooner rather than later, and what you may be able to do to effectively intervene.
So what is so profound about this? Well, obviously in Northern California there is a major issue about attrition and competition for tech talent. It’s not surprising for me to see a Nor Cal tech startup focus in as a solution to this problem. In fact, my initial impressions of hiQ Labs were not flattering, lol! What I see in their digital strategy is more about attracting data scientists, appealing to investors interested in the BIG DATA space, and inviting media exposure by tech business journalists. Sorry, but I can see right through that kind of stuff. Not that it isn’t smart in its own right, but filter this through a customer perspective- what matters to people and how their product or service can make a difference in peoples’ lives- I see most of what they promote as “surface level” in that respect.
Clearly hiQ Labs is not the only company in this space. So this kind of begs the question about what differentiates them. In the above article, it is pointed out that many mainstream enterprise management and customer relationship management software vendors are folding in HR related analytics into their suites. According to this piece, the main differentiation for hiQ Labs is they are also using external data for a predictive capability that is four times more powerful. More powerful than what though? The other companies look primarily concerned with the business venture of analytics – that is, they seem more concerned about the technology, and not really about the people that use it. To compare powers on that scale might be an indication hiQ Labs cares even more about the tech business and even less about the people, lol!
Like I said, the thing that stands out to me is their focus on “people analytics”. I think this may be a decidedly different field than BIG DATA although there is obvious overlap. They do touch on it when talking about things like combining internal and external data sets. I don’t think they are pitching small data, or even exclusively external data, but maybe making a point of mentioning these things in combination. An analogy comes to mind on using two lenses in a telescope – near and far – to focus in on some desired object and have superior clarity on the subject.
Gosh I know we start getting back to that whole left brain/right brain thing and my skepticism starts to rise back up again. On the other hand, this does kind of address the shortcomings in purely analytical logic – that you need to be willing to put it to the test with empirical evidence wherever that may be, that you should be vigilant in finding information that can prove, disprove, and otherwise strengthen the validity of results. Somewhere in there you also have to make a point to remember why you are doing something, and that is always going to come back around to “people”.
One more look into what I am doing on a qualitative level and perhaps you can appreciate why I am impressed with the potential of hiQ Labs. I promote an idea I call “social modalities” which is a way of breaking down social systems into discrete and interoperable modes of behavior – personal, professional, organizational, and business. Not to go into detail here on all that, but I will say I see hiQ right there at the intersection of professional/ organizational. It is significant to me in coaching up companies how they should relate to their employees, as well training professionals on how to contribute greater value to their teams.
For instance, I might recommend companies help their employees better promote their career successes on social media, even if that means those people might find better jobs. By that action, the employee might realize they cannot find a better company to work for. It might sound counter-intuitive, but I wonder what the retention data will reflect.
Or, I might advise employees to be more proactive in networking to find someone that can do their job better – building on what they have established and bringing in new skills and energy. What kind of professional works to phase themselves out of a job, aren’t they supposed to make themselves indispensable and protect their spot- even if that is not in the best interest of their company? That might be the kind of modern professional you want to recruit, retain, and promote in your organization.
In such exercises can be found lessons that transcend all the way to customer experiences – how customers relate to companies, how business becomes personal. I’ll just throw this out there but HR has got to be probably one of the smartest entry points to introduce a company to “people analytics”. If you can train a company to take care of their people internally, instead of instituting blanket policies - to be more precise, targeted, and impactful – well I think you would then be in good position to help a company do the same kind of thing externally within their markets. The technology can certainly be helpful, but someone has to make the point that it still comes down to people – so what better place to do that than in Human Resources! It reminds me of something I read in a Jack Welch book about HR Director becoming at least as important a role as CFO.
Something tells me hiQ Labs might be a company to keep your eye on. I would not have paid them a first thought if it had not been for someone on their team supporting a qualitative argument on a public forum, and not a second thought had they failed to engage me in a one-on-one discussion about it. There may be something different going on here.