Category Archives: Human Resources

Chief Data Officer, the position you have to afford

Good Lord! Another Chief something Officer… Do you really need one? Yes you do, and you had better not wait too long before hiring one.

Chief Data Officer is a rather new function, at least with such a responsibility at that level of seniority.
So why do you need such a role? There are two main reasons for driving your data strategy at C-level: the variety of the data and its strategic monetization.

data_ubiquityFirst, data is ubiquity. Nowadays, except perhaps for a few survivalists, everyone is creating and using data everywhere, every time and, most important, without any real limitation.

Data is so abundant, that no one can grasp it globally at a single glance any more; a minimum requirement is to handle it with the proper governance, an optimum organization requires a global strategy. Considering the amount of sources (sales and client support, accounting and finance, HR, competitive intelligence, product database, industrial processes, PII, social networks, to name a few), no one in the company may own solely all this data.

A dedicated Data manager definitely is key.

data_valueSecond, data is value. All these sources, with numerous records, and an ever-growing amount of attributes, imply that investing money on the market means checking data before, either to verify assumptions or even more straightforward, to find an already existing answer that you should not be paying for.

In a fierce and global competitive world, data is an incredible asset for the company, maybe the most important one, for sure the less exploited; many actions could be improved by a sound data management, including shutting down data management silos, really sharing information across business units. As data cannot belong to one or the other stakeholder, its management ought to be lead at the highest level, at C-level.

A dedicated Data officer definitely is key.

Who is this Officer in charge of Data Management? “Meet the Chief Data Officer” wrote Brad Peters, earlier in 2014, on the site of The Economist.

hiring CDOFinally, affording a CDO position is a unique way to drive growth. For sure, you have to “make room” for this new Officer, taking away from the BU’s a part of what they believe is their power, data ownership. A significant move, that must be initiated by the CEO. And, of course, you have to hire the relevant person for the job, with enough experience to drive a global data strategy, but also with a good mix of technical knowledge and business acumen, so as to implement it. No spring chicken by any means!

I would be glad to answer any question about the CDO role, and help you define its job description. And maybe you will discover that I am a rather good candidate…

Data entry in 2014: the vivid learnings of card punching

Pondering data quality checks? Considering elaborated, automated (and expensive) schemes? Let me suggest card punching.

Punch cards? Depending on your age, you will either take me for a fool (meaning you know what a punch card is…), or simply ask “what is this?”. Let’s start with a short presentation. Basically, a punch card looks  like this:

punch_card.75dpi.rgb

This type of card has been used to record instructions for processing, starting in the early eighteenth century, especially in the highly standardized industries, such as textile; on a more romantic standpoint, it also is the basic material for barrel organs… It has then been used rather for data storage as of the middle of the twentieth century, and it has been one of the key drivers of the IBM success in the early ages of Data Processing.

But punch cards are not used any more, and this, since the late eighties… So, in this area of highly digitalized working environment, what are the learnings of such “analog” tools?

Actually, the cards themselves are not the important thing, it is how they have been used, and what we may re-use nowadays. The punching system required at least three major conditions to work, each of them reinforcing the quality of the whole process; these steps were: standardization, precise instructions and double data entry. Let me explain each in a few words.

  • Standardization has been a prerequisite to implementing punch cards, as they had to be readable from one machine to another… IBM made their worldwide success on their 80-character column standard (which was also the width of a terminal screen…). Standardization still is an asset for Data Entry, especially to provide an homogeneous frame to any operator (or operating system) performing data entry onto your systems. A well-design data entry system endorsed by the whole company is already a very good step towards data quality.
  • Precise instructions are needed to ensure your processing flows smoothly, as one cannot afford to have two people understand a process differently, even slightly. When given multiple choices, the operator has to know what to do in ALL the potential options, so that no human factor may be implied in quality. This is the step where machines are better, provided these machines do not have to do too much rendering. For instance, reading an image and entering the data as numeric or alphanumeric code still is quite difficult nowadays, even though the best engineers are working on it (see this Google project about cracking House Number Id’s in Google Street View).
  • Double data entry is the key quality control when talking about punching cards. The puncher/checker duet (in French, we name this “perfo/vérif”) has been the most efficient way to ensure correct data entry in the past, as these small holes in the card were not self-explanatory, and mis-punching was easy. So double data entry has been the best way to guarantee satisfactory levels of data quality, at least in a standard environment, with regular levels of investment (some automated systems, especially using the latest neural network techniques, may be more efficient, but definitely are more costly to implement…).

Let me elaborate more about Double Data Entry (DDE); DDE still is a very efficient way of improving quality. The chart below sums it up clearly:

DDE Error Rate

The percentage of recorded errors falls down dramatically when two people run the same process in parallel, and then compare their results. Similar rates are reached when running the process in a sequence, e.g. when someone checks the outputs of another (both methods are valid, the latter requesting a supervision, e.g. a different human relationship between the two data entry operators…).

I understand that these statistics have been collected ages ago, in times when the machine was good enough to be a repository, but not an operator itself, but I strongly believe that the simplest methods are still to be taken into account, at least where quality (customer satisfaction) is preferred over quantity (lowest costs). And even if one is rather keen on processing quantitatively, one cannot keep their customers on the long term without a decent (i.e. high) level of quality…

So, on top of more recent data processing ways, there is a lot to learn also from the card punching working methods. And this may certainly widely apply to your business… Should you have quality issues, you certainly would want to look into implementing such sound and simple working methods on top of your existing QC. And I would be glad to help you assess them.

Finally, there is still a way to use punch cards, even though in a humorous mode… Maybe some schizophrenic geek will love this way of googling: Punch Card Google… Still, the request processing looked a bit fast compared to my recollection 😉

Generation C: being forty-something may be trendy again…

Generation C. Gen C. A new buzzword, announcing the downfall of the Generation Y (which itself outdated Generation X a few years ago…). And definitely, the sign that, in our digital world, the age barrier, along with other old-fashioned sociodemographic factors, is tumbling down.

What are we talking about? The C stands for “connected”, but also for “creative”, “communicative”, “collaborative”, and its activities are driven by two other c’s, “content” and “cloud”. What is interesting in this new concept, is that it is not related to the age of the user itself. Generation X and Y used to refer to educational schemes, the X one driven by the upsurge of TV in our life, through numerous channels and dedicated programs, while the Y one was linked to the computer penetration in our homes along with the spread of an ever easier internet access and digitalized exchanges. For a parallel comparison of Gen Y and C, a very good read is “Gen C, Gen Y, Gen who?” by Jake Pearce.

Gen C is different. It is driven by usage, beyond age, education and culture. This implies at least two major consequences for the matters I like to deal with.

In the first place, this is another sign for the  lack of relevancy of sociodemographics. It is now clear that the target for marketing campaigns cannot be defined solely on the basis of age, gender, geographical location or whatever predetermined personal attribute. Target ought to be meant as a group of common interest, sharing same habits, same interests, same fads… This is Gen C vs. X or Y. How we may achieve a satisfying targeting is another (huge) question. Basically the issue may be summarized as follows: “cookie or not cookie?”, and I shall deal with this matter in future posts, showing how a long-life clustering and targeting methodology is to be performed without cookies, especially in this era of acute privacy concerns.

In the second place, then, I believe that the emerging Generation C is a sign for a new deal in Human Resources Management in the marketing area, especially where digital and new technologies are concerned. I have attended a Club Digital conference in Paris last Tuesday (Nov 5th), whose subject was “Recruitment and Career in the Digital Business: key factors of success” (more info in French on http://www.clubdigital.fr/, or on Twitter with keyword #DigitalFR). One of the key learnings is that an efficient digital strategy is to be a mix of design and technique, of guidance and execution, of marketing and IT. So of course Digital Natives in their early twenties are badly needed, but on top of their knowledge, some additional experience is required… Guidance, organization, management, in a few words, alignment with the company’s strategic resources at high level (marketing, human resources, finance, sales…) is also at stake. Understanding business challenges, deciphering client needs, organizing data management may imply more than academic expertise. And for this, one needs seniority, some business acumen, in a few words, people having already lived successful challenges, as well as experienced failures, that taught them lessons…

Thus, according to the members of the conference panel, forty-something year old Generation C managers are even a scarce resource, as the need for digital resources is immense, and the share of experienced senior managers in this area very tiny. The Geek world is now ready to welcome Oldies Goldies: this is really good news!

With my Windows phone always connected to the world, an in-depth expertise in big data management, along with my digital experience,  I should be considered as a trendy forty-something year old manager. Good start, isn’t it?