You could have been on retreat on a mountain, cut-off from all communication for the last four years, but that would be about the only excuse I can think of for you not knowing the new mantra: “data is the next hot thing”.
By: Jan Henderyckx
Most likely, your management wants to get into “the BIG data“ space by hiring a bunch of data scientists. Failing to do so would create such a BIG (capitalisation intended) competitive disadvantage that we would all be out of a job pretty soon. “So why are you waiting to wheel an elephant into the IT-room?”
Is that really the first and only thing to do in order to quickly achieve a competitive advantage?
Any rom-com screenwriter may tell you that the pretty girl has always been under your nose, but you simply didn’t notice her until the end of the movie. In reality there is a huge untapped potential in many companies to get better insights and improve operational efficiency without bringing in exotic datasets or going into the uncharted waters of data lakes.
Obviously new capabilities will allow you to push the envelope, but you would be surprised how much you can get out of your current envelope without having to push it too hard.
Being data driven a mind-set, not only a box of tools.
Data Driven
What does it mean to be data driven? To me, it’s essentially quantifying the decision taking process by using relevant data points to draw conclusions. This definition immediately points out the weakness of this approach. Innovation is in some cases not the result of looking backwards at measurements, but the conscious choice to go off the beaten track. Hence the vision of Apple on analytics as they claim to be the company to deliver the product that you didn’t even know you needed.
Nevertheless, as history seems to be repeating itself and as people are not as unique as they would like to believe, there is a lot of value in quantifying your decisions.
Do you have untapped information and data insight potential?
In many cases companies are failing to unlock the full potential of the data they already capture,
either by not acting on it or by simply not connecting the dots due to their silo organisational structure. How would you spot missed opportunities? A simple approach would be to look at it from two angles:
– what processes are not capturing transactional data, and
– what transactional data is not being linked to a process?
In many cases there is far more available than what is being analysed. The bottles of water that are already available on your companies table, but remain unopened, could prove to be more valuable in the short term than having to run to a lake to stop your data thrust.
You only need to ask: “what data will bring me closer to reaching my targets?”
Having an eCommerce site, but not acting upon dropped baskets? Making a next best offer has a high probability to turn into a sale. For sure, a quick route to an increased net profit.
For every industry and business model, there are plenty of data driven cases that will help you reach your objectives and they might be closer than you would think.
So who or what has been under your nose, but has remained unnoticed till now?
Yes we can. But should we?
Any company should consider their own core values when capturing and using information about their customers even if the legal constraints regarding the use of the data allow you to use it.
Authenticity is increasingly becoming an important value for most consumers and invading in the privacy of people by (ab)using their information is not consistent with that image. So make sure to stay out of the customers personal zone and respect their desire for privacy as it might backfire on you and end up being counter productive. A recent example of a bank trying to monetize the transaction details of their customers shows that there is a limit to what you can do without being perceived as an intruder. Needless to say that there is increasing regulatory pressure to stop you from using personal data within the EU that has significant financial penalties. The data privacy aspects are fundamentally changing your data processing.
Establish a policy framework the governs data collection and use
It should be clear for any data collector or user what constraints are applicable to the information that is being manipulated. This applies to the use of the insight derived from the data point but also to basic storage and retention attributes such as encryption, witnessed logging and active disposal.
With the rise of self-service models, the proper communication of the applicable standard operating procedures is becoming more important.
Beware of the hoarder
Hoarding: the compulsive acquisition of data that is perceived by the company as having intrinsic value.
The trend of hoarding data is becoming an architectural pattern: “We will capture everything, you never know when and how it could become useful”.
There are a few issues with this approach of just capturing the world. With every piece of data that is stored, a cost and a risk are associated. One cost element is the operational cost of the storage platform. Given the rise of commodity platforms and the fact that we can often drop one of the three elements in the CAP-theorem (Capacity, Availability and Performance), the cost per GB is going down significantly. This doesn’t apply to all types of data. Any piece of information that has a life cycle needs a process that keeps the information consistent with the evolving reality. The rate at which information is becoming inconsistent with reality strongly depends on the type of information you are trying to maintain. Once you got a birthdate correct it’s likely to remain correct but email-ids or addresses are much more likely to change.
You shouldn’t be allowed to store data
unless the quality decay rate is consistent
with the effort you are willing to put in the maintenance of it.
Before deciding to store any piece of information it must be clear that your ability to get useful insight or improve operations is going to be bigger than the cost and risk associated with keeping the data.
Improper governance of information is the largest contributor to the associated risk. The policy framework is one element of keeping the risk at an acceptable level but a second element is the ability to have sufficient metadata on the information to allow it to be properly governed.
Metadata for survival
Just capturing the data without properly defining and attributing core metadata is creating a huge risk. You simply can’t apply the right policy if there isn’t enough information about the data point. In most cases, regulatory compliance forces you to define the lineage of the information that you use and there has to be proper ownership and accountability. To be able to answer these questions, the information needs to be described and not just captured. Next to the regulatory question, one needs to address the “fit for purpose” element. Is the quality of the insight good enough to trust the decision that you are going to make based on the information at your disposal? How do we judge if the accuracy is within acceptable boundaries without properly defining the dataset that is at the origin of the insight? Making the right decision assumes that you understand the data. The latter can’t be done without proper metadata.
Yes we Can become data driven
Being data driven is not a far-fetched idea and many companies have proven the value of getting the full potential of the information in their organisation. It does however require significant change in mind-set of the organisation as you can’t simply install the software and hope for the best.
Neither is hiring a bunch of data scientists the complete answer. It requires a coordinated effort throughout the entire information life cycle coping with the planning, capturing, maintenance, use and disposal of the data.
Jan will present his information strategy methodology with practical examples and guidelines in a two day seminar “Defining and Executing Your Information Strategy”, scheduled on 3-4 March 2015 and 24-25 September 2015 in London.
About the Author
Jan Henderyckx, a highly rated consultant, speaker and author who has been active in the field of Information Management and Relational Database Management since 1986. He has presented, moderated and taught workshops at many international conferences and User Group meetings worldwide. Jan’s experiences, combined with information architecture and management expertise, have enabled him to help many organisations to optimise the business value of their information assets.
He has a vision for innovation and ability to translate visions into strategy. A verifiable track record in diverse industries including non-profit, retail, financial, sales, energy, public entities. Contributed to better streamlined and higher yielding operations for some of the leading businesses through a combination of creativity, technical skills, initiative and strong leaderships. He is a Director of the Belgium and Luxembourg chapter of DAMA (Data Management Association) and runs the Belgian Information Governance Council. He has published articles in many leading industry journals, and has been elected to the IDUG Speakers Hall of Fame, based upon numerous Best Speaker awards. Jan is Chair of the Presidents Council DAMA International.