DATA REVOLUTION: Towards a Data Centric Transformative Culture

First Published on The East African.

In the recently concluded Pan- African Data Summit on Global Partnership For Sustainable Development hosted by Government of Kenya in partnership with its Sierra Leone counterpart one question stood out. How do we adopt and transform to the data revolution age?

It will however be important to not immerse ourselves in definitive terminology. BIG data will save the world. How often have we heard that over the past couple of years? We’re pretty sure both of us have said something similar dozens of times in the past few months. “Big Data” has different definitions to different people and there isn’t, and probably never will be, a commonly agreed upon definition out there. However, the phenomenon is real and it is producing benefits in so many different areas, so it makes sense for all of us to have a working understanding of the concept.

The basic idea behind the phrase 'Big Data' is that everything we do is increasingly leaving a digital trace (or data), which we (and others) can use and analyze. Big Data therefore refers to that data being collected and our ability to make use of it. The problem is this: The things we can measure are never exactly what we care about. Just trying to get a single, easy-to-measure number higher and higher (or lower and lower) doesn’t actually help us make the right choice. For this reason, the key question isn’t “What did I measure?” but “What did I miss?”

It seems we’re stuck with the term Big Data yet It’s basically a manifestation of a very real phenomenon – the datafication of our world and our increasing ability to analyze data in a way that was never possible before.

Why now, you might argue, Of course, data collection itself isn’t new. We as humans have been collecting and storing data since 18000CE What’s new are the recent technological advances in chip and sensor technology, the Internet, cloud computing, and our ability to store and analyze data that have changed the quantity of data we can collect. Things that have been a part of everyday life for decades — shopping, listening to music, taking pictures, talking on the phone — now happen more and more wholly or in part in the digital realm, and therefore leave a trail of data.

In pursuing the answer to this question, How do we adopt and transform to the data revolution age? I was privileged to draw on the insights, perspectives and questions of the amazing range of presentations made during the high level discussion in addition to the sideline discussions I was having with a couple of participants. It was worthy noting that Data mainstreaming is coming of age, Mooted against a background of emerging need to create collaborations between Government, Citizens and Companies, the partnership has snowballed to a network of more than 200 data champions working around the globe. 

At the epicenter of the triad relationship of Government, Citizens and Companies is a seismic shift that is redefining the conventional interaction of those entities. Governments coming to the realities of open governance and democratization of information access, Citizens being driven by new emerging technologies that redefine how they lead their lives and rules of the business have changed, more so businesses founded before the internet are on the verge of extinction. Many of the fundamental rules and assumptions that governed the traditional businesses have been redefined. The good news is that change is possible.  The other big change is in the kind of data we can analyze. It used to be that data fit neatly into tables and spreadsheets, things like sales figures and wholesale prices and the number of customers that came through the door. Now data analysts can also look at “unstructured” data like photos, tweets, emails, voice recordings and sensor data to find patterns.

As such, it emerged from the event themed unleashing the power of data and partnership for Africa, that Data Revolution provides one such lifeline to the rewriting the rules of the game. Moreso, Data in Action, as too much time has been spent drafting strategies on data without much happening.

One of the Key drivers towards data revolution was recognized to be development of local talent and solutions to Africa’s Native Data. With the recognition that the key barrier to Data Revolution has been inadequate technical capacity, Strathmore Business School Dean Dr. George Njenga emphasized on the need to develop local talent to meet the growing demand for Data Skills and in retrospect take data to the market in a format that can be easily accessible, understood and consumed to the last mile. Towards this, he hinted that the University has already started to focus on creating cutting edge solutions in the form of APIs and Algorithms to solve Business and Social problems ranging from Agriculture, Health Energy and Security.

Whereas its widely acknowledged that improvement in infrastructure is driving digital consumption with Safaricom CEO Bob Collymore , while quoting the state of the internet report by Akamai, revealed in his Keynote that Kenya is ranked first in Africa in internet speed Data revolution requires institutions to upgrade their strategic mindsets more than IT infrastructure.

Partnerships are going to drive the transition to data revolution with this realization on the sidelines of the event Strathmore Business School did host delegates and partners in a cocktail launch event of a regional data center that is mooted to be the first in the region. Domiciled at the Africa Media Hub, its Director Rosemary Orlale alluded that the Data Centre will create linkages with various institutions and align itself to the emerging needs.

Transition from Big Data to Smart Data, big data in itself is meaningless in its latent form and only helpful when exposed to potent algorithms that can ascribe meaning and visualized in a way that can reveal the patterns. To that extent, there has been over reliance on statisticians on matters data and less involvement of the data users who often ascribe a sentimental behavioral value to the patterns being observed. That is the role played by the data users in curating predictive algorithms hinged on their experiential rather than computation ability. Strong collaborations and trust need to be created to allow dual flow of information.

The other handicap we face is the data silo mentality. Towards this end, governments were requested to speared head the open data policy intra govt agency and spread outward.  especially ought to create an enabling environment for its departments to share data. More emphasis need to be created by all institutional players to move towards creating a rich data culture.

One central insight emerged and its going to shape the data revolution landscape- Its not about big data but smart data. We are optimistic about the potential of data to improve human lives. But the world is incredibly complicated. No one data set, no matter how big, is going to tell us exactly what we need. The new mountains of blunt data sets make human creativity, judgment, intuition and expertise more valuable, not less. Big data in the form of behaviors and small data in the form of surveys complement each other and produce insights rather than simple metrics.