Emerging Data-Phenotypes & Organisation Design.

On a recent listening trip to Asia-Pacific, an interesting sub-text to many of my conversations was. that most of my counterparts were not impressed with Big-Data or even Data Analytics!! Everyone has access to Big-Data and Data Analytics, but many have confided it has not translated into the bottom line or better work flows.

To squeeze more milk from the data analytics stone, organisations supplant “Big Data/Analytics” with “Business Intelligence”, “Predictive intelligence” and recently “Prescriptive intelligence”. CIOs felt that the applications of BI were so vast, buying everything from every vendor should cover everything.

But something was missing,A conversation that I had with the “Head of Innovation” stood out regarding the challenges of integrating disparate data. Getting a “true picture” would be impossible apparently as data was so diverse across such a large organisation and BI was at best “guesstimated”. This fragmentation he kept alluding to as “Data Silos”, but importantly he described how they were being created by its own people and had developed a life of its own.

The Dark Matter of Data:

CIOs like him allude to this ‘people created’ data that had in the last 2 years become equivalent to the entire data that an organisation has collected in the past 50! This people related data or in today’s world “Streaming Data” is replacing and offsetting Legacy Data sets, which in turn are changing organisation structures and processes, and challenge organisational responses in real time.

This tsunami of data created by its people, (e.g. sentiments, behaviour, workflows) that some term as the Dark Matter of Data where real intelligence can be mined, but lies largely undiscovered or uncovered. Some have suggested that to cope with this tsunami of data organizational structures will need to change and processes or work flows used to design organizations will be different However, these pundits differentiate big data from purportedly relatively slow-moving, people linked data. I argue that we need to address People Streaming Data and Legacy Data Sets symbiotically.
To quote: “…..The processes by which organizations are designed, however, will be relatively unaffected by big data. Instead, organization design processes will be more affected by the complex links found in people data.1

How does People Data create these Data Silos?

As you read this post you agree or don’t agree with many of its positions. We humans select, and act on data what we perceive as useful or relevant, but for the most time, ignore certain data, or a selective INNATTENTION to detail.2 Data Silos then get created by the business user’s data PERCEPTION or need. These cognitive work flows that emerge out of this vortex of perception-policy, I venture to call is a user’s DATA PHENOTYPE as they interact to the world around them. Perception Data make Business Stories and users need a BI system that they can relate to.

The Trap of the Better Mouse Trap.

SBuyers and Sellers of big data products can harp around features; I noticed this can lead to product comparison and perhaps fall into an echo chamber of jargon, product features comparison and a beauty contest. Some of the people I interviewed felt this product comparison only adds to the current fatigue and jaded discussion within Big Data and Big Analysis that I referenced earlier, by trying to figure out who has built a better mouse trap or bang for buck- i.e. Price. So, buy everything from everybody. Value is different proposition.

Thinking Design and Designing Thinking.

Organisations are wanting to DISCOVER how their hearts beat, how they tick. What are the processes that work and what do not. What is the true cost of the business and can departments innovate and run at their true clock speed. How can departments reduce the noise to signal ratio, how do People/Departments in their Data Silos interact symbiotically? Indeed, how do they fit into the larger ecosystem called the Global Economy. But the question asked of me was : “Can internal and external processes be identified and PROCESSES designed to get the organisations to “hum”?

Putting People First

Shifting focusing to the end-user, shifts the discussion away from providing reports that “one size fits all” instead to what is relevant and intelligence to the end user. Conversely, how does Perspective Data feed into insight at the top, the CXO, the Board. The trap of product focused thinking believes multiple departments or people can use the same tool, the same data, the same visuals when just a few relevant insights built around their data phenotype can reveal and show a higher adoption of BI in the organisation.

The bottleneck to better ROI on Business Intelligence Systems I see is that many organisations are building BI around “features” (Products), not work flows or Processes. It’s the data perspective that matters, not the amount of data analysis presented. Presenting 1-2 need-to-know insights - makes that the focus of the user’s business story. Data Perspective is borne out of user context. For an example of how individual or department Business Stories/Silos interconnect with perspective visuals. Or reports that lack information regarding diet habits that could result in better preventative measures for the onset of diabetes, which could translate back to the actuarial model and offer variable premiums for diabetics based on lifestyle? Another problem discussed is that despite good BI being in place, rapid deployment or portability of across 1000s of users in real time remained daunting.

If an organisation wants to get data out (push) and get data in (pull) how fast can a system be deployed or designed from a few 100s, to 1000s or even millions? Is it surprising then that organisations all the the creation of data silos because it cannot deploy a good BI across 1000s and indeed, a good BI system adoption gets smothered? For An example of rapid deployment across different end users, (Self Service BI) in real time, from 10s to 1000s Tim Brown Captures the synthesis of People and Legacy data well: “Design thinking puts users and their needs at the centre of applications and at the starting point for developing any new product or solution. Big data and design thinking draw on solution-focused, action-oriented processes, and people who are not necessarily designers apply them more broadly in the context of business.3

Slinger, Morrison
Eric Fromm, To Have or to Be.
Tim Brown, CEO -IDEO.

Tags: Big Data, Analytics, Data, Business Intelligence, Self-Service BI, Data Silos, Design Thinking, Data Discovery, Business Story, Ac-hoc Analysis, Advanced Analytics