Connected data is more than another opaque industry buzzword. Used correctly it can help give both deeper detail and a bigger-picture understanding. Used incorrectly it can confuse or, worse, weaken your strategy. Our jargon-free Q&A with new Managing Director Julian Dailly shows how it could be useful to businesses from start-up to multinational.

What is connected data?

Connected data denotes multiple descriptions of the same thing, be it a person, an event or a place, which enables a better understanding of its nature. Connected data can simultaneously reveal further detail and prove a bigger-picture context.

Connected data enables people to look at the same data in multiple ways; uncovering new perspectives and possible courses of action. 

Why is it important to businesses today?

It is a source of potential advantage because it helps with taking more targeted action. 

However, it’s also a potential source of disadvantage if it overwhelms, confuses and paralyses businesses who don’t understand how to best use it. 

What kinds of data are being recorded?

Organisations are collecting an increasing amount and variety of data, enabled by improved data capture, processing and analysis technology.

Chiefly data recorded falls into 4 buckets:

  • Behavioural data – what people do. This might be how many people go to their website, what they buy in their stores and how they interact with their brand online and offline
  • Perceptual data – what customers and potential customers think and feel about a business, brand or organisation
  • Financial and operational data – how their business serves and generates revenues from its environment, sometimes drilled down to a specific product, location or sales channel
  • Employee behaviours and sentiment – both in terms of their productivity and their commitment to their employer

In what ways can these sets be cross-referenced to create insight?

Principally these data fields are combined in the same way they have been combined for decades; by linking “like for like” fields in different datasets to cross reference one set of results against another. This can be done to multiple datasets to create enormous “big data” repositories through which queries and can be run to uncover patterns, prove hypotheses, manage performance and discover new insights. These could be about the underlying people, events, places and phenomena being looked at.

What level of insight can be achieved this way?

Ultimately, the potential level of insight is infinite yet depends only in part on the breadth, accuracy and accessibility of the data. By far the most important factor in extracting powerful insight is the brainpower asking the questions. 

A very smart interrogator can find very profound insights from a small amount of data if they use the right perspective. Conversely, organisations that have access to inordinate amounts of data can continually fail to derive useful insights because they are unable to look at it in ways that reveals never-before seen observations. 

Typically, the more “institutionalised” an organisation the harder it will find the insight discovery process, due to rigid historically-oriented ways of thinking. Newly formed companies are more cognitively flexible and more likely to look laterally at the data they see, which often is in far shorter supply but used to greater effect. 

What are the tangible benefits to a business of doing this?

The benefits of connected data, and the insight that comes from it, is the ability to pursue strategies other people would not consider because they don’t have the evidence to justify them.

This is a source of competitive advantage as, because risk is perceived uncertainty, it enables companies to pursue high reward strategies at lower levels of risk. So in long run it helps them generate superior shareholder value.

Is this process expensive?

The process can be either expensive or cheap, chiefly dependant on the type of data to be analysed and the expertise of the brainpower set to it. Google Analytics, web traffic data, financial and operational data can be obtained at virtually zero cost. Bespoke datasets, such as customer surveys, consumer opinion or complex data about how specific sub groups think feel and act can become costly. 

There are two important points to bear in mind:

  • Firstly, generally the more exclusive a dataset the greater its value as it can be used to develop truly unique strategies that create competitive advantage. 
  • Secondly data and insight, used correctly as a source of potential advantage and economic gain, should be seen as an investment. People that see data as a cost have already fallen at the first hurdle. For example, a business with sales of £50m needs to learn something that enables it to increase its prices by just 0.2% to generate a 100% return on investment from a £50k insight project. This is a far higher ROI than required by most FTSE100 business to accept an investment (typically 15 – 30% ROI). 

Which companies can get the most out of connected data?

Virtually all companies can benefit, but many don’t and some fundamentally can’t and never will. 

The old adage that ‘information is power’ still holds and those who embrace this mantra benefit from doing so.

The only companies that will genuinely struggle to get a benefit from data, information and insight are those that face zero competition, because they have no need to generate competitive advantage. And, those companies that are unable to accept recommendations developed through the analysis of data. Typically, these companies, which are usually driven by strong personality-led cultures become frustrated by the perceived need to cede their power to “what the data says” over “what we experts know to be true”. 

This is one of the biggest strengths and weaknesses of data driven insight: it divides audiences into those broadly “for it” and those openly or otherwise “against it”. Those for it see it as empowering and profit generating and those against it can feel threatened by its opaque algorithms and capacity to challenge instinctive decision making of traditional leadership models. 

The flip side of this is these companies are the ones from whom market share is usually stolen by younger, more open minded competitors willing to look at the world through a fresh lens.

What are your top tips for success with Connected Data?

  1. Remain open minded for as long as possible about what the data is telling you to do
  2. Don't collect and analyse data without a purpose. Analysis and insight carried out in a silo'd vacuum leads to great ideas no one is prepared to act on.
  3. Try to combine as many diverse datasets as possible. A diversity of inputs is the strongest predictor of a powerful insight.
  4. Do not collect too much data or your organisation can become overwhelmed. For example, try to match the frequency of insight bursts to the speed at which decisions are typically made so people get inputs when they need to make decisions.