As you might expect, the word “data” loomed large in the British government’s recent Integrated Review of security, defence, development and foreign policy.
The first few pages alone feature pledges ranging from creating a “new Situation Centre at the heart of government, improving our use of data and our ability to anticipate and respond to future crises”, to “establishing the UK as a global services, digital and data hub” and vowing to be “at the forefront of global regulation on technology, cyber, digital and data”.
Of course, this strategy is hardly the first to feature data heavily. Seemingly at every turn, defence strategy references the urgency of being more “data centric”. But will data ever be as a valuable an asset to the military as weapons and ammunition? 

What actually is data?

Let’s just take a step back and clarify what “data” actually means.
It can be used to describe a wide range of facts, measurements, observations, numbers and words, and its volumes can vary from minuscule to truly massive. The sheer volume available now is already overwhelming, yet people and organisations have a seemingly insatiable appetite for more.
But to maximise its value data needs to be understood and not looked at in isolation. The real art is “smirging” together different bits. You could call this “enrichment” but I prefer “smirging” as it gives a clue as to the apparent mess of colliding data sets of differing provenance and format. One way to think about its value is to break it down by the types of questions it can be used to answer.
Descriptive Analysis can be used to determine what happened, whereas Diagnostic Analysis is used to determine why it happened. Predictive Analysis uses patterns from past data to try and determine what may happen. Prescriptive Analysis identifies what course of action would be best to take. The insights from this analysis can transform operations by enabling powerful data-driven decisions across all industries or markets.

Putting the brakes on

But if data has the potential to deliver so much value, why hasn’t every organisation already unleashed its full power? Unfortunately, there are some common hurdles. For example:
  • Lack of data literacy: Organisations are short of the in-house capability to understand what is possible, how it can be achieved, and what data needs to be captured.
  • Lack of data skills: Organisations don’t have the technical or analytic skills at the scale required to realise data value.
  • High data volumes: Organisations lack the resources to collect and store all the data being produced, or don’t know what data can be discarded, and what should be kept. 
  • Legacy systems: Organisations’ technology platforms are often not compatible with modern data collection and processing requirements.
  • Governance and security: National and industry regulations control which data can be stored, how it should be stored, when it must be deleted, who may process it, and who may control it. 
And in Defence, there are a whole other set of complexities to contend with. These include:
  • Multiple domains. There may be a very specific definition of domain or other partner such as supplier, country boundary and perhaps also purpose, such as operational frontline or back office support function. 
  • Unpredictable network bandwidth. Hence the need for investing in a comprehensive digital backbone. 
  • Technological array. Every imaginable bit of technology is out there somewhere across defence IT. 
With all these complications, there’s a desire to wave a magic wand and fix it all. There’s a huge array of cutting edge analytical tools and platforms on hand but actually, we’ve found that the main effort needs to go into laying the foundations for getting to that point in the first place. This may involve sorting out enterprise data architecture, finding common ways of describing the data or agreeing standards for its transportation.

The value of experience

This is where extensive data experience comes into its own. To determine what data needs to be collected, how to best analyse it, what the output of that analysis will be and how it can add value to your organisation for a particular use case. This can be done in roughly three stages:
  • Phase one – mobilisation and preparation: A sponsor is identified to champion the specific data cause. The scope, objectives, legal, policy and governance aspects are established. Any technology is set up whilst the business problems are considered in more detail. The data necessary for collection and analysis is identified, along with acquisition method.
  • Phase two – developing data analytics and demonstrating the value of data. The team acquires the relevant data and determines what value can be derived by combining and analysing it. The team loops through several iterations of tasks to obtain and validate data before the data is transformed, prepared, integrated and possibly smirged.
  • Phase three – the engineering of an enterprise data solution. This is effectively the ‘productionisation’ of the capability into a repeatable, robust process or platform. Taking what is a proof of concept into a supported and enduring data service.
Organisations are increasingly becoming aware of the power of data to help them find competitive advantage. However, as the volume and variety of data increases and the regulations governing the storage of data evolve, understanding what should be collected, how it should be stored, and how it can be analysed is becoming increasingly complex.
As confirmed by the Integrated Review, it’s clear that the military is dramatically increasing its understanding of the power of data. Whether it ever becomes as appealing to its personnel and leaders as the things that led them to sign up in the first place is something for only them to decide. 

About the author
Mivy James is Digital Transformation Director at BAE Systems Applied Intelligence

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Mivy James

Digital Transformation Director, BAE Systems Digital Intelligence