3.3 Explain how to develop a cohesive set of conclusions/findings

Why do organisations gather data/information and intelligence?

Before we move forward to consider how to develop a coherent and useful data analysis/research findings (business intelligence), let’s pause at this section of the module and ask ourselves: why are we gathering the data? Because, the answer to this question will determine how a consultant/researcher should approach their task. What information types do they require? What are the likely sources? What tools and infrastructure will be needed? Where will activities and findings be safely stored? Typically, firms and organisations go about researching and gathering data in order to:

• To achieve competitive advantage • Better information can help target scare resources and/or reduce duplication • To achieve prior warning around a major incident which could save lives, prevent injuries or huge financial losses • Identify threats and exposure to risks • To detect and prosecute criminal activity • Acquire sensitive knowledge to ‘control’ the subject or situation, typically, with important negotiations in mind (Bingley: 2015)

All of these reasons boil down to one single overall aim for gathering intelligence: to reduce uncertainty.

Case Study: How is the intelligence cycle organised?

Like most conceptual applications in the security sphere, there is no single, authoritative conceptual model that can be said to illustrate the end-to-end development of an intelligence product. Given the kinetic nature of security management scenarios, and vastly differing operational conditions from task to task, there simply cannot be a one-size-fits-all approach. But the CIA model

outlined below does draw for us a convenient and plausible intelligence model that is often emulated by other organisations:

Figure1: The ‘Action-on’ CIA Intelligence Cycle Model:

Source: Goodman and Omand (2009): https://www.cia.gov/library/center-forthe-study-of-intelligence/csi-publications/csi-studies/studies/vol-52-no4/teaching-intelligence-analysts-in-the-uk.html

For any organisation, public or private sector, business intelligence cycles tend to include at least four core components:

Direction: The beginning of the process. The client informs the Intelligence Manager what they need or wish to know. A recurring challenge is ‘information void’, whereby decision-makers often do not know enough about what they need to know, in order to give clear direction in the first instance. This is because they begin the task with a negligible amount of useful existing intelligence. This stage can also be used to issue feedback and change tactical direction in response to prior intelligence shortcomings.

Collection: Raw data and information is collected from a variety of sources which may help intelligence analysts at the next stage of the cycle. Sources could be: Geospatial (GEOINT), Human (HUMINT), Imagery (IMINT), Intercepted Digital Communications (SIGINT), Measurement and Signature (MASINT), Open Source (OSINT). For business, marketing analytics and search engine optimisation analytics will be critical insights to develop and grow the business.

Processing/Elucidating/Analysing: The human analysis and assessment of available information, collated, synthesised and processed into timely, relevant and accurate intelligence. Successful assessment and interpretation of data by intelligence analysts is akin to correctly piecing together available jigsaw pieces, within a given timeframe, to establish the most accurate situational picture possible for the client.

Dissemination: The process of moving and communicating the actionable intelligence reports to the client and/or any given end-user. This must happen in a secure manner which will not compromise any of the three prior phases of the intelligence cycle. For example, a detailed report about a competitor’s successful product launch, should only be circulated to a specified audience. In some environments, including IT and Banking, it is appropriate to classify information as confidential or not-so, in order for specified audiences to receive the information. IT might also set access controls, in which certain team and individuals have access to key server areas or shared drives.

Information Hierarchy:

Of course, production of any relevant information and appropriate knowledge sharing can be very useful to business and Government decision-makers within any commercial or regulatory operating environment. But merely gathering useful information, or employing company researchers to do so, still potentially falls far short of the specific benefits that a disciplined Business Intelligence processes can usher in. Business Intelligence is the impartial pursuit of insightful and highly refined information that will reduce operational uncertainty for organisations. For example, reports from daily newspapers may well tell us that

hackers were attacking IT networks run by commercial banks. This will, indeed, be very useful for a security manager in Manhattan, New York. But they might not be able to action this information other than to issue a general warning to staff, perhaps to urge them to be more vigilant and report anything suspicious. Yet more specific and insightful knowledge, such as prior methods, trends and timings, the most popular targets, the scale of expertise and research used by perpetrators, or if there was a suspected underlying reason why some banks or staff networks were prioritised as a target, could all be fairly construed as snippets of actionable business intelligence.

As such, business intelligence is considered by many to sit at the apex of knowledge management models, and is often referred to ‘insight’ or ‘wisdom’, as we see below:

Figure 2: Knowledge Hierarchy Pyramid

Source: CERT Guidance into the DIKW knowledge hierarchy model, accessed at: https://www.certguidance.com/explaining-dikw-hierarchy/

Reflective Exercise 1:

In your private notebook. See the Knowledge Hierarchy above. Now consider a project that involves researching data gathered about a competitor’s successful new car model launch. Explain in more detail how your team would move through the stages of business intelligence research (see Figure 1 Intelligence Cycle) in order to produce some Courses of Action (CoA) that you recommend to your Executive Board. (CoAs should be based on advanced, insightful, refined information that would be considered ‘Wisdom’ within Figure 2.)

Knowledge Hierarchy explained:

Data: Raw information gathered or received from a third party which has not been analysed or subject to any form of processing.

Information: This could be data has been sifted or subject to a basic to moderate degree of processing such as translation, cross-referencing, formatting, comparative analysis and double-checking.

Knowledge: Supporting information, or pre-existing understanding and comprehension, which is required to help assess, evaluate, organise and process incoming data and information into actionable intelligence.

Intelligence Outcomes:

We have seen that intelligence products are principally designed to provide critical insights into defined ‘subjects’ or target areas. Demands for intelligence can often come in the form of Priority Information Requests (PIRs) or slightly less urgent Information Requests.

As we have established, intelligence is information which is refined, assessed and disseminated usually with the intention to trigger or assist certain action by the client/end-user. Conversely, intelligence can also be used to keep a watching brief on potential adversaries, or monitor certain threats and risks in order to confirm NFA. Intelligence gathering therefore helps to provide context and

clarity to our decision-making. It can help to clear a logical pathway through an operating environment riddled with uncertainty; a domain that the great Prussian military strategist Carl von Clausewitz famously described as the “fog of war’ (von Clausewitz revised: 1993). Forms of intelligence products can include:

• Identify incumbent organisational and personnel weaknesses and Courses of Action (COA) • Identifying risks to employees and the organisation through Threat

Assessments • Target/Competitor Group Profiling (TGP) and Monitoring • Issuing Early Warning to decision-makers.

We have shown that providing such information to decision-makers must be evidence-led and fulfil certain criteria to refine its raw elements. Also significant is the manner in which critical information is presented. If key information is not presented in a convincing and persuasive manner, then all of the hard work that went in to the research will be lost within the commercial ‘fog of war’. What’s more, a consultant conducting a poor presentation, or who appears poorly briefed when asked a question, will struggle to find that they have future work promises fulfilled. In presenting information findings, ensure that it runs in a coherent manner in alignment with the stated company strategy (Rumelt: 2012).

Reflective Exercise 2:

Take some time to read Michele Kiss’s (2018) article – 10 Tips for presenting data at the following URL: https://resources.observepoint.com/blog/10-tips-for-presenting-data

In your own private notebook, consider and reflect upon your own skills. How effective are you at presenting in each of the ten ways that communications expert Michelle Kiss advocates?

Further Reading:

CERT Guidance (2019) DIKW Model: Explaining the DIKW Pyramid or DIKW Hierarchy. Accessed on 19/1/2020 at: https://www.certguidance.com/explaining-dikw-hierarchy/

Rumelt, R. (2012) Good Strategy, Bad Strategy. London: Profile Books

References:

Bingley, R. (2015) The Security Consultant’s Handbook. Ely: IT Governance Press

Goodman and Omand (2009): Teaching Intelligence Analysts in the UK. CSI Publications (Vol. 52 No. 4) accessed on 20/1/2020 at: https://www.cia.gov/library/center-for-the-study-of-intelligence/csipublications/csi-studies/studies/vol-52-no-4/teaching-intelligence-analysts-inthe-uk.html

CERT Guidance (2019) DIKW Model: Explaining the DIKW Pyramid or DIKW Hierarchy. Accessed on 19/1/2020 at: https://www.certguidance.com/explaining-dikw-hierarchy/

Von Clausevitz, C. (1993) On War. London: David Campbell Publishers

Rumelt, R. (2012) Good Strategy, Bad Strategy. London: Profile Books

Kiss, M. (2018) Ten Tips for Presenting Data: accessed on 19/1/2020 at: https://resources.observepoint.com/blog/10-tips-for-presenting-data