Re-engineer your organisation’s DNA to boost its agility

Any organisation that wants to rapidly adapt to change with sure-footed agility needs to be able to rapidly adapt its DNA.

But what on earth do we mean by an “organisation’s DNA”?

So that we can answer this question, we need to view organisations through a zoomorphic lens.

Organisations have complex internal systems that allow them to survive and thrive by responding to changes in their business environments; if we think of them like this, their similarity to organisms becomes obvious. And we can use this mental model to figure out how to adapt our organisations more rapidly, but using an assured framework of ideas.

We know that an organism’s form and function largely depends on its DNA – it is this blueprint that, to a high degree, prescribes its ability to respond to change. But its DNA can also be adapted, enabling modified responses that are better adapted to changes in its environment. Typically for organisms these adaptations only happen over a number of generations. More rapid adaptation has only been possible where the DNA has been re-engineered by human intervention.

But our organisations also have a blueprint – we may not recognise it because it is informal, episodic, or personality driven. Nonetheless there are ways of working that deliver responses to business events.

In these times of seismic environmental changes, our organisations’ ability to adapt rapidly, has been brought into stark relief. We know that in the months and years ahead, the continued testing of their agility will be their most constant challenge. Many of our organisations will need to make fundamental changes to their blueprint, so they can adapt rapidly enough to simply survive – never mind thrive.

Defining An Organisation’s DNA

Okay, so we know we need to be better at adapting, but how? What is it that we need to analyse in detail? How can we set about fixing what until now didn’t even appear to be broken?

Our organisation’s ability to re-engineer its blueprint relies on it being able to answer the three standard simple questions:

  1. What are we doing now?
  2. What do we need to do?
  3. What approach will we get us to this destination?

The self analysis required to answer these questions must be based upon the objective understanding of the way the organisation operates today. And this analysis must use the organisation’s data as the basis for its analysis. As we know, it is this operational data that provides the lifeblood of our organisations. But, if an organisation does not fully understand its operational data, it cannot possibly use it to provide a reliable basis for driving change.

To get a firm grip on its data relies upon articulating the three DNA Data Domains that provide its:

  1. Definition
  2. Control and
  3. Monitoring

Let’s look at these domains in a little more detail.

The Three DNA Data Domains

If we are determined to become more agile, and also believe that data defines the lifeblood of our organisations, then we must concentrate on becoming data centric and use our data to become truly agile. Let’s look at the role of the three DNA data domains in making this a practical approach.

Defining Data

We must define our operational data so that we can maximise its benefit. It is this underpinning domain that, for example, we rely on to:

  • provide holistic reporting across the enterprise
  • deliver re-usable components
  • enable strategic analytic based outcomes
  • develop an agile, loosely coupled system landscape
  • adopt new technologies including Cloud and Machine Learning 

To create effective data definitions requires an organisation to document its business processes and map them with their associated data.

Figure 1 – Process and data interactions

It is this core pair of definitions that fundamentally define the way organisations respond to business stimuli and events. As we can see in figure 1, structural business data models must form the heart of the data definitions.

Figure 2 – Data definitions driving the system landscape

Once established, the defintions can be used as accelerators, for example to create data flow contracts for the data that flows through the organisation’s veins.

Controlling Data

For all our organisations, effective management of their data is critical for their ongoing success. And, of course, for most it provides the inescapable evidence required by ever changing legislation and compliance regimes. Also, it is not hard to argue about the constant need to improve data quality, or maintain appropriate access to our data.

Therefore we must take effective control of our data. A few examples for these control domains include:

  • hosting jurisdiction
  • privacy controls
  • retention policies
  • access and data modification entitlements

Obviously, the more that we can automate these controls, the more confident we can be that they are effective, and the easier it will be to adapt to constantly changing requirements. But notice that managing our data is critically dependent on establishing its definition as a pre-requisite – how can you possibly manage data you cannot define?

Monitoring Data

To understand what is happening in our system landscape, we need to constantly monitor data changes in it. For example, these monitoring capabilities will allow us to compare operational data with its:

  • definitions
  • basic profile, including data quality
  • compliance with policy and regulation
  • governed production and consumption

The following diagram illustrates how we can use data flows to monitoring and compare the actual data state with the required data state. In addition, we can see how any variations can be corrected to improve conformance with its DNA specification; improving data quality metrics for example.

Figure 3 – Data feedback loops driving data and process changes

At a higher level, the monitoring of our operational data should be used to provide insights. This is where the realm of data analytics can, for example, be used to drive:

  • strategic directions for the organisation
  • ease of use and suitability of products
  • improved customer journeys and experience

Adapting Our Organisation’s DNA

We can now see how all three DNA domains are essential for a healthy organisation. But it is crucial to realise that they are intertwined and each cannot be considered in isolation.

Redrawing figure 3 into a more generalised pattern, we can see that data feedback flows can be used to adapt the organisation’s ways of working and definition models.

Figure 4 – Data feedback loops driving adaptation

This approach must be built into any data centric organisation to enable it to learn as an organisation, and rapidly adapt its DNA in a sure-footed way.

Organisational DNA Data

Naturally the three DNA domains all fundamentally require data. But notice that this data is not part of the operational data as such. It constitutes a special framework of data that provides the context for the organisation’s operational data.

Data professionals use the term metadata to describe the data that defines its operational data.

If operational data provides the lifeblood of an organisation, then metadata provides its DNA blueprint.

Unfortunately the term metadata is typically not well understood by anyone beyond a relatively small group in most organisations. Even amongst these groups, there is rarely consensus over what metadata means, or why its shared understanding should form a core part of organisational data literacy. However, if we want to become data centric in order to drive agility, we must promote the use and power of metadata as a fundamental enabling step.

In my experience, using the term metadata in our conversations, inhibits rather than enables successful progress towards data driven agility. Framing its concepts in more intuitive terms for an organisation, will accelerate adoption and integration with your organisation’s common data language.

The following themes might be able to allow you to gain traction in your organisation:

  • Define – defining our data’s meaning to deliver a shared data understanding and a common data language
  • Control – executing effective data governance and management processes to ensure compliance and increase data benefit from operational and strategic processes
  • Monitor – capturing data metrics and producing analytic outcomes to drive operational efficiencies and strategic direction

Taking Control

To become truly data centric, an organisation must understand how data defines its DNA. This realisation must be followed by determined actions and strategic delivery to re-engineer its DNA to guarantee a truly agile future.

Our operational data is framed by our metadata. These two data domains are the Yin and Yang of our data estates. In the same way we create frameworks and management of our operational data, we must evolve mature processes that actively manage our metadata. But here we must not confuse maturity with level of completion – far from it! There is no future normal, no steady state datum to measure progress towards.

We must engineer agile adaptability of our metadata in order to engineer organisational agility!

As the pre-requistie enablers to this vision though, we must elevate the shared understanding of the underlying concepts and, in particular, those that are data centric. These must form the foundation of the organisation’s shared Data Language, raising collective Data Literacy to transform its Data Culture enabling it to become genuinely Data Centric and ultimately Data Agility.

Thank you for reading this. I hope that you find the ideas here useful and help you evolve strategies that will deliver benefit to you and your organisation.

I wish you the very best and trust that you and your loved ones are keeping safe in these challenging times.

Further Reading

If the ideas in this article resonate with you, then you may be interested in looking at the following books allied to this topic:

  1. Enterprise Data Architecture – How to navigate its landscape available here in the UK and here in the US
  2. datagility – powering data agility for tomorrow’s organisations available here in the UK and here in the US
  3. The Data Model Toolkit – Simple Skills To Model The Real World available here in the UK and here in the US

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