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Agile and Digital Transformation: The Emperor’s New Clothes?

Here we go again – Agile Ways of Working – arguably another sound bite to add to the Lexicon that’s gone before: Big Data; Robotics; Predictive Analytics; Machine Learning; Voice-to-Text; and Distributed Ledger Technology to name but a few. Take all of the above, throw into the blender and hey presto your business is transformed into a new shiny, next-generation operation fit for the 21st century! Add ‘sandpits’, ‘garages’ and other ‘innovation labs’ charged with concocting this step-change together with the adoption of Chapters, Scrums and Sprints to ensure you can pre-fix ‘Agile’ to everything you do.  

As someone who provides Advisory services to the Financial sector, the never-ending deluge of bleeding-edge ‘solutions’ to address all business woes should be music to my ears. Except it isn’t. Scratch beneath the brochure-ware and it quickly becomes apparent that there’s very little substance in terms of how to operationalise these ‘components’ to drive sustainable and meaningful business benefits.

I don’t dispute that there are some extremely interesting and potentially disruptive transformative ‘plays’ that ultimately will significantly impact the way we do business (DLT is already throwing up some interesting point-to-point intra and inter-business opportunities although market-wide adoption remains some way off). Similarly, being Agile, in its literal sense, should be a cornerstone of how we do business - but how do you make sense of it all and more importantly, how do you determine the what, how and why?

I often hear people talking about their ‘Digital Strategy’ which is somehow standalone and removed from everything that’s gone before. When people reference digital, exactly what do they have in mind? A digital strategy should be developed in response to agreed business outcomes - a means to facilitate and potentially accelerate the Business Strategy. Similarly, ‘digital’ needs to be framed holistically, end-to-end across the business with a clear understanding of how this embeds within the Operating Model.  

For many, ‘digital’ reads as omni-channel, front-end GUI and client self-service. This is indeed one valuable application but there is clearly no point driving new business and enhanced client experience on the front-end if downstream transaction processing is sub-optimal. In thinking holistically, there’s a distinction to be made between ‘digitalisation’ and ‘digitisation’. The former relates to front-end capabilities: data visualisation and customer portals for example, while digitisation relates to automation of the transaction processing value chain. Digital solutions in this space include Business Process Management i.e. workflow, Robotic Process Automation, Machine Learning and Optical Character Recognition (digitisation of paper plus unstructured data analytics).

As stated, when determining the ‘what’ the starting point must be the business strategy and the associated business outcomes. Cost, efficiency, revenue, client experience, compliance, risk management and people engagement are familiar challenges faced by all. Taking these drivers into account, understand where your business sits on the maturity curve in terms of adoption of:

  • End-to-end Lean process review to address manual interventions, re-work and ‘off-system activities;
  • Service Integration And Management (SIAM) to address capacity and demand management across both internal and external service providers
  • Implementation of front-to-back workflow to drive process automation and ‘right-first-time’ 
  • Robotic Process Automation to drive throughput and speed to market
  • Machine Learning to enhance the end-user experience, agility and best execution (in its broadest sense).

A further consideration which is surfacing more and more is data. Whether driven by MiFID II, GDPR, FRTB, Legal Hold, data lineage or simply the increasing cost of data storage, the need to understand how data is sourced, published, consumed and retained as part of an enterprise-wide Information Lifecycle Governance framework is key. Yet, here again, many organisations are not thinking end-to-end. 

You may already have fully-documented process flows but you now need to capture the underlying entity data flows to understand how data ownership and data entitlement is assured by reference to security policies and jurisdictional, regulatory and legal considerations.  

The solution to the data challenge for many has been to build a Data Lake (Hadoop seems to be the de facto standard). In some ways, this simply adds another layer to an already over-complicated data architecture where federated data is moved, copied, aliased, redacted and masked across users, business units and jurisdictions with very little if any view on ownership, entitlement or auditability.  

The ability to attest to central governance and data security within a federated self-serve data model is fundamental to how you control your business going forward. Data needs to be viewed and managed as a digital asset as opposed to a physical asset, and solutions that allow for a single version of data without the need for copying, moving or masking provide a significant edge in the era of Open Banking, Operational Resilience (see my previous blog), Subject Data Requests and ‘gone-aways’. More specifically, data storage optimisation is becoming an increasingly examined area – given the growth in costs for data storage – and one that we have advised multiple clients on.

In helping clients assess business maturity and how best to align digital solutions with desired business outcomes, we use a proprietary diagnostic tool. It facilitates a quick holistic assessment by reference to six phases of the digital transformation journey, together with key drivers (‘levers to be pulled’) that influence digital transformation and alignment to business strategy.

The 6 phases together with indicative levers include:

  1. Assess (levers: customers and products; channels; analytics, Customer Experience)
  2. Define (levers: strategy; commercial; alliances)
  3. Design (levers: organisation, governance; technology, people; process)
  4. Build (levers: innovation; build; test and learn)
  5. Embed (levers: digital appetite; roadmap; agile operating model)
  6. Manage (levers: cyber security, data management; operational resilience)

The diagnostic considers both the Current State and the ‘go-to’ Target State for the phases, identifying key gaps to inform sequencing and prioritisation. Outputs are instant and visual, clearly showing where you as an organisation are meeting, exceeding or falling short of what’s required to ensure successful outcomes. 

Having worked through this process with a number of clients, we have found that the most productive approach is to work collaboratively through the diagnostic, where TORI’s role is to probe and challenge; followed by a subsequent session where we consider the outputs to inform a richer conversation around key gaps and priorities.  

In terms of people who should participate, this exercise should be kept “tight and directional” and does not require a large group but rather those people mandated and responsible for setting strategic direction and designing the digital transformation journey. If you would like to hear more about how we help clients make sense of Digital Transformation, get in touch:

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