I recently had the pleasure of judging the UK Digital Experience Awards, in the Analytics and Use of Data category. After the scores had been submitted, the virtual awards ceremony was over, and we’d exited Zoom, I was struck by a feeling of recognition. It wasn’t a familiarity with the specifics of any of submissions I’d judged, nor with the anyone presenting them – it was a familiarity with the challenges they’d faced and endeavoured to overcome.

There are common challenges amongst businesses looking to transform the digital or customer experience.  So here are five hard-won lessons from the coal-face of transformation that I wish I’d learned sooner.

1. Visioning isn’t a one-off

We all know the importance of a vision (and/or a mission, purpose, north star etc), and I’m a big fan of a ‘plan on a page’. But some people seem to identify this at the beginning of a programme – which helps obtain buy-in and investment – but then rarely look back at it. 

This ‘do it, then forget it’ approach can lead to problems, including going off course mid-way through a project, or getting to the end then struggling to articulate how you have delivered on promises.

In my hands-on experience, good visioning practice should be:

  • Clear and explicit about goals and targets. It shouldn’t be high concept or esoteric; it should specify what you intend to deliver, tying up with a business plan or investment case and setting realistic expectations about when benefits will be realised (more on this later).
  • Forwards-looking and pragmatic: it should create a framework for planning, including things like enabling capabilities, resourcing, ways of working, measurement, etc.
  • Understood by all: everyone involved should have a sense of ownership of the vision, understanding the role they play in realising it. Colleague co-creation is the best way I know to make this happen.
  • Referred to often. It’s impossible to anticipate every issue in advance, so when the unexpected happens, it helps to refer back to the vision, to use it as a reference, or even a check-list for decision-making. But that doesn’t mean you’re entirely beholden to the original thinking, because it should also be…
  • Able to evolve: Things can and will change – focus may shift, priorities get adjusted and new insight comes to light, and so the original vision may rightly need to evolve accordingly.

2. Have a plan for in-life.

Transformation isn’t achieved the day the tech launches! Whether you’re transforming a back-end system, a customer-facing experience or a whole digital ecosystem, it is likely technology plays a leading role – but the delivery of that tech is just the start.

In advance of launch day, you’ll need a plan for the in-life operating model, resource, training and a practical plan to realise the benefits. I’m surprised how often this is overlooked or rushed through at the last minute!

For example, if you set out to deliver digital personalisation, you need more than the data management platform, content management system and targeting tools to do it. You’ll need plenty of insight-driven use cases in a testing plan, a cross-functional team with capacity to create or configure content to be targeted, trained and proficient analysts to set up the campaigns, and, of course, an agile operating model to keep the pace up of testing & learning.

3. Data doesn’t = insight.

Everyone’s excited about data these days and it plays a role in most DX (and CX) transformations.

But of course having data, and even having all the right kinds of high quality data together in one accessible place, isn’t enough. You need a plan to interpret and mobilise data, and this takes talent and time.

For example, if your business is immature with data, having a holistic, customer-centred BI dashboard is a great starting point. But the dashboard will only answer the first question of insight-generation, which is ‘What are the numbers?’. Great insight goes further than this; it also seeks answers to three more questions:

  • Why? i.e. root cause analysis
  • So what? i.e. commercial implications and
  • What next? i.e. persuasive recommendations

I call these the four levels of insight and I recommend you think about the people and the process that will push for these answers in a rigorous way.

(I’ll also add that having a data scientist doesn’t = data science either, but that’s another story). 

4. Embrace impact measurement

There’s always a tension when a big project delivers: it might have been on time and on budget, but did it deliver the benefit back to the business that was expected?

This is the point when project sponsors fear a negative result, and especially fear a ‘computer says no’ kind of response from their analysts.

And this is normally when analysts feel two pressures that shouldn’t conflict, but sometimes do: to identify the full value the initiative has delivered and to remain impartial and scientifically accurate.

There could be an entire article on this subject alone, but the two most important principles are:

  • Plan to measure: you may need to build the ability to measure accurately into your delivery plan, e.g. staged releases, controls. And it definitely helps everyone’s level of trust and comfort to be transparent and to obtain buy-in on your methods in advance.
  • Plan to fail: don’t expect success from the day of launch (it is rare!). Instead de-risk delivery by planning to fail – but fail as small and fast as possible. Build in time to iteratively test & learn so your small failures lead to big successes.

5. Over-estimate the difficulty of Culture change: it is harder than delivering tech!  

Delivering new platforms or systems are hard, but there are at least tried & tested processes to follow.  Effective culture change seems rarer than successful project delivery – and as such, there are fewer proven solutions.

Digital or CX culture change is often around being digital first, customer-centric or data-driven. In my experience, there are no silver bullets to obtain these outcomes, but I have seen some success with:

  • Serious stakeholder engagement. Identify influencers and bring them in early. Engage widely and treat stakeholders the way a product person would treat customers: understanding their unmet needs and trying to address them; tying activity to stakeholder KPIs.
  • Collaborative planning. You’ll need advocates and adoption across every level and vertical. I’m a believer in the ‘Ikea effect’, a behavioural economics concept that says we place greater value on things we have played a role in creating. Use stimulating co-creation workshops to generate ownership and action from stakeholders.
  • Communicate like a marketer: openly and regularly; a constant dialogue. Like a marketer, consider both ‘brand’ comms ie motivating updates relevant for everyone, and also ‘trade-driver’ comms, where you monitor progress in key areas. As with social media, authenticity and transparency go a long way, so don’t shy from sharing challenges as well as successes.
  • Expect results may be slow.  There’s always resistance to change, but don’t give up! Be persistent and trust the efficacy of what you’re implementing. If it really does pay to listen to customers and/or to use data for decisions, the results will come through, and as they do, others across the business will follow the example.

Bonus tip: don’t get attached to taking credit for ideas – one of the signs of successful culture change can be hearing your ideas presented by others as their own.

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