Data strategy: How to keep it real in the era of technology feast and insight famine

1,009,491 days later and Rome is still being built. Likewise, Lucy Acheson calls for a healthy dose of pragmatism in this four-step mantra for planning and growing a data strategy.

Lucy Acheson (1)I have been putting off writing this article for months. Each week I complete all of my work tasks, steadfastly avoiding putting pen to paper, or digits to keyboard. It’s a bit like doing all the house work before tackling a mountain of ironing. Classic symptoms of a severe case of writers block or I-hate-doing-the-ironing-itis.

Let me explain. I genuinely have a burning desire to evangelise about data and the possibilities it affords us as modern marketers. I really do, but it’s hard to think of a novel and engaging angle. It’s all too hard to avoid talking about its size and how cool it is, because it really is too big to comprehend and I do fervently believe we will use it to save our planet and to ensure that the human race has an exciting future.

But if you are reading this article as a modern marketer you already know that right?

Yesterday (thankfully) I had a road to Damascus moment. I was having lunch with a friend who is head of CRM for a company who will remain nameless. We were munching bruschetta, musing two of my favourite subjects: marketing automation technology and data science – and the optimisation of both – when she said “It’s so great to chat and to get confirmation that ‘not perfect’ is a shared reality and that it’s OK!”

And that’s when it hit me.

I realised that every single one of my clients past and present are grappling with imperfect data ecosystems which will never be fully optimised, no matter how hard they try. Furthermore, they are all having to run so hard to capture and take advantage of insights from consumer behaviour, that on sleepless nights I wonder if they question whether the effort is ever worth it, whether the gargantuan and expensive effort is honestly, hand on heart, commensurately dwarfed by the life changing gain all data professionals and gold prospectors dream of?

This is a rather depressing reality for me at my mid-career point, especially having tried to accomplish just what I realise we haven’t been able to crack for the last 20 years. However, my thoughts made me begin to ponder what success really looks like given the reality of this frustratingly imperfect world.

What yardstick can we measure ourselves against today to know we are winning in the titanic man or woman versus data marathon? Or, more importantly, what should our strategic and operational mantra really be?

Before we talk about KPIs and hard and soft success measures, please let me reassure you, I am a believer. I drank the data Kool-Aid 20 years ago. I grew up in the London agency which gave birth to the Tesco Clubcard.

Successfully wrangling data – and lots of it – has been my day job for a fun-filled 4,800 days or thereabouts. So I do get why we do what we do, and I completely see the possibilities that new technology and data science tantalisingly offers. I am just trying to be a modern day realist and to encourage all those who employ me or with whom I work to be of the same persuasion.

A truism of this straight talking realistic approach, is the duty to speak of what some modern marketers are steadfastly ignoring today. Namely espousing the reality that technology stacks are an ever evolving Frankensteinian challenge and that data and analytics are not the fail safe silver bullet we sometimes wish. We still must be smart enough to ask the right questions. (Sorry, the machines still need someone to drive them.)

Marketing technology will evolve, or stagnate (as we often unfortunately see) over time, and analytics is still really in it’s infancy in terms of providing actionable insights for most of the marketing departments and businesses in Australia.

I am painting a particularly bleak picture, but the trick is not to become despondent about the shared status quo, and to realise that everyone is in the same boat and we would do well to learn from one another.

I read in a publication last month that a particular client had cracked marketing automation and was super happy with their new tech stack. But I know for a fact that they have been through hell for 18 months and are neither happy nor optimising the technology to one iota of its true potential.

My mission is to help people to learn from their pain in order to avoid it for ourselves, which is why so many brands are turning to technology agnostic experts for assistance.

‘Guide me through the crazy maze’ they cry, ‘so I may safely reach the other side. Give me a fighting chance to explain to my boss why we made this investment in the first place!’

Similarly, I know from firsthand experience that many clients in this market have a severe lack of analytic resource availability for marketing teams to tap into. Their insight teams are so busy on BAU business intelligence week in week out, that often the marketing strategy building work streams are marginalised and put off, sometimes permanently.

Related: Peter Strohkorb says business technology implementations are no longer an IT matter »

As an example, when we asked if we could run counts for a project with one of our enterprise clients recently, we were told it would be six months before the analytics team could even look at the brief let alone undertake the analytics required. Not the speed to insight and subsequently speed to market we had in mind.

This is why offering marketeers dedicated analytic resources to drive the machines they are purchasing is so crucial. What’s the point in having a Ferrari if you have no petrol to put in it?

We are all struggling, however I believe it’s how we choose to react and how we go about setting realistic objectives in this era of technology feast but insight famine that will sort the children from the adults.

What, then, would a failsafe rulebook from which to navigate our way successfully through this seemingly complex but desolate environment look like?

Never forgetting the crucial points, that data is awesome and we should enjoy working with it. And always believing in better.

My rulebook mantra:

 

1. Learn from others

I have not worked with a client in my 20 odd years who has not been fascinated and hungry to learn from the anecdotes and case studies of other clients. It’s why we all trip along to conferences, and listen to subject matter experts who are more experienced or well versed in a subject than ourselves. It’s why we run and flock to meet up groups and it’s why technology agnostic but credible consultants have the modern edge.

Put simply, if you are lucky to work with a multitude of clients, who are in exactly the same place or similar places as everyone else in the market, then you are brilliantly placed to leverage their learnings when helping someone new.

Now, I know that every objective, data set and data ecosystem is unique, but it helps to have built, managed and optimised many in the past in order to help your clients of today.

Similarly it helps to have analysts who have worked across many similar client datasets in order to get to and to solve a problem quickly and accurately the first time of asking. These lucky data scientists are, to quote my favourite client, ‘as rare as hen’s teeth.’ If you find them keep them close!

 

2. Don’t bite off more than you can chew

One of my mentors in my youth warned me about taking on too much and becoming a ‘busy fool’, something that I genuinely strive to avoid on a daily basis. Being a fool is after all terrible blight on one’s character and to be avoided at all costs.

I therefore advise being single-minded in purpose, while at the same time ensuring that all ventures embarked upon have been set up for success, or are actually running well before considering ‘what’s next’ on the technology smorgasbord or data science all-you-can-eat buffet.

I’m not saying that you shouldn’t have a 12 month or 24 month plan and look to the future, but I am amazed at how often plans are diverted or bent out of shape in reaction to a knee jerk scenarios or seemingly attractive ‘get rich quick’ lures.

If we can’t learn systematically and are in danger of being busy fools, we shouldn’t be in charge of building the plan in the first place, and definitely shouldn’t be handed the keys to the Ferrari.

 

3. Don’t throw out the baby with the bathwater

Corporate amnesia is a reality for most businesses today. Technology is in place and analytic models lie poised ready for operation, yet it’s not uncommon to hear very elaborate myths and legends around how they were built unreliably and by people of questionable talent, who thankfully no longer work at the organisation.

Sometimes it seems easier to start again rather than lifting the bonnet to see what is salvageable. Technology is cheap now, and – if you can find analyst to do the work – it’s best to build new, right?

Well I say no. If we don’t learn from what has gone before can we ever truly evolve? Are we going to be stuck in a never ending knot of build, use, then chuck away to try something new? (Sadly this is possibly a human trait)

Even if we can’t push away the cravings for ‘new’ totally, I do believe in at least having a go at salvaging insights from the past before reinventing the wheel. Even if we do indeed find that it’s the case that ‘the models built by the last bloke were rubbish and I can’t believe we ever actually used them!’

 

4. A healthy dose of realism in all you set out to achieve

This point has peppered my prose so far. But no matter how uninspiring and dull it sounds, being realistic with what we can learn or implement each week, month, quarter and year will pay dividends in the future.

In short, have a plan, stick to it and if you’re lucky you might actually exceed expectations, while avoiding the ‘busy fool’ moniker.

Imagine if, because of this pragmatic approach, we can report back in dispatches that we have made or achieved five fundamentally business driving breakthroughs, creating a bomb proof platform from which to plan our future. Then the coffers might be opened again for us to invest in more of the shiny and new.

I genuinely believe that by following this ‘Rome wasn’t built in a day or even a month’ plan, bit by bit as we test, learn and evolve, we will then, and only then be able to call ourselves modern marketers.

So far it’s taken approximately 1,009,491 days to build Rome. This is based on the traditional founding of the city (21 April 753 BCE), but we should also consider that the city has been sacked and rebuilt several times.

 

Lucy Acheson is LIDA’s head of data strategy.

 

 

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