Were we not all inspired by the promise? Were we not freshly motivated by speakers at business conferences and writers of thought leadership pieces who highlighted the untapped potential of data?
Many a C-Suite decision-maker resolved to leverage this newfound power and start driving it within their organisation.
For a decade we’ve been hearing things such as “data are the new oil”, “we’ll make marketing and IT work together”, and “we’ll build dashboards and put them in reception”, but – despite now being greeted by shiny 78-inch screens with live, animated graphs and figures – most businesses remain fundamentally unchanged.
The plan was to build data-driven businesses that are characterised by prediction and are insights-driven, businesses that have a test-and-learn culture and continuous optimisation. The promise was that these businesses would use data as the foundation for agile and critical decision-making and innovation to improve operational efficiency, minimise risk and drive new or maximise existing sources of revenue.
Instead, many of these businesses have only, at most, paid lip service to the approach despite best intentions.
To do data-driven properly requires that data become the foundation of your business. After all, when we talk about data, we’re (mostly) talking about customers – the very lifeblood and foundation of every business since the beginning of time.
It’s not the kind of approach you can half adopt – a business must be either all-in or all-out, otherwise the exercise becomes a waste of time and money.
There are plenty of reasons that adoption hasn’t been as comprehensive as it should be, but I posit seven major ones – and my theory is that most businesses will find at least three of them true. They are:
Inclination and apathy
Let’s start with marketers – while many are adept at spotting trends, not many are good at adopting or adapting to them.
Many marketers are stuck in a comfortable phase, probably delivering acceptable brand strategies and communication plans without the requisite trust or technical ability to leap forward.
Inclination is required to help drive the adoption of new technology, so maybe it’s the team itself that needs a reboot, not just the methodology.
Down the corridor – in much darker offices – is the apathy of many IT departments to implementing new technologies. Stuck resuscitating outdated PCs and connecting HR to the printer, they’ve lost sight of the fact that technology and innovation are what drew them to IT in the first place.
They need to understand the value of building/changing systems and processes, and running new software to help get them back in the game.
The business then needs to facilitate collaboration and adoption, and then measure efforts and hold the full team accountable to real business results.
Whether it’s an internal team or a contracted business partner, such as an agency or specialist consultant, groups are often fiercely territorial and will blindly defend their efforts – naturally. Silos form easily and can make it hard for businesses to adapt.
Overwhelming data volumes and systems
If you’re dazed by the volume of data available to work with then you’re doing it wrong. Often, the amount of data, the legacy and closed connected software, and systems that generate this data mean that the task is overwhelming.
Data need to be useful to business applications and functions – in other words, data must be used to facilitate more business. If it all seems like too much, it’s time to go back to the processing drawing board.
Analytics and insights (by themselves) generally fail as a proof-of-concept
Often, as a starting point, businesses decide they will be more intentional with their reporting. This is usually done at the end of a project that didn’t start with key customer hypotheses.
Because this generally doesn’t yield any major results or return, it’s a matter of time before stakeholders lose interest.
What is misunderstood is the fact that data-driven is not the same as analytics. Data-driven is a much more foundational and pervasive approach to business.
Your proof-of-concept should evaluate how a more holistic approach to data could be effective by implementing it across a smaller, more manageable aspect of the business. This should focus on a single part of the customer journey – with all its associated systems and data – to stand alone and be tested.
Critically, that plan should include various ways in which using data could enhance the customer experience or optimise service delivery.
The Cambridge Analytica effect
The idea that all data is evil and is used for nefarious purposes has deterred many a company from pulling the trigger. Data can be used in multiple ways, but if your intention is to help serve your customers and do better business – and you’re willing to invest in doing it properly by making sure your gatekeeping checks and balances are comprehensive – you can only succeed.
Cost of tools
The tools employed in sourcing, managing, interpreting and using data are often charged for in foreign currency, particularly US dollars. That makes them expensive for South African companies to adopt and license, thanks to the rand’s weakness against major currencies.
For bigger organisations, successful data-driven marketing also relies on an investment in expensive infrastructure and big spending on IT integration and maintenance.
There are often smart ways around this, but you need to know where you’re going and map how you’re going to get there. Unfortunately, it’s often hard to do this without practical exposure to various functional parts of the business and experience with implementing varied solutions.
It should go without saying, but, ultimately, the investment should make the business more profitable.
Tools without operators
Many businesses have been sold – often by a highly trained and effective salesperson with a secret weapon in their own data intelligence – a piece of glossy, expensive software with the power of one-stop-shop customer solutions. These tools are paid for with chunky ongoing budgets, are installed and connected, and they sit unable to perform the promised tasks.
Tools gather dust if they’re not being actively used – by people (inside or outside the organisation) with know-how, mandate and responsibility, and with a proper plan that is being measured.
There are many other reasons for businesses failing to optimise data, but these are the big ones we see most often when we’re called in to help.
Don’t lose that excitement, just remember: Successful data-driven businesses are entirely underpinned by strategic intent and operational follow-through that embeds effective information systems, customer data and predictive analytics at their core.
Geary is a director at One Custom, an independent customer experience and marketing intelligence agency