By Michael Brennan

With over six months of pandemic life behind us, we have all had to get used to remote working, digital interactions and collaboration, and an unprecedented reliance on e-commerce. This is as true of consumers as it is of business, and it all adds up to a significant expansion of the digital realm.

Many businesses will have had to scramble to enable remote working at scale, adopting new channels and platforms in response to a rapidly changing situation, and leading to unprecedented demand for the likes of Zoom, Teams and Slack.

Others will have had to build an e-commerce capability overnight, and from scratch, in order to keep their business going and to meet customer needs and expectations – arguably it’s these expectations that we need to be particularly conscious of as we move deeper into the next phases of the crisis.

It’s fair to suggest that the solidarity and goodwill that characterised the first phase of lockdown has now dissipated to a large extent. At times it can even feel as though the nation is at war with itself, whether that’s car drivers versus cyclists, the North vs the South, Blue Collar vs White Collar, the Old vs the Young and so on.

And yet one thing that unites these disparate tribes are their (high) digital expectations, defined by their experience with the likes of Netflix, Amazon and similar. Indeed today’s consumers have been referred to as post-digital – in the sense that they get it, don’t see it as a novelty, expect a seamless cross-channel (and device) experience, and most importantly expect you to get it too.

So, it should be clear, that for many businesses and organisations there is a need for some proactive strategic thinking to address both internal, operational and employee needs, and the external expectations and needs of customers and prospects. Cutting across these two domains which we can refer to as defensive and offensive capabilities, is the critical question of data protection and security.

This is exactly what an effective data strategy should deliver, an integrated approach to data needs. Many will have shied away from this in the past, indeed many may have pushed back against the digital imperative before the pandemic, arguing against the need for a transformative approach and instead drifting into digital.

Today transformation is firmly on the agenda for all forward-thinking organisations, you have all the justification that you need written into the experiences of this year. Indeed, some would argue that risk has now overtaken cost as the number one issue for business owners.

Very helpfully of course the digital model does not demand vast up-front investments, after all the as-a-service model is firmly predicated on paying as you grow, with recurring payments taken from Operational rather than Capital expenditure. Most importantly a strategic approach to digitalisation will save you money compared to legacy operations – while also mitigating business risks.

One fundamental reason why

Even before the events of 2020 blind-sided us, it was clear that many organisations were struggling to realise the benefits of a data-driven approach, with their frustration only increased in proportion to the hype and hyperbole surrounding all things data over the last decade and more.

And that is the clearest possible rationale for a data strategy –  because most organisations are still not seeing the benefits of their data investments – and we think there are some key reasons why this may be the case including a failure to take a holistic, strategic, approach at the outset and a dash to exploit and leverage data without due consideration of the infrastructure and management required.

So, what is a data strategy?

First and most importantly it’s essential to appreciate that any data strategy should be firmly grounded in the overall business or organisational strategy, it should be led from the top table and not farmed out to IT, it should have significant sponsorship from the Chief Executive, Managing Director or similar and it should encompass people and culture as much as data and technology.

The data strategy should clearly address the behaviours, culture, infrastructure, skills, and technology required for data to enable and drive the business strategy. It requires an organisational commitment and the centralisation of data management and ownership. No longer can different business functions – be that marketing, sales, operations, finance, or HR – work in isolation or in siloes.

An effective data strategy must encompass data architecture, governance, and management approaches including an authoritative, universally accepted, version of truth.

A Single Source of Truth

Many of you will have heard your analysts or data scientists wax lyrical about this idea – the importance of a single version of the truth – but may be slightly unclear as to what this critical concept is all about.

To bring that to life let’s think about how individuals and teams across an organisation might work with data. In doing so you will rapidly see that the same data is used for different purposes at different times across different business functions – for example, you will need customer and order details for marketing, sales, operations, logistics and billing purposes.

And each of these business functions will have their own reporting requirements and so will contextualise and communicate the data differently (don’t forget Peter Drucker’s dictum – information is data imbued with purpose and context).

Then layer in the fact that each of these business functions may be using their own systems (or spreadsheets) and quite possibly BI dashboards, and you really do have a recipe for data chaos and ultimately an underperforming business.

The solution is to have a clearly defined approach to master data management, including all of the principles of data governance, such that the business can be assured that there is a central repository of critical business data that represents the master or single source of truth.

Then with the right governance principles in place, you can enable individual functions and teams to work with multiple versions of the truth to meet their specific needs – without corrupting the master repository and so negatively impacting on data quality which is the critical ingredient for success with data. After all no matter how smart the algorithm – if you put garbage in you’ll get garbage out!

Bringing it all together

And so we come back to our starting points in terms of stabilising and optimising internal operations in the new normal of remote and hybrid working at scale, while delivering the best possible digital experience for customers and prospects alike.

In both scenarios and applications the quality of data is vital to success, just as customers will recoil from inaccurate data (starting with their own personal details) so employees will not trust new platforms and systems that are delivering dubious or contested data due to a lack of governance.

So there are some reasons why this Autumn may be the perfect time to start to take a more strategic approach to your data, talk to Profusion to find out more about how to develop your strategy.

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