You’ve heard it countless times before: “Data is your organisation’s most valuable asset…” (or words to that effect). The trouble is, it doesn’t always feel that way.
From customer behaviour in retail through to machine-level information in manufacturing, organisations are generating data in ever-growing volumes. Recognising that this data has value is easy. Actually knowing what to capture, harnessing it and rendering it usable: that’s where the real challenge lies. Without a plan, it can seem unsurmountable.
Success demands a strategy: a comprehensive vision setting out what you want to achieve with your data, and what you need to get there. To get you started, here’s an outline of what this strategy should comprise…
Starting Point: Why a Data Strategy
An estimated 73% of company data goes unused for analytics. Businesses are passing up the opportunity to translate data into insight, and insight into action. So the topline reason for a data strategy is to stem this obvious wasted opportunity cost.
A strategy can unlock ways to deliver better customer experiences and uncover new growth opportunities. It provides a lens in which to identify trends impacting your business and to track performance. Most importantly, data is only an asset if you actually put it to work. Think of your strategy as a roadmap for generating a maximum return from it.
Start with the End in Mind
Think about your topline objectives first of all. The perennial goals for most businesses tend to include increasing profitability, reducing costs and identifying areas of growth. In the current climate especially, more immediate priorities could be focused on priorities survival, stabilisation and recovery.
Linked to this, it’s worth drilling down to identify specific business problems you want to address. Just some examples could include:
- Obtaining a better understanding of buyer behaviour to predict demand
- Creating stronger, more personalised customer experiences
- Spotting production or supply line bottlenecks and responding to them swiftly
- Driving efficiency and maximising use of existing resources
- Identifying the attributes of high-performing staff
- Streamlining operational and regulatory reporting and staying on top of compliance
- Forecasting and modelling for a range of possible scenarios
With your objectives identified, you can focus on shaping the individual elements of your strategy to achieve them.
Create a Data Inventory
Through a data inventory audit, you identify the sources of data you have already and where it resides. Next, assess what data you have in the context of your objectives. It may be that in order to get answers to the questions you want to address, you will need to supplement your proprietary data with external data sources (for instance, currency exchange information or sector-specific market trend reports).
People, Processes, Technology
In a similar way to your data audit, a people audit is also recommended. The broad objective is to assess the level of data skills that exists within the organisation.
At this point, it would be very easy of us to suggest something along the lines of “start hiring now to fill your data skills gaps…” But of course, for most of us, unlimited staffing budgets are currently very much the stuff of fairytales.
These days, it’s more often a case of working your strategy around your existing people. It usually involves an element of upskilling (something that the vast majority of employees actually value). It often involves focusing on self-service and user-friendliness in your choice of technology. Finally, it involves plugging those skills gaps in a way that’s actually achievable: not necessarily through hiring more people, but through tailored, flexible, external advice.
The key element here is governance – i.e. “the process of managing the availability, usability, integrity and security of (your) data”.
The universal principle of “Garbage in, Garbage out” applies absolutely to data. You need the right processes in place to collect, store, govern and analyse your data, otherwise the level of insight you gain from it will fall well short of expectations. Again, for a future-proofed governance foundation, an element of expert input is invaluable.
Opting for an all-singing, all-dancing data analytics platform is never in itself a guarantee of success. When we hear stories of major data projects that have failed, it isn’t necessarily the technology that’s the problem; and nor is it the fault of the user business. More often, there’s a fundamental mismatch between what the organisation hoped to achieve and what the solution is designed to deliver.
Extraction, storage, warehousing, visualisation and reporting capabilities, method of deployment, configuration and more: your choices in all of these areas demand careful guidance, along with referral back to your overarching goals.
Are you ready to start off your data strategy with the right foundations? Explore our data strategy services.