Breaking Through
In recent posts we’ve discussed how companies that adopt data driven cultures use empirical data to help drive profitability, control costs, boost customer numbers and more. However, given the hype and hyperbole, why don’t more companies make better use of data?
The chart below lists some of the top challenges that companies face:
It's all about strategy
The overriding message is that all of these points should be components of a comprehensive data strategy. Although this is highlighted as a barrier itself, it also governs all of the others.
In my view, executive buy-in is by far and a way the most important, irrespective of the relative percentages in the chart. If this is not in place, the benefits will be limited. It provides the key which opens the door to solving all other challenges.
The table below has been shared previously. The most data-savvy businesses have a data culture driven by executive mandate.
Privacy is a virtue
Amidst growing public awareness and concern regarding data scandals, businesses are wary. The impact of reputational damage and the serious punitive measures which now exist are real. This can get to the stage where innovation and business improvement are curtailed by unnecessary fear.
Policies, such as Europe’s GDPR, actually have a dual purpose in this respect. They protect the consumer and they also provide a best practice self-auditing tool for business. Businesses need to embrace these policies at their core. This means real investment in time and effort. It should become a badge of honour, worn with pride.
The right solutions and full implementation
To be effective the tools, and the human beings using them, need to be right.
Technologically, this means the right data collection tools, storage options, processing software and hardware. The data strategy needs a strong technology component. Experienced data engineers and IT personnel are crucial to ensure effective design and implementation.
To maximise usage, the solutions need to be simple. The tools need to be user friendly, staff need to be fully trained and the right staff need the right access to tools and data across the organisation.
Again, all of these points should be key components of an effective data strategy.
Just one more thing ...
There is one point that surprised me by its omission from the top barriers as identified by the MicroStrategy research shown above. This is a major challenge facing all businesses, whether they are Analytically Challenged, Practitioners or Improvers; staffing.
Research from Go Data Driven in 2018 identified recruitment of data scientists and engineers as a problem for 30% of organisations looking to strengthen their data analytics
If data is truly the new oil, then data scientists and data engineers are the new prospectors, and they are much in demand. Furthermore, the challenge is two-fold, not only are they hard to find, but retention is also a challenge.
These are individuals at the leading edge of data, software and hardware developments and they are often highly motivated by curiosity. It’s important to recognise this. Some businesses allow time-out each week for data scientists to follow their own investigations. While this might not work in all cases, it can be a good tool to keep the brightest individuals by nurturing their curious and innovative minds.
So, to reap the full benefits of a comprehensive data strategy, it’s vital to start with executive buy-in and then to tackle all of the challenges that exist, not just cherry pick the easiest or the more parochial in nature.
In our next post, we will touch on a simple methodology to create these over-arching plans, while also embracing the key value of iSquared; i.e. simplifying complexity.
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