AND WHAT TO DO ABOUT IT!
Most, if not all business leaders today, recognise the value of their data and analytics function without necessarily realising the benefits.
As a result, many boards are looking at their Analytics function and wondering how and why they haven’t managed to extract real value.
Outlined below are my thoughts on the top 10 mistakes businesses unwittingly make when trying to build their Analytics capability – and what to do about it.
1. Putting the cart before the horse
Taking a tool or technology first approach rather than taking the time to understand what the business is trying to achieve could be a costly mistake.
Start with the business objectives and only then determine the data, tools and technologies best suited to deliver those objectives.
Remember, real transformation starts with Strategy not technology.
2. Ignoring the human element
As you build your data infrastructure, it is all too easy to forget that it’s not just about the data. You already have experts within the business so why not use them? How you build in subject matter expertise as well as company and industry knowledge is key.
It’s the combination of people, process and technology that delivers real value and actionable insights.
3. Trying to run before you can walk
In other words, wanting to do advanced analytics and data science before putting the fundamentals in place.
To avoid this problem, first determine what state your analytics capability is in, then where it needs to be in order to deliver today’s answers while still planning and building tomorrow’s capability.
4. No end state vision or clear data strategy road map
Understanding the company’s long term business objectives is key to determining the role that your analytics team needs to play to help deliver them.
The key question here is, what role should data engineering, data analytics, data science or machine learning take in delivering those objectives?
5. Limited understanding of the skill sets required
It takes more than just good operators to create a First Class Analytics function.
You also need business savvy analysts and data scientists as well as strong data and analytics leaders who understand the benefits and can influence at board level to help drive change across the organisation.
6. Unrealistic or misaligned expectations
This can lead to falling for the hype peddled by ‘cowboy’ sales people and then blaming the tools or the analytics team when it goes wrong.
Better to step back and understand where you are today, determine where you need to be and to have a clear, informed view of what the business needs from data and analytics.
7. Lack of senior management buy in
It is imperative that senior management understand what data analytics can and cannot do.
Unfortunately, it is often the case that senior management don’t really see the need for a strong Analytics team that adds real value. As such, they only partly buy into investing in the required skills and resources.
When this happens, it will always be difficult to champion analytics across the organisation. Being able to demonstrate the potential added value in language that senior management understand is vitally important.
8. Handcuffing the Data and Analytics team
This comes back to understanding what the data and analytics team can do and ensuring that they have the right data and technology resources to deliver.
Don’t put them in a dark corner and restrict their access to decision makers or to data.
Without data there is no data science, data analytics or data anything!
9. Thinking data and analytics is JUST a support function
The Data and Analytics function, if deployed correctly, is a business critical function with immense transformative power. However, it is obvious that too many Boards are dismissive of the power that good data analytics can bring to the business and often invest just enough to achieve the bare minimum.
Access to fast, accurate data and analysis enables more informed and quicker decisions which in turn accelerates business growth and profitability. Without this, the business will wither, become obsolete and out of touch with what customers want.
10. Giving in to personal bias
People love to make decisions based on personal biases, intuition and the loudest opinion in the room – Don’t!
While expertise clearly plays a role in decision making, strong analytics and data provide the best foundation for decision making.
11. Bonus point – Getting side tracked by BAU
It is easy to tie up resource on today’s fixes rather than tomorrow’s solutions because they are always urgent!
But as important as managing BAU is, growing the business also means you need to have the analytics team focused on the future.
That being said, your team may not always have the bandwidth or skillsets to handle both. If so, perhaps this is the time to consider bringing in external expertise that can work strategically alongside your in-house team to deliver today while building for tomorrow.
Avoiding these mistakes is crucial in building a First Class Analytics function. In particular, the importance and value of senior management buy in and end user adoption should not be underestimated - but it often is!
I make no apologies for repeating that real transformation starts with Strategy, not technology. You will see the benefits of this approach when the analysis outputs provide accurate and timely insight, which is then taken up and acted upon by the commercial teams to accelerate business success.
The above is not an exhaustive list, and not all of this will apply to every business, but I’m sure that a number of these will resonate with you.
If so, we'd be delighted to offer you a free 30 minute consultation to help determine where you are in your journey and how best to navigate the different stages to achieving analytics maturity.
If you're open to that, please click here to contact us and we'll be in touch to schedule a call.
Brendan launched Blue Label Consulting in 2011. With innovative use of Data through AI, ML and other quantitative methods, he delivers robust analytics and actionable insights to solve business problems.