The art of making data work for you
Digitality gives business operators extraordinary power to collect data, but Macks Advisory has discovered all too few of them have acquired significant skill in mastering the art of making their data collections work for them. It’s a skill that’s a blend of science and artful instinct that practitioners can use towards not merely attaining survival but winning the race to success in their industry.
Bear in mind that while numbers are reliable indicators of where a business is going, they shouldn’t be relied upon to make decisions on how to get there.
Using numbers to govern decision-making can be problematic, especially for newcomers to a business who lack experience assessing data and acting on the assessment, or don’t have the necessary tools/resources to do what figures indicate should be done -- but they try to do it anyway.
It’s important to remember that when next you’re faced with making as crucial decision for your business, the worth of what you decide could to a very large extent depend on importance of the data you employ, how much of it you use, and whether it’s consistent in how it relates to the growth of the business throughout its historical life cycle.
Collection of the right data and utilising it effectively to create actionable insights for your business is of course easier said than done. We suggest you consult a proven expert on the most appropriate data collection and management tools for your business.
Choosing the right tools
While analytics, artificial intelligence (AI), and machine learning (ML) all play key roles in data collection and use, data quality and sound business data practices are equally important. As far as IT is concerned, companies assemble quality data using a master data management (MDM) methodology that defines how data is collected, aggregated, matched, consolidated, quality checked and distributed.
There are plenty of tools and automation solutions available for MDM that reduce the tedium of manually culling data, normalising it, deciding what parts of it should be matched with what other parts, and who in an organisation should receive which data.
It’s because businesses have varying specific requirements of data, that to maximise its use operators are likely to need specific expert advice about necessary tools.
Even then, the importance gut instinct will often still play in decision-making is graphically illustrated by a resource that referred us to Netflix’s international competition to produce an algorithm that would deliver at least a 10% efficiency gain in a particular area of management. The winning algorithm produced the required result but has never been activated -- because the decision-maker had a hunch (subsequently proved correct) that engineering necessary to allow the algorithm to function, would cost more to install and maintain than the worth of the 10% gain in efficiency it produced.
Down to the nitty-gritty
Yet numbers are undeniably important – especially those that determine key performance indicators – but business operators must acquire ability to recognise and unpack nitty-gritty data collected along the way in determining major indicators.
For it’s this timely unpacking and questioning of data packages that prevents money being spent on under-performing projects that can never come good, or on figures relating to customers and potential customers than show they aren’t interested in services and products the company offers.
A mounting pile of anecdotal evidence shows companies’ employees, whether working in offices or from home, aren’t focusing on putting data collections to work. They aren’t aware of the extent to which data can contribute to decision-making, or the extent to which it can maximise profit from the 20% of customers on whom 80% of the worth of a business traditionally depends.
We have difficulty understanding why, with necessary information so readily available, so many business owners fail at least to make sure their best employees are focused on attending to the needs and encouraging the aspirations of that 20% of customers so vital to 80% of their companies’ business.
Data-informed v data-driven
Data-driven organisations are propelled as a rule by numbers that dictate when staff should be moved on when targets aren’t met, that determine when product lines should be changed to increase market share. In short, numbers are regularly employed as emotionless servants of ruthless employers who believe mere figures should be regarded as arbitrary indicators of what will work best for a balance sheet.
But if you’re predominantly a numbers person you are in danger of being beguiled by a set of quantitative data that can never give you a full-picture view of a situation.
In contrast, data-informed managers, while they are happy to consider what quantitative data tells them needs to be done to enhance a balance sheet, also want to see data indicating the best way to get where this quantitative data indicates their organisation should be going.
Thus, they know they must also collect data on what competitors are doing, where their industry seems to be heading (and why), while leaving room in any major decision-making process to exercise gut instinct.
Trainers decide to put blinkers on certain horses to minimise distractions and help maintain focus on what’s immediately in front of them. But it’s the data-informed brains of jockeys – because the riders are not only looking forward, but also to right, left, and occasionally behind them, to see what competitors are doing – that enable jockeys to have as much, if not more influence on race results than horses.
Our conclusions
All businesses, large and small, can benefit from core analytics that help them gain insights into customers that can be employed to enhance bottom lines by optimising marketing and delivery of better products.
Without analytics companies are ignorant of sources of potential customers, and of existing customers’ needs and aspirations. Analytics can at least give business operators quantitative data needed to make informed decisions that can generate profits.
If you want to make business decisions based on data – and data tells us you should be doing this – then resolve to periodically revisit and revaluate core assumptions you make about your business. The more you question these assumptions, the more you remeasure and engage in fresh analyses, the more secure and probably more profitable your business is likely to be.
