Businesses typically take time to grow. The great majority grow through incremental gains – perhaps through referrals to new potential customers, success with a tender, sheer perseverance attending conferences and trade shows which eventually yield new contacts.
Data helps those marginal gains to be bigger and to arrive more often. And it can often open the door to quick wins that will give your business an immediate boost.
In this blog we look at why data is matters when growing a business, and what it takes to ensure success.
Value comes from visibility
Using data should be like shining a torch into your business. It can reveal what’s working and what needs to work better, what your prospects and customers are doing and talking about, whether you have competitors catching up with you, and a whole lot more.
Some opportunities to make gains will jump out. Others will only appear after extensive digging.
However, as you start to see more you will also start to make better strategic decisions, simply because you will be more confident about what you have to do to build a stronger and more sustainable business.
The reward from your use of data can be substantial – in terms of additional revenue, capacity growth, and reduced cost. But there’s an important prerequisite that has to be met – you need to first figure out what you are looking for, and when you find it, how you will use it. This will ensure you don’t dedicate large amounts of time and cost for minimal gains.
A Digital Marketing Agency suspected some of their services to clients were costing more than they received in revenue. They knew they needed to focus upon the hours being worked and the revenue billed. Once the relevant data was given the light of day it revealed where spend needed to be reduced and contracts re-negotiated.
An electrical contracting company discovered year-end profit was well below expectation – given that every contract had a pre-determined margin built into the price. They knew they needed data to show whether work was not being invoiced, or contractors were being paid for work that hadn’t been authorised. Once assembled it revealed how profit could be returned to planned levels – yielding an increase from 12% to 25% in their return on sales.
A logistics company with over 130 trucks and vans wanted to find any way possible to save fuel. They wanted data to show how much fuel could be saved through better driving. This would allow them to put a compelling case together for additional driver training. The return – a 5% saving on an annual fuel bill of over £1mn.
A sales training company wanted to expand across Europe and the US. They wanted data to reveal which businesses might be looking to train their staff – perhaps because they have opened a new office, or announced a major growth in staff numbers. Once they were able to source the relevant data they were able to knock all their sales targets out of the park.
Figuring out what to look for
What if you want to put data to work, but you are unsure what to look for?
This is a situation facing a great many businesses. There is however a simple diagnostic that can put you on the right track..
It’s based upon the principal that, for most businesses, there are seven fundamental drivers for growth.
Prospects – your target audience who don’t yet know you are there.
‘Possibles’ – Prospects who have responded to you in some way and who could possibly become customers (they’re sometimes called suspects however this implies they are somehow ‘suspected’ of something).
Purchase behaviour – how often and how much customers purchase from you.
Doing more & better for less time and cost – finding ways to lift quality, service & capacity for less time and money.
Pricing – getting it as right as possible.
Funding – winning the hearts and minds of potential backers.
Profit – boosting, trimming and pruning customers and contracts based on the margin they deliver for you.
E.g. Prospects are a driver for growth because if you increase your pool of prospects you are likely to then increase your pool of Possibles. Similarly, if you increase your pool of Possibles, you may see an increase in customers. Improve the purchasing behaviour of your customers and you might earn more from them and spend less time and cost serving them .. and so on.
The diagnostic starts with the question – ‘which driver would deliver the biggest return if you could increase the number associated with it by, say, 10%?’.
To answer this question, some simple metrics are useful. For example, if you have a large number of Prospects to whom you are reaching out, but a much smaller number of Possibles, increasing your pool of Prospects by 10% might not be much use, but 10% more Possibles might yield more customers.
However, it’s likely that you will already have an idea which drivers you would like to focus upon first – which is exactly what we need in order to move forward.
Framing the critical questions
The path that you then follow involves a sequence of further questions to the point that you have a small set of ‘critical questions’ – the answers to which would give you a clear direction in your use of data to shape decisions.
E.g. the critical question for, say, a Charity providing support services for Children might be ‘in the Programmes that have delivered the best outcomes, what factors have done most to influence those outcomes?’.
The question is a good one if it makes it clear what data you will need to provide an answer – in this instance tables of outcomes from support Programmes alongside characteristics of the inputs e.g. child age, the nature of the issues bringing them to the Programme, the staff involved, the number of interactions, the size and mix of child cohorts.
It is a good question if it also reflects the value associated with the answer – e.g. the ability to develop and promote more support Programmes that have a high probability of success.
Questions about doing more for less time and cost can prove to be a greater challenge. There are a myriad of places to look. However if you start with questions that relate to the customer experience such as ‘what does the customer think about our quality of service’ you will be directed to data that may carry vital insights about aspects of your business that are not working so well.
This will prompt a further set of questions that may direct you to data that exposes delays and complications that may be hidden to you but be obvious to the customer.
It takes many iterations before the right question starts to reveal itself but the effort is worth it.
You may then be able to go straight to the data that you need. Or, if the data doesn’t yet exist, be able to create it out of the data sets that you do have access to – or commission its collection.
Whichever it is, you are going to minimise the time you spend searching data for insight, ‘wrangling’ it into the shape needed for next step – visualising it and exploring it for the information you need.
The next steps
In the next blog we will look at what happens next. If everyone in your business has agreed the questions you want to answer first, you can start to build definitions for the data you will need and plan how you are going to bring the answers to the surface.
We will explore the tools and skills that will help you to get going, and we will look at how to go about developing that all important visibility.
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