When looking to improve an aspect of your business with big data, it's easy to jump straight to investing in new technology. Data-based tools, after all, are at the forefront of the modern business and seem to be able to do absolutely anything you could ask of them.
But, while new tools certainly are exciting, there's something you must do first before you can justify the expense - otherwise you risk being unable to achieve any kind of meaningful ROI (not to mention business result). So what is it?
Process optimization.
It's not as exciting, no, but it must come first - and here's why.
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People tend to view new tools, especially big data tools, as a magic wand. Invest, implement, and watch the results flow in. Let's say you don't have a risk management function right now, so you buy risk management software. Sounds like the problem is solved, right?
Unfortunately, it probably isn't. To keep on that risk management example, if the user of said software doesn't know how to perform risk management in the context of your business requirements, they won't know how to use the tool.
It's like trying to become a race car driver without knowing how to drive a car, or bake a cake in the best possible oven without a recipe to follow.
Technology is meant to support a process, not create one
Technology exists to serve and support existing business processes, and generally can't create a new one. Quite simply, any data-based tool (no matter how impressive) without a process behind it - that is, guidelines on where, when and how to use it - is doomed to be a poor investment as your people will struggle to get the most out of the investment. How do you change gears in a car? How much flour goes into the cake batter?
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We openly recognise that pitching 'process maturity' as a new initiative is not as exciting as 'we want this tool because it can achieve these results'. But a set of mature processes can take those tools and supercharge them - helping you push them to new levels that would otherwise have been impossible.
When we have mature bakery processes, suddenly a lot of complexity becomes a lot more clear.
Let's assume we purchase a risk management tool and deploy it immediately, without mature processes behind it.
So the big question after all of this is: if we have an immature process now, how do we identify and and - more importantly - improve it?
Here are two methods.
You can find opportunities to optimize processes by spotting problems as they occur 'in the wild', as it were. This is a reactive method rather than proactive - for a proactive approach, see below.
So what am I looking for?
What you're hunting for is a process that should exist, but doesn't, or a task that people are performing without a clear process. This task may be necessary to the business, but done informally, or perhaps it's unnecessary and therefore isn't adding value (i.e. wasting money).
Let's say you ask the risk management team for an overview of the company's cyber threat level. This one request will help you check the maturity of this process. How?
This is vital data! But there was no process to find it - that's a sign something is wrong.
Improving your immature processes, see below!
Checking processes reactively is absolutely fine, and a great way to spot and fill holes on the go. But, you can take charge of the improvement process and even get ahead of it by planning to optimize and ensuring it is done in a cost effective manner.
But how?
Learn more: For a detailed explanation on how to optimize immature processes, download our guide.
Data is key to unlocking the next phase of your business, and indeed modern technology such as AI, machine learning and automation can't function without it. But you can't just invest in data-based tools and hope for the best - every great tool needs a process behind it.
Immature processes create unstructured data that is hard to find, let alone use. Until these processes are improved (or implemented, if they don't exist), people won't know what to do or how to do it, which means they can't possibly make the most of their new technology.
So, the first step to any investment in data science and the technology that powers it is an investment first in process optimization.
Our digital transformation experts are here and ready to help you find those immature processes, plot out a roadmap to improving them, and fill in the gaps between. Contact us for a free maturity consultation and we'll see what we can do for you.