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Most businesses collect far more data than they ever use. It comes in from your finance system, your CRM, your operations tools and the spreadsheets people keep on their own desktops.
Gathering it is the easy part. Knowing what to do with it is where most organisations get stuck.
So here’s the short answer. There are five things you can actually do with your data:
The rest of this blog takes each one in turn, with the Microsoft tools that make it practical and a sense of what good looks like.
Data on its own does nothing. It sits in storage, costing money, waiting.
It becomes useful the moment it changes something. A decision made with more confidence. An afternoon of manual work saved.
The problem is rarely a shortage of data. It’s that the data lives in too many places, in formats that don’t talk to each other. Getting a straight answer means someone exporting from three systems and stitching it together in Excel by hand, and by the time the report is ready the moment to act has passed.
Everything below closes that gap between having data and getting something out of it.
The most immediate thing you can do with your data is see it clearly.
A dashboard built in Power BI pulls figures from across your systems into one live view, so your sales numbers and your operating costs sit side by side and update on their own. Nobody waits for the monthly report. The people making decisions can see where things stand at any point and act on it.
We worked with Otsuka to move their reporting off Excel and into Power BI. That cut 4 days of manual processing and gave the team that time back for the decisions themselves rather than the spreadsheets behind them.
Good analytics answers the questions you already ask every week, faster and with less doubt about whether the numbers are right.
Once your data is in order, it can do more than report the past. It can give you a fair view of what happens next.
Forecasting reads the patterns in your history and projects them forward: the stock you’ll need next quarter, or the customers drifting towards leaving before they actually go.
Power BI and Microsoft Fabric bring machine learning into this without a data science team on staff, so the modelling runs on your own numbers and updates as new data arrives.
Seeing a shift early gives you room to plan around it, while you still have options.
A lot of what people call working with data isn’t analysis at all. It’s admin.
It’s the low-value handling that fills a working week:
Power Automate takes that off their plate. Invoices get captured and logged without manual entry. Records update across systems the moment something changes. Reports build and send on a schedule with nobody touching them.
We automated our own invoice processing and cut invoice handling time by 60%, taking the approval chasing off people’s desks entirely.
Speed is the obvious gain. The one that matters more is consistency, because work that runs automatically runs the same way every time, and that strips out the small errors that creep in when a person repeats a task a hundred times. Your team gets their hours back, and the data they hand on is cleaner for it.
The newest thing you can do with your data is hand it to an AI agent.
An agent is software that takes a request in plain English and acts on what it finds in your data. Build one in Copilot Studio, connect it to what you already hold in Microsoft 365 and Dynamics 365, and it can draft a proposal from your CRM records or pull a report together from scattered project notes without a person doing the legwork.
This is where organised data pays off twice. An agent is only as good as the data it can reach, so the businesses getting real value from AI tend to be the ones who sorted their data first.
We build custom agents like this in eight days through Agents in 8, working with the systems a business already runs on. We worked with WeChange.AI to build a proposal agent that now saves them 7-10 hours a week and has lifted their win rate by 20%+.
Every use above rests on one thing: your data being in a fit state to use. This is the step that gets skipped, and it’s usually why data projects stall.
In most organisations, data is scattered across systems that were never built to work together. Microsoft Fabric brings it into one place, so your reporting, forecasting, automation and AI all draw on the same trusted source instead of a dozen that disagree.
Get the foundation right first, and everything above gets faster and more reliable. Skip it, and you spend your time explaining why two reports show different numbers.
We did exactly this for a plant hire firm, unifying their data with Microsoft Fabric and Power Platform. It now saves them £97k a year.
This is why Bespoke treats AI, automation and analytics as one conversation. They run on the same foundation, and the businesses that get real value build that foundation first.
In fact, you shouldn’t try.
The organisations that get value from their data usually start with one problem worth solving. A report that eats a day every month. A forecast nobody trusts.
You don’t need a big budget or a rip-and-replace project to begin either. Most of this runs on Microsoft licences you’re probably already paying for, working alongside your current systems rather than replacing them.
The harder part is knowing which problem to start with and what it’ll actually take. That’s what a Triple A Assessment is for: a one-day engagement that looks across your AI, automation and analytics options and hands you a ranked list of where the value is and a clear first step.
If your data is doing less than it should, that’s the place to start.
In a business, you use it to make decisions and remove work. That means reporting on how you’re performing, forecasting what’s ahead, automating the manual handling and, increasingly, feeding it to AI agents that act on it. On its own data does nothing. It earns its place when it changes a decision or saves someone time.
The main uses fall into five groups: reporting and dashboards, forecasting and prediction, automating manual processes, powering AI agents and unifying scattered data into one reliable source. Most data projects are a version of one of these.
The same things larger ones can, at a smaller scale. One dashboard pulling sales and costs into a single view, or an automation that handles invoicing, can be built without a big team or budget. Start with one clear problem.
Pick one problem worth solving rather than launching a broad data programme. A Triple A Assessment is a one-day way to see where the value is across AI, automation and analytics and leave with a ranked first step.
The amount of data generated, consumed and handled on a day-to-day basis is bigger than ever before. ‘Big data’ has transformed business practices, to the point where a company’s use and collection of data can be integral to its success.
More data of course means more processing, which can significantly add to your company’s workload. That’s where data automation comes in.
With a reliable automation system, mundane data handling tasks can run effortlessly in the background, freeing up your workforce to work on other things and increasing overall results.
Data automation can be achieved using business applications such as Excel and Power BI. It is implemented to take over general ongoing data-related tasks that would usually require a lot of time and energy.
Types of data automation include:
Data automation can be used in various departments within businesses from a variety of sectors. Some of the most common can include:
Perhaps least surprisingly, data automation saves a tremendous amount of time. Not only can it take care of multiple processes at once, but it also saves staff from having to perform arduous, time-consuming tasks, such as data collection, filing, analysing and processing. This frees up your workforce for more important projects, thus boosting overall productivity in other parts of the business.
Data automation also leads to increased visibility. Imagine clusters of filing cabinets in different places, all stuffed full of important data that was a chore to sift through. Thanks to cloud-based storage, data can be made available to anybody who needs it from wherever they are. Saving precious time and streamlining workflows.
Many manually processed documents like invoices will pass through several hands before finally being approved and paid. In fact, research firm Gartner found that the cost of processing invoices in the UK was on average anywhere between £4 and £25, with some businesses even spending £50 per invoice.
Meanwhile, data capture automation has been found to cost up to 20 times less than manual data capture. Providing a seriously lucrative opportunity for businesses to shave pounds off their processing costs (and take pressure off finance teams!).
Many accounts-payable departments have numerous hidden costs and expenses. Not to mention that manually storing data requires added labour, organisation and office space costs. Imagine how much you could save…just by automating your data processes.
Because automated data systems can process many datasets or documents per minute. This helps to increase output massively, leading to faster turnaround times, more relaxed staff and inevitably, happier clients.
As well as encouraging more satisfied staff (who will surely appreciate not having to spend endless hours on mundane data entry tasks), it also frees up space in the business for growth, creativity and innovation. It can be said that a company is only as good as its data. Continuously monitoring, refining and modifying one’s business strategy requires access to accurate and relevant data, all of which will contribute to sustained business success.
Data automation doesn’t just make it easy to collect and access data; it also provides extra security too. Most automated data management systems continuously create back-ups of your data in the cloud, so your data is always available and always preserved.
As mentioned earlier, data capture and processing can be difficult, time-consuming tasks – ones that very few people can do for hours on end without making a mistake.
Natural human error and eventual fatigue will undoubtedly lead to errors somewhere along the line. Meaning lost time and more costs for your business to put right. Remembering the 1-10-100 rule, a company could spare far more money by ensuring they have all their data processes properly automated, in order to prevent as many errors as possible and be able to detect and address issues quickly when they do come up.
This will in turn lead to a smoother, more improved service for your clients and set your company apart from its competitors.
Our Power Automate consulting services can help you find an effortless automated data solution that fits seamlessly into your business.
Get in touch with our team of Power Automate consultants to discuss your business needs. Or take a look at our range of solutions to see what we can do for you.
