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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.
In a world of ‘big data’ and information, more and more businesses are striving towards digital transformation as a way to keep up with the ever-changing technological landscape.
So what exactly is digital transformation and why should you be making it a focus for 2021? Here, we’ve outlined everything you need to know about this increasing business trend.
Digital transformation has taken on many meanings in today’s digital era of big data and data management. The truth is, it’s a term that can mean multiple things to different businesses, depending on a company’s main priorities and overarching end goal.
Broadly speaking, digital transformation is the practice of integrating digital technology into all areas of a business, significantly changing how it operates and provides value to customers. In doing this, digital transformation also requires businesses to rethink old models, become more agile in responding to new problems, get comfortable with failure and continually challenge the status quo.
According to Jay Ferro, CIO of Quikrete, digital transformation should begin with “a problem statement, clear opportunity, or an aspirational goal” – basically, your company’s ‘why’. This could revolve around improving customer experience or increasing productivity, or something more aspirational, like becoming the absolute best in your industry using new digital technologies you didn’t have years ago.
There are several reasons a business may decide to take on a project of digital transformation. But for many, the most basic and common reason is survival – they simply have to.
An organisation’s ability to adapt quickly to potential manufacturing disruptions, market pressures and changing customer demands is critical to its long-term success. This has become even more apparent in the wake of the covid-19 pandemic, when consumer habits shifted dramatically and businesses were faced with totally new and unprecedented challenges.
Recent studies show that increasingly the digital transformation process is being viewed as a long-term investment, with relevant initiatives set to take over a 50% share of worldwide technology investment by 2023. Technology is no longer just a choice – it’s a fundamental business strategy that must be part of wider operative-initiatives.
Five common ways that digital transformation can help your business are:
As just mentioned, data and analytics can play a key role in an organisation’s digital transformation efforts. Stats show that fewer than 50% of documented corporate strategies mention data and analytics as essential components for delivering enterprise value, according to Gartner, but this is changing. By 2022, it is predicted that 90% of corporate strategies will mention big data and analytics as a critical enterprise asset.
The answer, therefore, is clear: data and analytics competency should be paramount within your business for digital transformation success. This means defining a strong data strategy and implementing the relevant data transformation methods in order to make the absolute most of the information available.
Leading organisations in various industries are wielding data and analytics as competitive weapons, using them to accelerate growth and inspire innovation. But many companies still struggle under the weight of their traditional business models and processes that may not allow for the potential that data and analytics can bring. Others may also not be able to make the cultural shift needed to work with big data, or commit to the information management and analytics skills needed to truly make the most of its power.
Here at Bespoke, we provide various solutions to help you transform your data strategy. From direct consultancy to our range of out-of-the-box automation and analysis tools, we can guide you every step of the way towards making the most of big data. Simply get in touch to arrange a free initial consultation with one of our experts.
It wouldn’t be entirely surprising for companies to ask: is there an end to digital transformation? How can we know when we have reached it? When will we be able to say we have truly achieved digital transformation?
A more relevant question might be, what comes after digital transformation? Is there a next phase, and what will we call it?
Gartner has named the period beyond digital transformation as the ‘ContinuousNext’, which will reflect the capabilities all companies need to keep up with the continuous change driven by technology.
ContinuousNext is a formula for success in a world that is constantly changing…”through and beyond digital transformation”. Meanwhile, Accenture is naming this period as the “post-digital era”.
Overall however, industry experts agree that digital transformation is a continuous process, as technology will always continue to advance rapidly, coupled with ever-changing consumer behaviours. Rather than view digital transformation as an end goal, organisations will have to consider it a constant process that will enable them to adapt, evolve, and drive forward change within their field. Ideally, it is the state of flow that all businesses should be striving for.
Get in touch to find out how Digital Transformation can revolutionise your business.
