A data strategy is a short, working plan for what a company's data is for. It names the decisions that matter most, the report or view that would change how the business runs, where the data for it lives today, and what to build first. 110 Analytics, a tech and AI company in Malta, works one out with your team through a free call and a data audit, then builds it in your own account and keeps it running.
Signs your business needs a data strategy
If two or three of these are said in your business, the gap is not another tool. It is a plan for what the data is for.
- Everyone has a different idea of which data project should come first.
- We bought a reporting tool before we knew what we wanted it to show.
- Our IT supplier asked what we want to report on, and nobody had an answer.
- We have data in every system and no idea which of it matters.
- We track plenty of numbers, and none of them changes what we do on Monday.
- I want to use AI on our data, but I do not know where to start.
- Every department wants its own dashboard, and nobody has said which one matters most.
Why do data projects that start with a tool stall?
A data project that starts with a tool starts in the wrong place. The software is chosen and installed first, and only then does someone ask what it should show. That question was the hard part all along.
Without an answer, the tool fills with whatever is easiest to connect. Each department asks for its own reports, built to its own definitions, and sales and finance bring different figures for the same thing.
Then the dashboards stop being opened and the monthly pack goes back to spreadsheets. The tool was not the problem. A dashboard full of the wrong metrics is worse than no dashboard, because it looks busy and changes nothing.
The opposite mistake is a strategy that stays on paper: a long document of recommendations, with nobody left to build it.
What is a data strategy, in plain terms?
A data strategy is a short plan for what your business data is for. It starts with the decisions you make every week and every month, works back to the numbers those decisions need, and checks whether those numbers exist and can be trusted. Then it sets the order of work: what gets built first, and what waits. It is written for the people who run the business, not for IT.
At 110 Analytics, the strategy is where every engagement starts: a free thirty-minute call with Glen, then the data audit, which produces the plan. The plan is then built in your own account and kept running by a fractional team, so the people who wrote the plan are the people who build it.
Not everything a business can measure changes a decision, so the plan says what to stop measuring as clearly as it says what to build.
What does a useful data strategy contain?
A useful data strategy answers a short set of questions, each one with your team and from what your systems hold today.
The decisions that matter
The few decisions that better numbers would change: where to put sales time, what to stock, how to price, when to hire. The plan starts here, not with the data.
The one view that would change most
The one report or view that would change how the business runs. It is the first thing built, so the plan is judged on something you use rather than on a document.
Whether the data exists
Which systems hold the numbers that view needs, from the accounting system to the spreadsheets in between, and whether the data is there at all.
The definitions to agree
The terms the first view depends on, such as revenue, margin or active customer. Each is agreed once with your team, written into the model and inherited by every report.
What comes first, and what waits
Everything after the first view is listed in the order it earns its place, so nothing is built just because it was easy to connect.
What to stop measuring
The reports and metrics that take time to produce and change nothing. Retiring them is part of the plan, not an afterthought.
What is in place by the end of the first month?
Implementation is the first month after you accept the quote. By the end of it, the first step of the plan is live: the one view that would change the most, on agreed definitions, current to yesterday. What sits underneath it is described on our business intelligence page, and how the audit maps it on our data audit page.
Everything after the first view stays on the list, in order, for the ongoing team to build next.
What a data strategy changes, in one business
A hospitality business in Malta runs several restaurants and a catering arm. Each restaurant has its own point of sale, the books are kept in an accounting system and staff rotas live in spreadsheets. The owners have a long list of data ideas, from a dashboard for every restaurant to trying AI on the numbers, and no agreed place to start.
- Every manager has a different first project in mind, so none of them has started.
- Each restaurant reports its takings its own way, and the owners compare them by eye at month end.
- Staff cost sits in the rota spreadsheets, so nobody can set it against what each service took.
- The next idea on the table is a new point of sale.
- The plan names one decision first: how to staff each restaurant, service by service.
- The view that serves it is agreed: takings against staff cost, by restaurant and by service, current to yesterday.
- Takings and staff cost each have one written definition, agreed with the managers and the finance lead.
- The points of sale, the accounting system and the rotas load overnight into one warehouse in the business's own account.
- The rest of the list is kept, in order, for the ongoing team.
No system was replaced. What changed was the order: the decision first, then the view, then the data, then the build. The AI idea is still on the list, after the definitions it would read from.
A strategy deck, or a data strategy that is built and owned?
Strategy without analytics is an opinion, and analytics without strategy measures the wrong things beautifully. This is how a strategy delivered as a document compares with one that is built.
| A strategy deck | A data strategy, built and owned | |
|---|---|---|
| Starts with | Interviews and recommendations | The decisions you make |
| First thing you can use | A document | A live dashboard |
| Definitions | Recommended in the document | Agreed with your team, written into the model |
| Who builds it | Someone else, later | The team that wrote the plan |
| Where the work sits | In a file | In your own account |
| When the business changes | Rewritten at the next review | Kept current by an ongoing team |
How we build a data strategy, step by step
- A strategy callThirty minutes with Glen, free, with no pitch deck. You leave knowing where your data is fragmented and what it is costing you, the one view that would change the most, and whether 110 Analytics is the right fit.
- The data auditAbout three hours with Glen and your team, mapping where each figure comes from and which steps are done by hand.
- The planThe audit maps where your numbers come from today and what the first step changes, so the plan names the one view to build first and the data it needs. It closes with a quote.
- The buildThe warehouse, the agreed definitions and the first dashboard, three to four weeks from an accepted quote, in your own account. Your team agrees the definitions; we do the building.
- The fractional teamAn ongoing team keeps the reporting live, revisits the plan as the business changes and builds the next item on it.
What we do not do
- We do not hand over a long strategy deck and walk away. The plan is short, and the same team builds it.
- We do not start with a tool, and we do not sell software, platforms or licences.
- We do not make your decisions. The plan says which numbers each decision needs; the judgement stays with your leadership team.
Glen Sultana founded 110 Analytics after a career built where the numbers move daily. Our people have run analytics for tier-one companies, S&P 500 firms and high-growth technology businesses. Glen is the person on the first call, and he runs every data audit himself.
- Built in your environment, under your account
- No lock-in: if we part company, it keeps running and stays yours
- Based in Malta
Straight answers
What happens on a strategy call?
It is thirty minutes with Glen, free, with no pitch deck and no salesperson. You leave with three things: where your data is fragmented and what it is costing you in decisions and reporting hours; the one report or view that would change how the business runs, and whether the data for it already exists; and a straight answer on whether 110 Analytics is the right fit.
Do we need a data strategy before buying a BI tool?
It helps to know what a tool is for before you choose it. A BI tool such as Power BI or Looker Studio shows whatever it is pointed at; it does not decide which decisions matter or what each number means. We recommend the platform before the build, based on what you already run.
How is this different from the data audit?
The data audit is one step of it: about three hours with Glen and your team, mapping where your numbers come from and which steps are done by hand. The data strategy is the thread through the whole engagement: the call names the one view that would change the most, the audit maps the data behind it, and the build starts there.
How long does it take?
The call is thirty minutes. The audit is about three hours of your team's time, with Glen in the room. Once you accept the quote, it is three to four weeks to the first live dashboard. After that, an ongoing fractional team keeps the plan current and builds the next part of it.
Who owns the plan and what is built?
You do. The plan is yours, and anything built from it sits in your own account and stays yours if we part company.
Do you work with our existing IT supplier or ERP partner?
Yes, alongside them rather than instead of them. The systems you run stay with your suppliers. We read the data from them, read-only wherever the system allows, and agree access and load timing with whoever looks after each one.
Where does AI fit in a data strategy?
Near the end, not at the start. Our AI layer answers plain-language questions from the same governed model as every report, so it needs agreed definitions and one source to read from first. Switched on before that, it has no agreed version of the numbers to read.
Who is a data strategy for?
Established companies in Malta where the data sits across several systems but nobody has decided what it is for, and where leadership wants to decide on evidence rather than instinct.
Data strategy terms, in plain English
- Data strategy
- A short plan for what your business data is for: the decisions that matter, the numbers they need, and what to build first.
- Data audit
- In our sense, a review of how a company's business numbers are made: the systems, the people and the steps done by hand. Not a GDPR or IT security audit.
- The one view
- The single report or screen that would change how the business runs. It is the first thing built, so the plan is judged on something you use.
- Order of work
- Everything after the first view, listed in the order it would change a decision, for the ongoing team to build next.