At Intelidat, we are focussed on delivery of top quality information based on quality data. We call it Intelligent Data.

Intelligent Data is planned and available to support your data-driven decision-making.
Our mission is to help business capture, store and use Quality Data by building a culture of Data Quality.

It all starts with your Information Strategy – click here to see more

8 out of 10 businesses struggle with data quality

Is your data:

  • Easy to find?

  • Available and accessible when you need it?

  • Includes everything you need?

  • Secure?

  • Detailed, granular, and unique?

  • Reliable and consistent?

  • Correct, accurate and up to date?

Then you have the basis of quality data

Data Driven businesses need top quality Information

Call 0330 043 6949 to schedule a call.

Why do you need an Information Strategy

What is data?

Data is just facts.

Putting facts together in context leads to Information: who, what, where, and when.

The application of data and information leads to knowledge – how & why.

Wisdom, is the application of our knowledge and information – it takes the questions of “why” and “what if”. It takes the results of our modelling and forecasting to deliver actionable insights.

Step 1 is to refer to your Information Strategy.

intelidat – what is data diagram

Do you have an Information Strategy?

If not, or you are not sure, or want to know more – Click here

Data Quality Issues

Machine Learning & AI

Integrated Business Systems

Data Stacks; Data Lakes & Warehouse

Digital Analytics & Funnel Optimisation

Data Security & Cyber Security Basics

At Intelidat, we trust in the value and power of Intelligent Data – how you acquire it, store it and use it.

We have been delivering quality information for over 30 years. The technology and uses of data might have evolved but the commercial drivers have just got stronger.

Quality Data is based on Integrated business systems

Business systems should bring about efficiency, they should be scalable and they must be secure.

But to deliver quality data, systems must be integrated across the business. One of the key causes of poor data quality is business silos. We see too many subsystems designed solely to meet the needs of a single process that makes the Business System less efficient.

Good systems are user friendly, so your users want to use them. They follow a logical process flow. Where possible, they use existing data and they perform both simple or complicated steps automatically. They manage your process and data quality. They are not tied by departmental or Silo boundaries. They promote best practices and enforce quality standards.

Good systems marry the needs of the user, the process owner, the department but, most importantly, they represent the needs of the business.

Can you buy a good system?

At Intelidat, we help you understand your existing systems and process flows, identify bottlenecks and inefficiencies and plan how to evolve to an integrated solution.

We know that you can buy a technology solution for a particular function but the key challenge is implementing that technology as part of an integrated business system. That needs a digital vision that marries commercial needs with software solutions that encompass the entire business.

Are you ready for AI – Artificial Intelligence is here.

Are you ready to take advantage?

What is the cost of poor data?

Many organisations still do not recognise the true value of their data.  Moreover they don’t realise that bad data can have a major negative impact on their business and that it can actually cost them money on a daily basis.

IBM has estimated that bad data costs the U.S. economy around $3.1 trillion dollars each year. Additional research from Experian also found that bad data has a direct impact on the bottom line of 88% of American companies, with the average company losing around 12% of its total revenue.

These staggering statistics come in spite of the increasing investment businesses are making in new business tools and AI initiatives. The fact is that the growth in the volume of data companies are accumulating seems to be inversely proportional to its quality with business leaders appearing to prefer to rely on their intuition when it comes to decision making.

Poor-quality data leads to poor decisions.

A decision can be no better than the information upon which it’s based, and critical decisions based on poor-quality data can have very serious consequences.

The growth of bad data represents a major impediment for organisations trying to maximise the strategic benefits that data can provide, while also posing a compliance risk.

Indeed, research by Royal Mail Data Services revealed that organisations believe inaccurate customer data costs them, on average, six per cent of their annual revenues. Perhaps more worryingly, over a third were not sure how much it costs them.

Data quality issues can increase exposure to a variety of risks, which would include compliance and financial risks.

  • Regulatory issues around reporting and protection of private information.
  • Operational risks arsing from poorly assed processes leading to health and occupational hazards.
  • Market risks through incorrect or inadequate industry knowledge.
  • Financial risks range from inadequate sales or operational facts, to the inability to recognise threats and opportunities.

Not only will inaccurate decision making derived from bad data cause various mistakes and inconveniences, but it will also lead to an increase in costs.

Research done by Gartner shows that the average yearly costs companies suffer due to poor data quality is around $9.7 million. Additionally, Gartner has also surveyed various organizations to learn about their costs associated with the impact of poor data quality.

They have calculated annual expenses at around $14.2 million on average. Bad data equals bad business; it’s as simple as that. Ovum Research has estimated that companies lose approximately 30% of revenue on average due to low data quality.

Fixing poor data costs a lot more than prevention.

1-10-100 the spiralling costs of poor quality data.

  • Back in 1992, George Labovitz and Yu Chang developed the 1-10-100 rule as a quality management concept to quantify the hidden costs of poor-quality.
  • When applied to data quality the supposition is that for every unit spent preventing poor quality data entering the data estate, will in turn save 10x units on fix/remediation activity and 100x units if nothing is done, leading to failure.
  • When relating this concept to data quality it must be recognised that the principle, rather than the exact numbers will apply.

The secrets behind good quality data?

An Information strategy aligns your data, information and technology needs, with your business processes, goals, and KPIs.

Map your Enterprise, System and Solution Architectures, develop your Business Glossary and build your data vision.

Define your Master Data Structure.

These are the foundations required before a business can aspire to be Data-Driven

Data Quality is underpinned by four pillars.

  • People
  • Processes
  • Systems
  • Technology

Getting all of these pillars working towards a common goal is the basis of Quality Data

Companies that recognise the value of their data recognise that the responsibility for Quality Data sits at the top of the business.

These companies recognise that the information & data quality champion is a C-level executive with responsibility for data across the whole business.

They will be an Information and Data visionary.

They will bring a vision to the data flow that will encompass all business systems.

Your strategy will define how data is named, stored, processed and shared across the business.

Who can take what action, upon what data, in what situation using what methods.

This strategy crosses silo and departmental borders and keeps the business goals at the heart of all data governance decisions

Businesses need a data vision that delivers quality data across the business.

Building integrated business systems requires a focus on the underlying data at all stages in the journey.

Many companies mistake the role of technology in Data Quality.

  • Technology may be at fault, however the key fault behind poor data often lies in Departmental Silos and inappropriate technology selection.

The key technology selection that any business must make is the technology that underpins the Data Stack

Where does quality data start?

Data Quality is usually rooted in the business culture.

Good Quality Data is a business responsibility
The culture starts from the top.

Who on your board is responsible for Information and Data Quality?

Quality Processes begin with Quality Data.

Data quality principles should be an integral part of your business systems.

Organisations increasingly share data.

Data centric organisations add value through data.

Systems should be integrated using collaborative data.

Technology is an important factor.

Systems based on Excel are a big contributor to poor data quality issues.  Despite this, Excel is the world’s largest “database”!


Enter data once, and use it many times is the first principle of quality data & integrated systems

Systems running in isolation of each other contribute disproportionately to data quality issues.

Data Quality – Searching for the Magic Bullet

There is no quick fix to Data Quality Issues.

The solution lies within the business culture: people, organisation and processes, systems as well as technology.

Data-driven starts with your Information Strategy

We can help

If you are wanting to develop a data-driven culture, we are here to help.

Start by understanding your business needs in your Information Strategy.

Book an online call at a time to suit you

How can we help?

Fractional Executive – COO / CIO

Mentoring services to help your team deliver a data-driven culture.


We have the experience to be able to review your processes, systems, technology as well as your people and organisation structure, in order to plan a route forward

Chief Information or Chief Technology Officer.

At Intelidat, we can support you with a fractional CIO or CTO to help you plan, deliver and optimise your data quality culture.

The CIO has an inward focus on all things data. The processes, systems, technology and culture that encompass data quality.

A CTO has an outward client-centric focus.

In reality, these roles are now merged into one.  The CIO is increasingly being pushed to the forefront of the executive board as the importance of Data Quality takes hold.

At Intelidat we can help you develop a Data Vision that brings your systems together into an Integrated Business System that supports a Modern Data Stack

Attending your board as a consultant with a responsibility for data, we look to help move you towards a data centric culture.

We advise as to how you can bring your systems, processes and technology together so they are working with your people and organisation towards a common goal.

Tracking how your marketing works, where your best leads come from, how they behave on your website or optimizing your Sales Funnels is definitely best managed through data.

Are you using a Digital Tracking Plan to understand your acquisition success?

Whether you are using Google Analytics or a paid analytics service, the quality of the data that you feed into your software will greatly enhance what you learn.

Wanting to understand how your visitors turn into leads, struggling with source/medium reports and spreadsheets. Try a visual solution.

Keeping your website fast and safe needs work.

We do not interfere with the creative process: we just help keep the site running safe and secure with some simple advice.

If you would like to arrange a Demo of our Risk & Compliance Tool, please fill in the enquiry form using the button below.