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
It all starts with your Information Strategy – click here to see more
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.
Do you have an Information Strategy?
If not, or you are not sure, or want to know more – Click here
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.
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
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
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”!
Systems
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
Data-driven starts with your Information Strategy
How can we help?
Fractional Executive – COO / CIO
Mentoring services to help your team deliver a data-driven culture.
Consultation
Get in touch…
If you would like to discuss your needs, please call 03300 436949, or fill in our online enquiry form.
For a full list of services and indicative pricing, please go to our Services Page.