Does your team generate huge spreadsheets of data on a regular basis?
Do you have related information that is in different places or systems that you sometimes combine manually?
Do you sometimes have people entering the same information into one system when some or all of the same information is also in another system?
Perhaps you have heard someone say, “You can find that information here… oh… but don’t forget to check that other system as well…”
Have you ever been in a meeting where someone has shown a chart and rather than use it to make a decision, the group questioned the validity of the chart itself? Perhaps the person that prepared it wasn’t able to provide important details about what was factored into it? Perhaps there was a suggestion that some items were omitted or others double counted?
If so, read on, because you probably should be looking at data integration.
Data integration – what is it?
Data integration is the process of having your various systems talk to each other so that you can have your data combined when you need it to be, and where it is duplicated then all the systems can get the same data from a single system (called “the single source of truth”).
How does it help me immediately?
Studies show that highly data-driven organisations are three times more likely to report significant improvements in decision-making compared to those who rely less on data.
However, for very good reason executives will only make data driven decisions if data are beyond question.
To have data driven decisions, data has to be up to date and accessible yes, but even more importantly it has to be understood. There has to be a way to know exactly how data are collected so that we can explain anomalies. We have to know what’s included and what isn’t. We have to know how often it gets updated and when we need to reconfirm a result we have to know we’re starting with the same data we had last time.
That’s why data integration is pivotal to affecting any change towards data driven decision making.
How does it do that?
Data integration is the simplest way to ensure your data is complete and up to date whenever you use it. Not only that but having your data integrated properly allows for incremental improvements in efficiency and encourages data-driven decision making at all levels in the organisation because it is fundamental to turning your information into a single managed asset where everyone is using the same source of information and is able to agree on its accuracy and interpretation.
By way of example, we often help our clients integrate systems. By far the most common integration is intended to allow details of their staff names and email addresses to be propagated from a central system (often it is the payroll system) so that as soon as people are employed, they gain instant access to other systems and as soon as they depart, that access is suspended.
Equally importantly, changes to information are kept up to date as well. When a person’s name or title changes, that update is made to the payroll system and everything else picks it up instantly, unlike in the old manual-update days where some entries might be overlooked.
How does it help me in the long term?
It’s also the first step towards automation either now or in the future; when there is a well structured information source it becomes much simpler to set your systems up to respond to pre-set patterns, such as triggering onboarding actions as soon as a new entry is made in the staff list, setting up reminders for people to refresh their certifications as they expire or setting critical reports up to be generated overnight each month.
Not only that but it makes your systems much more flexible. With integration comes standardisation. With standardisation comes the ability to move more easily between platforms when you need to. How often has a project been stalled because “it would be really hard to replace what we have now and we just don’t have the resources. Let’s keep it going a bit longer…”. Organisations with effective integration strategies do not confront these problems and can upgrade systems when required with much lower levels of difficulty.
How does it work?
From a technical point of view, most good systems are designed to be integrated (that’s not always true, but it usually is). That means that data integration is often a matter of enabling features you may already be paying for!
Despite that, technical people are involved in the process for two main reasons:
1. Security: Whenever information is shared, it’s critical to do so in a way that you can be confident does not expose it to theft or interception. This isn’t as hard as it sounds – it’s a matter of following standardised procedures, but as technical people are typically the best place to know those procedures, we involve them.
2. Normalisation: Even when two systems can have integration simply turned on, there is usually a translation involved. Your systems may well be designed to talk to each another, but they may not “talk the same way”. For example if one system sends a date to another as 8/7/2025 then some systems will interpret it as the 8th of July while others understand it as the 7th of August. A name sent as “Michael”, “Connor” leaving another system unsure which is the given name and which is the surname. Technical people have access to extra tools (translators) that can sit between the system and ensure information is received in the exact format a system expects it.
Where do we begin?
As with any strategic decision. Plan.
Begin by agreeing on some well-defined goals that align to broader business goals. For example, if you have a business objective to reduce staff turnover through staff development, then your training results should feed into information gathered during staff appraisals in a way that allows for generating training plans that factor in knowledge gaps that stand in the way of career aspirations. As these gaps are bridged and staff are prepared for the next stepping stone in their career, this information needs to be surfaced when internal vacancies become available.
Armed with clear goals, your integration team can determine the best way to realise them. They will be able to identify the most reliable sources and factor in any exceptions when they know clearly what is the intended use.
It will allow them to ensure that the right data goes to the right people at the right time. It also allows them to restrict sensitive data access so it is available on a need to know basis.
What’s the cost?
Probably less than you think. There are expensive data integration tools on the market but unless you have dozens of systems participating in very complex and highly automated processes, you probably won’t need one. You are more likely to pay only for people’s time getting the systems ready.
The amount of time required will depend on the number of systems involved and the level of experience of the team. While vendors’ rates vary we’re more than happy to share our own rates as an indication. When we install a system for a client who wants it integrated to another system on their network we charge a flat once only fee of $AU 5000 ($US 3500).
Check with your own systems’ vendors for their rates but assuming they are similar to ours, it’s not a lot to spend on a gift that will keep giving permanently.
