Most small businesses will be aware that a data breach has the potential to wreak havoc, and high-profile cases like the TalkTalk data hack in 2016, which saw the data of 157,000 customers being stolen, highlight how serious the consequences can be.
How and where businesses store data, how it’s accessed and the permission levels around it all fall under greater scrutiny with the introduction of GDPR in May 2018 so data management and governance now need to be a core component of business strategy, as they affect every part of the business.
Starting with a full data audit is recommended as it will give valuable insight into what data you hold, and can quickly highlight changes you should make immediately. Organisations might feel they know exactly what data they’re responsible for, but in many cases, information can be spread across multiple platforms and systems, both virtual and physical, and it’s easy to overlook some sources.
Once the audit is complete, businesses can begin the process of categorisation of data, and consider what their broader organisational needs are. For example, they might be looking to create a data hub to manage customer relationships, or they might experience issues with data quality that need to be addressed. Requirements for data management strategy vary significantly, but there are a number of common considerations:
– What sources of data are there?
– How much data is there (new and existing)?
– How long should data be retained for?
– How valuable is the data?
– Who needs to access data and where should you apply restrictions?
– What devices will employees use to access data, and where will they be accessing it from?
– What is the data’s place in the data lifecycle?
– What do we want the desired outcomes of the new strategy to be? (eg reduced overheads, being more compliant, efficiencies in capacity utilisation)
Once these questions are answered, businesses will have a clearer picture of the data they hold, and where it belongs in the data lifecycle. The categorisation process also helps businesses to delete anything they no longer need. This in itself will help them prepare for GDPR, which enforces tighter rules on the scope of data that can be retained and how it’s stored.
There are tools in place which help to automate data management, and although they can prove very useful, it’s important that organisations ensure proper training around them; as human error is still the biggest source of security breaches today. Equally, each department should understand the link between good data management and positive business performance, which will help gain buy in and momentum as you implement the new strategy. This education process also helps cement data ownership across the company. If a department is responsible for a specific data set, and they understand why compliance and management is a priority, they are likely to take the ownership more seriously and consider it more within their day to day role.
Finally, agreeing KPIs for the new strategy is crucial. Most businesses will define a data management strategy because they are concerned about cost, compliance and performance, so desired outcomes should reflect this. If your business wants to drive down overheads, or improve system capacity, put some key metrics against this so you’re able to properly determine success, and if necessary, adjust it according to business need.
Ultimately, if your data management strategy has been well designed, your organisation should enjoy reduced costs, greater agility and efficiency, and importantly, increased confidence about compliance. Although it can be a lengthy process, these benefits make it well worth the time investment.
Andy Hinxman is director of Keybridge IT.
Further reading on data management strategy
Cut the cost of inefficiencies without laying waste to your assets
Andrew Millington, managing director of software company Exclaimer, designed an add-on programme to his customer relationship management (CRM) system in order to improve data management. He says it has increased his turnover by 20 per cent.
‘The problem was that we had a high volume sales system, with only four sales people getting 100 leads a day across different countries, all of which needed to be chased in the right order at the right time. We were also gathering important market feedback through the questions we were asking, which was analysed in the CRM.’
Millington decided to create his own software to improve staff performance and to refine the quality of his market research. ‘It’s a script designed so they can’t progress without entering answers to each question and if a customer is meant to be contacted at a certain time an alert will go out.’
Rob Karel, principal analyst at technology and market research company Forrester Research, says that more companies are adopting data management technologies as a way to improve returns on IT investments.
‘The vast majority of data management enquiries I field from my clients are not about technology,’ says Karel. ‘They’re about the soft stuff: how do we organise ourselves, how do we build a business case, how do we engage the business, how do we define return on investment, how do we decide roles and responsibilities. This is what my clients are feeling pain around; this is data governance.’
All-round performance
The term data governance describes the best practices for handling data that organisations should adopt if they are to derive the most value. ‘Those organisations that have done it well have done it in a very targeted fashion. If you aim to govern the 20 per cent of the data that impacts 80 per cent of your processes and operations, that’s a great start,’ he says.
However, Karel adds that it is no good simply investing in new tools. Businesses seeking to solve deep-rooted data quality problems that have undermined their long-term IT investments must begin by sorting out whose responsibility it is to maintain relevant information.
‘All these vendors are tools vendors, so absolutely they are going to evangelise about the tools that support the data governance processes,’ he says. ‘But the tools are not solving the problem. They are simply enabling a data governance process that must be designed and owned by the organisations themselves.’
While some organisations will want to pursue the holy grail of “master data management” (MDM), Karel explains, others will be happy to pick and mix the data integration and data quality techniques that will deliver the quickest and most impressive returns.
For Millington the benefits of such technologies are manifold: ‘We are updating the data on the CRM all the time so, for example, the person in tech support will now know exactly what’s been said between the customer and sales team,’ he says. ‘Since we’ve been using the new script our CRM records are near perfect with duplicates and useless information kept to a minimum. Our sales conversion rates have measurably improved.’
