The importance of data migration
What is data transformation, as opposed to digital transformation, and why is it important for traditional companies to make the most of a digital-first culture in 2020 and beyond?
Data transformation is critical for businesses to stay competitive and respond to rapid market changes. Whereas digital transformation encompasses the adoption of paperless processes, and now more usually cloud-based business applications, data transformation relates to the information that is recorded and managed within these systems.
Data is one of an organisations more important assets. Companies need to manage and maintain it if they are to optimise their relationship with customers, anticipate their needs, and offer relevant products & services.
Customers today expect businesses to have almost immediate access to records of previous interactions and transactions with them. Without this, customer experience may be falling short of the competition. This necessitates holding accurate and current information about customers and their requirements.
If a company has not modernised its approach to data, then it typically resides in unconnected systems or across a set of spreadsheets. This makes it almost impossible to use the data to drive actionable insight, be agile, and can also make it difficult to comply with stringent data regulations.
What are the main pain points for business leaders trying – and failing – to foster a company-wide, data-first mindset, especially for corporates with factories?
For new data management policies and procedures to be implemented, an initial data “cleansing” may be required to get all existing data to a point where it adheres to the new rules. This can be a resource-hungry process.
When existing systems are time-consuming or onerous to use, users tend to avoid updating and maintaining records if it’s not critical to order processing/revenue generation. “Why spend 2 minutes updating the mobile phone number of a supplier when I have other things to do?”
In the absence of capable, comprehensive and easy to use systems, employees managing data will often invent and adopt their own bespoke “island” processes and systems such as bespoke Excel spreadsheets, notes in Outlook or mobile apps, or even pen and paper. Management (and the rest of the organisation) will likely have no visibility of these and the data within them.
How do the boards of larger companies and corporates need to be convinced that their business model needs to be ripped up and a data-first approach adopted? What do they need to see/hear?
Competitors are not standing still, and organisations will be left behind if they don’t embrace the customer-centric approach that a data focussed organisation can provide.
Non-adherence to data policies (GDPR) can be very costly, up to 4% of a company’s annual turnover! Source: https://www.itgovernance.co.uk/dpa-and-gdpr-penalties.
Employees may be wasting time by undertaking administrative heavy processes such as internal reporting and recording the same piece of information in multiple places. By managing data in transparent, well-structured integrated systems, internal reports can automatically available in real-time and management can have a clear, real-time summary and detailed views of all business metrics.
When teams manage information in shared and transparent systems, the customer can experience a joined-up and continuous conversation irrespective of the employee that they are communicating with. This helps avoid embarrassing dis-jointed conversations, such as the typical “I already explained this to your colleague last time…”
What three top tips / hacks would you give to business leaders trying to embrace a business-wide, data-first approach?
Communicate a clear and positive data management policy that highlights the benefits of adoption from the perspective of the employee, i.e. how much easier it would be if they switch to new ways of working.
Adopt data matching rules and processes to look for and prevent the creation of duplicate records. If the same piece of information exists in two or more systems, how do you ensure that both values match? There should be a “single version of the truth” – this may include, re-structuring the data records and fields, reducing the number of systems or integration/synchronisation of the systems.
Configure business systems to validate data on entry or update so that partial records cannot be entered. For example, addresses must contain a postcode.
Ensure there is a Data Manager who has ownership and responsibility for preserving data integrity, accuracy & compliance.
Actively look for ‘dark data’ in your systems. What data exists but is inactive and probably stale? Is a contact record of any use if there’s not been any communication with that person in the last 3 years? Can this be archived/deleted?
When undergoing this pivot, how important are communication, vision, and transparency? What tips do you have to ease the bump?
Communication is the key. Everyone needs to understand the reasons for and benefits of the changes from the perspective of their roles. Only when a data user recognises that it’s in their interest to maintain the accuracy and integrity of data will they be inclined to do so every time. This can be illustrated by describing the implications of acting on partial, incorrect or outdated records, including wasted calls, embarrassing conversations, internet research time, time spent collating internal reports.
Create and share tailored views, charts and dashboards to give everyone clear real-time views of the information that is important to them based on their role, team, geography, product/service, client base, etc. These can extremely beneficial in helping prioritisation of next actions and strategies.
And how important is education around data, what it can do, and how can that be communicated better (for the c-suite and those on the factory floor – what media works best)?
Hands-on training is the most effective – don’t just share resources or links to videos. People learn most effectively when they are actively adopting the preferred processes.
Unlearning the old ways of doing things can be harder than learning new processes. Take steps to ensure people can’t slip back into old habits.
