Transformation Projects: Using the right tool to save time and money

 

by Simon Riley

“We didn’t understand the complexity of the data, or how & where it was being used throughout our organisation.”
“We spent time and effort data-mapping as part of our transformation, but we incurred delay and cost to our project because of unexpected data complexity.”

If those statements sound familiar, you may have been involved in digital transformation programmes in the past. In this article I will discuss some of the pain points around data governance I’ve experienced in previous roles, and how having the right tools at my disposal could have saved the organisation time and money.

 

It starts with the master data

When you carry out a transformation project, whether to your HR, finance or CRM systems, you will no doubt spend time in the analysis and design stages looking at your master data and investigating how this data is used from both an upstream and downstream perspective. You’ll arrange various workshops with multiple stakeholders and invest considerable time & effort during the analysis phase identifying the data that’s to be transformed, what it is used for and what downstream connections this impacts.

You start by identifying the master data and how it is used within the in-scope environment for transformation, then you look to identify where this data is consumed and for what purpose. But how do you know exactly what data is being passed? Is the data transformed and held into further documents or databases and then passed on to another system?

The likelihood is that you won’t find all the answers without spending an unrealistic amount of time and money carrying out a full data audit prior to your transformation programme – and if you do, the output will be invaluable to your transformation programme but will quickly become obsolete without continued resource-intensive effort.

 

When two become one…

Previously, I was involved in an HR transformation programme following the merger of two large companies. This involved circa 38,000 employees, roughly split 50/50 between two separate HR, payroll, performance benefits and time off systems, and a further 7,000 employees dispersed globally within various HR databases. It became apparent that it would be a huge challenge to quickly align HR, Benefits, Talent Acquisition and Reward operations and process the amount of data involved whilst at the same time preparing to migrate to a cloud-based SaaS solution.

With no tools at our disposal to catalogue, collate or classify data, a dedicated team consisting of business and data analysis experts was required to support the various functions within HR and finance. These experts ensured that the relevant operations teams were able to identify the correct data elements to assist with processes such as pay and bonus reviews as well as transformation activities such as alignment of job grades and pay scales.

This hugely challenging process was ultimately a successful (and enormous) technology project – but more importantly the ongoing operation and transformation of the company’s HR, payroll, and recruitment processes were dependent on it.

The overall programme’s success is in no doubt partly due to the herculean efforts of the data project team members. Running the data project came with considerable costs – namely external consultants who specialise in data and business analysis – but even they were “hamstrung” by the pure complexity of the data that no one person could fully understand. The data structure across both parts of the business was in a constant state of flux, as each of the four new cloud-based projects went live and operational alignment activities continued.

 

Catalogue, Correlate, Classify

A deeper level of data intelligence would clearly have resulted in a faster and lower-cost project delivery with less risk. In hindsight, I can see that the project would have benefited from:

  • The ability to catalogue where HR and associated financial data was held across the organisation would have provided the data element of the programme a static and well understood baseline to plan from, lowering the impact of complexity and associated delay costs incurred later on.
  • The ability to understand the data correlation from the outset would have allowed for a more effective data-driven conversation with the business to gain insight into the data usage, purpose, and relevance. This would have given greater understanding into the impacts of changes to the master data at source and resulted in more effective planning.
  • Classification of data elements would have given insight into the data and documents held within the HR systems to be transformed and would have enabled the programme to effectively address regulatory and compliance commitments such as GDPR and country specific requirements, such as Works Councils.
  • The ability to build business flows based on the actual data sources and applications. This would have assisted the Corporate finance function in their effort to complete the annual financial planning initiative with disparate data.
  • Data Quality assurance with active monitoring. This would have ensured that the correct versions of data are used and were not duplicates identified and remediated against.

 

What if you could find, map, catalogue, correlate and classify across all types of data, in any language,
across structured, unstructured, big data, cloud and apps – all with one tool?

 

Big ID is a tool which leverages Artificial Intelligence (AI) and Machine Learning (ML) to integrate with solutions across your organisation and provide complete visibility of data across your entire enterprise landscape. The solution presents the user with a data inventory so you can see its different attributes and where it resides – allowing you to determine its value and secure it where necessary.

Had we had access to the level of data intelligence that BigID brings prior to this HR Transformation programme starting, it’s likely that neither a team of expensive external consultants nor a dedicated senior project manager would’ve been required, resulting in a much smaller resource and cost profile.

The example I have given is for a single HR Transformation programme. I am in little doubt that the advantage of having BigID in place would have brought even more benefits to transformation programmes in Finance, Customer databases, facilities management and others.

Big ID also helps your company maintain data privacy, data protection, assist with rapid breach response, opt in/opt out governance, Data Rights automation and much more.

Contact the experts at Winterhawk to find out more about BigID, and how the solution can enable your digital, HR and finance transformation projects and support data protection in parallel.

 

Simon Riley is Winterhawk’s global Programme Management Director with over 20 years of experience delivering both business and IT change. He has managed enterprise-level SAP and Oracle implementations as well as large-scale cloud and transformation programmes across retail, telecom, energy, financial Services, and life sciences industries.