{"id":5365,"date":"2021-03-26T16:16:39","date_gmt":"2021-03-26T16:16:39","guid":{"rendered":"https:\/\/www.theoaklandgroup.co.uk\/?p=5365"},"modified":"2021-03-26T16:16:39","modified_gmt":"2021-03-26T16:16:39","slug":"project-analytics-getting-to-know-your-data","status":"publish","type":"post","link":"https:\/\/weareoakland.com\/blog\/project-analytics-getting-to-know-your-data\/","title":{"rendered":"Project Analytics: Getting to know your data."},"content":{"rendered":"

Welcome to part 2 of our 5<\/span><\/i>\u00a0part<\/span><\/i>\u00a0series exploring the evolution of Project Analytics and how it’s transforming the performance and outcome of major projects initiatives.<\/span><\/i>\u00a0<\/span><\/p>\n

\u00a0<\/span>In this article, we explore some use cases and best practices for getting started with project analytics.<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span>Closing the Project Analytics ‘Imagination Gap’<\/span>\u00a0<\/span><\/p>\n

\u00a0<\/span>“We need a critical mass of people who have the desire and the skills to make change happen at a personal and project level. Only with that critical mass can we change the sector.”\u00a0<\/span><\/i>\u00a0<\/span><\/p>\n

Gareth Parkes, Head of Data & Analytics at Sir Robert McAlpine,\u00a0<\/span><\/b>DataIQ<\/span><\/b>\u00a0interview<\/span><\/b><\/span><\/a>\u00a0<\/span><\/p>\n

In the early days of your project analytics initiative, one of your primary goals will be to bring together the data and process communities.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

On one side, you have those with an in-depth knowledge of the business process and can imagine the art of the possible with improved project analytics, and on the other side, you have the data team.<\/span>\u00a0<\/span><\/p>\n

To succeed, you need to bridge this gap and create a unified team.<\/span>\u00a0<\/span><\/p>\n

Moving data out of the backroom\u00a0<\/strong><\/h2>\n

Within major projects, the data function can often\u00a0<\/span>be seen as<\/span>\u00a0a backroom function and hence somewhat undervalued by the organisation.\u00a0<\/span>\u00a0<\/span><\/p>\n

Where\u00a0<\/span>we’ve<\/span>\u00a0observed project analytics success, the cultural mindset around data has shifted.\u00a0<\/span>\u00a0<\/span><\/p>\n

Project leadership<\/span>, in particular, have<\/span>\u00a0recognised the incredible value that the right mix of data skills and technology can deliver for better decision-making and operational outcomes.<\/span>\u00a0<\/span><\/p>\n

Creating a coalition of process and data expertise\u00a0<\/strong><\/h2>\n

To close the project analytics \u2018imagination gap\u2019,\u00a0<\/span>you’ll<\/span>\u00a0need to align those with the vision for project analytics (those who typically understand project processes intimately) and the internal data experts who understand project data and systems at a granular level.<\/span>\u00a0<\/span><\/p>\n

Whilst\u00a0<\/span>it’s<\/span>\u00a0admirable to have a grand vision of ‘shooting for the moon’ with Artificial Intelligence and Machine Learning, we recommend getting started by building a cohesive team of process and data experts to focus on some impactful (and achievable) short term use cases.<\/span>\u00a0<\/span><\/p>\n

What data skills will you need?\u00a0<\/strong><\/h2>\n

You clearly need to bring in some extra data professionals onto your project analytics initiative, but what roles are required?<\/span>\u00a0<\/span><\/p>\n

Data Analysts:\u00a0<\/span><\/b>\u00a0<\/span><\/p>\n

These are the ‘workhorses’ of any data-intensive program. You will need to ensure that your data analysts have the requisite skills because the data analyst role can vary across industries.\u00a0<\/span>\u00a0<\/span><\/p>\n

The Gov.UK website provides a good overview of a\u00a0<\/span>Data Analyst Job Description<\/span><\/span><\/a>:<\/span>\u00a0<\/span><\/p>\n