Data, data everywhere but not a drop of insight? What can PMO do?

Data, data everywhere but not a drop of insight? What can PMO do?

We live in digital times. Every second of everyday data about us is being generated, analysed and used to provide insight. The sites we browse online, health and activity data from smart watches, location information from our phones it’s all feeding analysis and insight. Your change programme is swimming in a sea of data too. Your teams are constantly creating digital information, be it status information, chat data, change logs, or reports, but is your PMO giving you data driven insights to drive your change programme forwards?

Traditionally Change Management has relied on the experience, judgement and often the intuition of PMs, using individuals’ understanding of the situation, and the often-limited available information to identify problems, make decisions and take action.  But times are changing. We increasingly rely on technology to deliver change programmes, while change teams are under increasing demand to make the right calls quickly, identify and resolve issues earlier and deliver more efficiently than ever before.

Will Artificial Intelligence (AI) give you insights and drive your change programme?

AI is an exciting prospect which may be able to replicate some of the human judgement and evaluation of information to help us to deliver change effectively. But AI comes with its own challenges; superficial answers which at first glance look great but on greater inspection can be sorely lacking, not to mention the risk of biases and hallucinations. Some of these challenges will undoubtably be solved over time by improvements in the technology and through greater use, but today the difficulties remain for change programmes to gain value from AI.

One of the greatest challenges with using AI to support your change programme is the unique situation of your organisation. Understanding the specific context of any question being asked is needed to get a true insight. Unless the AI model is specifically trained for your situation, you’re likely to get generic responses which don’t take into account your specific needs and challenges. To train an AI model to the specifics of your organisation it will need data. Lots and lots of trusted data, and even then, the model won’t truly understand what it’s assessing and the outputs it’s creating, but there is another way.

PMO offer a better way

Your PMO, with the right expertise and skills can deliver insights sooner than AI will be able to. With real world experience, situational awareness and context the PMO can bring data and judgement together giving your transformation team real, specific value. Using the growing volumes of data being created by change programmes and Big Data techniques PMOs offer a viable alternative to either relying on traditional experience and intuition or waiting for AI to be good enough to be trusted in your organisation’s particular situation. Big Data enabled PMOs can give change the trusted data-driven insights that help change leaders to make better, faster and more reliable decisions, optimise their controls and transform assurance and quality management quickly.

What is Big Data?

Big Data represents a change in thinking where information is no longer created and used for a single purpose within a transformation project but is used throughout the lifecycle and across the portfolio. Using ‘Big Data’ techniques, linking data and performing analytics over large amounts of structured and unstructured data generated during delivery, PMO teams can uncover hidden patterns, correlations, and relationships which were previously inaccessible to help guide the change programme.

Big Data is often described in terms of three characteristics:

• Volume using the significant amount of data available, supported by the right tools and infrastructure complex analysis can be performed quickly and accurately.
• Velocity the data being analysed is constantly changing and updating. The use of sensors and other digital data sources help inform Big Data analysis in real time or near real time without putting increased burden on delivery teams.
• Variety the data will be diverse, coming from a range of sources and types of information. The data will be linked and combined to allow new understanding to be found.

As many applications of Big Data rely on detecting patterns in disparate data sources the collection of data, the quality of it and its integration are critically important. Ensuring the quality and accuracy of data is crucial for obtaining meaningful insights so when implementing Big Data for your programme, remember to ensure robust data capture, validation, cleansing, and pre-processing techniques are used.

How can PMO and Big Data help?

With the growth of digital collaboration and communication platforms, internet enabled sensing and other data collection tools, a significant amount of change data is generated and can be collected. By making this data available and analysing this strategic asset the PMO can bring greater value to the transformation programme. Often knowledge such as logs, lessons learned, best practices, troubleshooting and firefighting information on issues as they happen is lost into personally held data or central archives. Programmes suffer more than a static organisation from losing data to archiving as the dynamic nature of change teams means people move on to new programmes and archival information remain buried in data stores. With the PMO using Big Data analytics they can process this vital information to growth and strengthen the change capabilities.

Decision making is a crucial aspect of delivering any change. The quality of decisions made throughout the change lifecycle can significantly affect success of the transformation.

Traditional decision-making methods use the limited, often patchily available data, opinions, and subjective judgments. The timeliness and confidence in these decisions is often reduced by data being inaccurate, out of date or incomplete resulting in poor decisions being taken or decisions being delayed while teams scramble to compile information. AI driven decision making relies on complex models, the imitation of understanding and sourcing potential responses from mountains of untrusted (and often unknown) training data.

With PMOs delivering real or near real-time insights and enhancing stakeholder understanding with PMO knowledge and experience, the change team can make better, clear decisions more quickly and with greater confidence to enhance delivery performance.

• Big Data analytics can improve stakeholder engagement by providing transparent, real-time information on progress and performance. This allows stakeholders to stay informed, collaborate more effectively, and contribute to project success. Data alone is not always compelling. The insights and context PMO can bring, coupled with effective data visualisation tools increasingly facilitate collaboration and communication among project stakeholders. Interactive dashboards and visualisations enable projects to communicate complex data effectively and efficiently, promoting better decision making and stakeholder engagement. Data visualisation tools can also aid in monitoring project performance and identifying potential areas for improvement.

• Because the rate at which data is coming into a Big Data enabled PMO it makes real-time analytics an incredibly powerful tool for change managers to monitor and control progress continuously and adjust as needed. By analysing data in real-time, PMO can support change managers by quickly identifying emerging risks, manage issues, detect plan variation and adopting a more agile and responsive approach to management. For change managers, whose job it is to ensure that often competing factors work together in symphony, data insights using integrated real-time dashboards and reporting tools allow stakeholders to be continuously updated with key performance indicators (KPIs), improving transparency and trust when it’s needed by the stakeholder.

• PMO leading on real-time analytics can enhance risk management by dynamically identifying and assessing potential risks present in large, complex datasets. During traditional risk and issue management, risks are often identified intermittently based on current delivery challenges. A PMO with the ability to detect the patterns of risks through predictive analytics, spot risk indicators for your business early and effectively evaluate emerging risks can enable change managers to implement appropriate mitigation strategies earlier, reducing the impact of risks on change performance.

• Like other aspects of project control a large amount of data is collected on the use of resources, types of resources, units of measure, the amount required, the amount used etc. Big Data analytics can facilitate better resource allocation and cost management during change. With the PMO providing insights into resource usage and understanding how the patterns or resource usage impacts on delivery finances, they can suggest corrective actions to improve efficiency. Effective analysis of financial data can help reduce cost overruns by finding and filtering unnecessary expenses. By analysing past project data, managers can predict cost overruns and implement strategies to mitigate them.

• PMOs using big data can evaluate previously untapped data to gain deeper insights about the maturity of the change. This information, coupled with their expertise, and assurance expert-opinion can help change programmes develop a much more accurate view of the maturity of delivery and give much greater assurance to stakeholders that the change is continually meeting both established governance standards and the business’s needs. Using live data, dashboards to monitor quality, assurance can be continuous, with deviation from best practices, improvements and performance continually managed.

The sheer volume of data needed for Big Data analysis to be effective can pose challenges in terms of data storage and processing capabilities. Investing in scalable storage solutions and efficient data processing technologies is often needed to manage the large datasets effectively. Choosing the right analytical tools and techniques for Big Data analysis can be challenging, given the rapidly evolving landscape of Big Data technologies.

Despite the challenge felt by most organisations to “get the data right” the quality of data is often not cited by leadership teams as the key difficulty in gaining a competitive advantage from Big Data. Improving and automatically gathering relevant delivery data will allow you to both get more value now from your PMO using big data techniques and help prepare your organisation for training and using AI models in the future. With a large, trusted dataset, you will be able to more effectively train any AI models which may be adopted in the future. Treating data as a strategic and enduring asset, will support understanding, insight and trust in the outcomes of analysis.

The top challenges include the lack of understanding of how to use analytics to improve the business and lack of management bandwidth. Ensuring your PMO and leadership team have the right skills will allow you to use Big Data to deliver insights sooner than AI.

With real world experience, situational awareness, quality data and analytics your PMO can give new value to your change portfolio.

There might be data, data everywhere but there’s a lot of insight PMO can bring.

Unlock the full potential of your business with our expert insights. Contact us today to discover how we can help you achieve your goals theteam@projectone.com