Accountability is critical in business. Professional services companies are held to high standards, and client expectations need to be met. But are the goals being measured for each project telling the true tale of success?
Companies are well-accustomed to setting statistical KPIs on which to judge project delivery. From budget to actual cost, earned value to ROI, they each provide a clear benchmark. However, projects are powered by people – and the impact of team chemistry on project performance is rarely measured.
For all professional services firms, there will come a point at which transactional data can’t answer everything, and they need to understand how team composition influences outcomes. Lucky for them, new technology is emerging which can shed light on the sentiment story, for enhanced insights on how to provide outstanding result.
Performance is personal
On the surface, the professional services industry is doing well. Only 14% of projects are deemed a failure, according to the Project Management Institute, and the amount of money wasted by poor project performance has declined by 27% since 2013. However, these statistics are only telling part of the story.
In a recent PwC study, the overwhelming majority (94%) of respondents understandably said engaged stakeholders (from team members, to managers, to customers) were critical to delivering a successful project. Yet very few organisations measure this, let alone understand its impact on performance.
This is set to change. Many companies are already using project management technology to track traditional metrics such as budget, profit margin, cost efficiency and customer satisfaction. Now, advances in Artificial Intelligence and Machine Learning will enable this software to start making sense of unstructured data – enabling sentiment analysis to enter the mix.
To appreciate the benefits of sentiment analysis, it is important to understand its meaning in a professional services context.
Essentially, sentiment is the tone of communication between everyone involved in a business project – is their language favourable or not? Project managers can get an idea of this now by asking team members their opinion, but the process is lengthy, and people may sugar-coat the truth.
Emerging AI technologies provide an alternative solution, analysing all the communications associated with a project to judge how well colleagues are working together, based on the words they are using.
Not only is this much quicker than getting individual feedback, it’s unbiased – meaning project managers can check-in at any time to see how things are really progressing.
Stopping people becoming a problem
The ability to analyse how well teams work together is invaluable. According to McKinsey, 97% of employees believe that the outcome of a project is influenced by team alignment, and intelligent learning tools can potentially detect a misalignment sooner than a project manager.
Not only does automatic data analysis get to the root of a problem quicker; sentiment data gives a broader breadth of explanation should the wheels start to come off, and interim deadlines are missed.
Sometimes performance problems are solved by a simple change, such as recalibrating the budget to prevent overspending. But often the answer isn’t that simple. Analysing sentiment data helps to determine whether it is a people, product or process issue that is hindering a campaign’s chance of success.
If it’s a people problem, and the issue lies in team morale, steps can be taken to improve unity and collaboration. If it reveals a particular team member is the source of the problem, individual support can be offered to enhance their performance – or they can be replaced by someone else that has a better chemistry with the rest of the group.
The equation for collaboration
On the subject of chemistry, sentiment analysis could help professional services companies to plan projects better from the outset.
The more individual performance data that AI tools track, the better understanding businesses will have of who their top performers are, where their strongest skills lie, and who they work well with.
Advanced project management technology will be able to utilise this data when setting up a new project, to automatically recommend which people the project team should comprise of, based on their previous success.
With this level of sophistication, senior managers will be able to tailor each project team to stand the highest probably chance of delivering a successful outcome. And they can continue to monitor that team throughout the project, using sentiment analysis to ensure their chemistry is developing as predicted.
AI: the what, how and who of professional services success
Although AI is a huge buzz topic in business, it’s still very much in its infancy, so we are only just starting to see how it can transform processes and performance. As its potential emerges in professional services, open minded organisations will benefit first.
Companies must be willing to invest in new technologies, which use AI and Machine Learning to leverage unstructured data. But more than that, they must put the internal framework in place to gather that data; channelling all communications centrally through their chosen project management platform, making it easy to extract and analyse.
If conversations are spread across email, project management dashboards and instant messenger chats, it is very difficult to get a clear and accurate picture of overall performance.
By making these small cultural changes, professional services businesses will be able to combine statistical and sentimental data, to truly analyse what makes some projects successful – while others fail. This will provide valuable insights into what – and more importantly, who – makes their campaigns work, so that not only can the best person be found for each job, but the best team.