Personal Analytics in Projects

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Our Guest is Dr. Trevor Clohessy, a Digital Transformation Lecturer and Researcher at the National University of Ireland in Galway and we discuss Personal Analytics in Projects.

Trevor’s research on cloud-based digital transformation has been published in a number of academic and practitioner fora. In this Interview, Trevor shares some fascinating insights and case studies from his research and recently published paper entitled “Enterprise Personal Analytics: Embracing the Potential, Avoiding the Pitfalls”. We also talk about IBM’s Personal Social Dashboard.

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Transcript from Episode 76: “Personal Analytics in Projects” with Dr. Trevor Clohessy

Can you share with us an overview of your background?
I’m currently working as a lecturer and an IT analyst in the digital transformations, in the National University of Ireland here in Galway, here in the business school. Previous to this, I was working as a lecturer and I completed my Ph.D. in 2015. My Ph.D. looked into the impact of cloud computing in organizations and specifically, the IT service providers.

So, there was that element of digital transformation that was going on that aligned nicely with my current position. Previously to that, I worked as an engineer and I have always worked with IT systems either I developed them myself in the box art matter manner, or I’ve worked with them off the shelf product. And it’s always been towards the aim of improving productivity whatever company I was within.

So, this paper then on enterprise personal analytics, there’s the statement in it and I am just going to read it out, a short and to-the-point statement but it states that “We believe that the emerging concept of Enterprise personal analytics has the potential to become the New Frontier of competitive differentiation”. A fairly strong statement, it’s fair to say.
We believe that is likely to carry out, and for your listeners who are familiar with the technology trend graph that comes out of here a year which identifies emerging technologies. Out of July in 2017, we’ve identified personal analytics, particularly within the workplace as, it’s currently at the peak of inflated expectations. So, even IT analyst companies have identified that this potentially has the power to be the next New Frontier of competitive differentiation.

But if you take a step back in your organization as long used analytics to improve performance and the research is there to show the top performing organizations used business analytics five times more than lower performance do. And it’s an industry where companies are spending more, more on their analytical disease. One kind of area which one we looked at which is kind of coming to the floor is this concept of Enterprise personal analytics.

Can you give us your definition of Enterprise personal analytics?
Just before I get into my own definition, we will have to look at the convergence of trends that lead us to be seeing, “you know, this could be a future trend within an enterprise”. And we’ve seen the miniaturisation of computational power, that is lead to various trends in learning analytics, sports analytics, human-centric analytics.

If you look at French philosopher Michael Foucault, he was saying that you know he was a big fan of being self-aware and self, and using knowledge for self-formation. And in 2012 it was this famous blog that came out by Stephen Wolfram and he says we’re moving into a new era of the quantified self or the area of self-awareness. For your listeners, if you just type in “the personality types of My Life by Stephen Wolfram” you can see how he carried out an experiment and he predicted that one day everyone will routinely collect all sorts of data about themselves, not only in the person’s sphere but within the enterprise scenario.

And my idea or concept encapsulation of personal analytics you have to look at the concept of personal data. Personal data can relate to a variety of concepts which look at biometrics personal finance, social media activities, health status, behaviours, emotion states, mobility, personal interests, and so on. The idea of personal analytics is getting this broader picture of a variety of these concepts for use within an organization.

When it comes to recording ourselves within an organization and the whole “Big Brother”, does that play a part at all or am I barking up the wrong tree?
When we go back to Orwellian and 1984 and you know Big Brother, of course, there is a disturbing aspect to this in terms of surveillance, too much data, and giving data to analytical amateurs who don’t know what to do with the data. But what we advocate in the paper is that we’ve developed a roadmap and digital transformation Enterprise person analytics roadmap which companies can use to direct how to implement or adapt personal analytics within an organization.

I suppose with a lot of these trends you have to look to the case studies in the business, use cases that are going on at the moment. If you look at the United States and companies like Intello, they mind social data and apply intelligence to figure out if employees are going to change a job. There are other companies like IBM and Bank of America, BP Time Warner, who have developed sophisticated wellness division programs. And the idea behind this is healthier employees or happy employees make better decisions and increase productivity.

And there also is a positive aspect from the organization as it reduces healthcare claims. I’m going back to study in IBM and in 2014 they issued 40000 fit bits over 2 years, there was a 96% uptake of the program, that was 92% of employees regularly logged their health data. After the program was finished, 63% stay down with the program and what we looking at here is you know companies are making moves to the enterprise with baby steps. But if we look at other advancements in the technology is like, there’s an Australian company who developed a new floor light which detects when an employee is in the zone, so it goes green when you can approach an employee, and red is when you can’t approach them and it depending on keystrokes and interaction with them, their computational and the set-up.

And there are other companies that are using an app called stressing which detects the level of stress within your vocal cords, to identify when employees are the nearly as stressful scenario and their decision-making might be impaired. But I think when you take a back into a personalized the way we use personal analytics as a driver, and as a motivator, the scenarios and if its replication in a company can be quite attractive.

What concerns do organizations have and what advice would you give them to address those concerns?
I am going to give another example. There is a company called Procter and Gamble and a company can conjuncts to pause whether they like what they hear about Procter and Gamble using personal analytics. They’re using part sophisticated techniques in order to focus on the human dimension in order to enhance both individual and team performances. And examples of this they’re evaluating across different enterprise team compositions, to evaluate their employees, in the column + or – players, similar to a sporting analogy.

They have co-developed this business fear rooms reviewing and acting on individual and team data analysis, even better analysis in close proximity to all project managers. A bit like in the placing an analysis on the bench in the sporting scenario. And most significantly employees keep track of their own performance metrics in order to improve on them. The example of this is their marketing team has the access to sales data, members of individual project team members have also access this is this compare who are in the top team performance within the organization.

So when a company looks at what P&G are doing for great success, they have to ask themselves the question, as a certain element of personal analytics, we could also adopt within the organization. I’m a big believer of taking baby steps towards this as in, there’s famous innovation quadrant that shown the most successful adoptions of technological trends had been low complexity and no novelty when first introduced. And you often hear of companies adopting the latest technological trend As high complexity and high novelty which means when a high novelty, because that the employees not aware of what it is and the complexity means the company may not necessarily have the infrastructure in place to roll out this effectively.

In terms of the baby steps then, and you know, there’s a lot of organizations there like Procter and Gamble and IBM and they’re probably you know trailblazers and leading the charge in all things new and innovative and if it doesn’t work, it doesn’t work, if it does, great. And they have the budgets and resources to try them out but for a small organization, you know, maybe 10 people maybe 100 people and maybe even 1000 people, where can they start if they’re not doing any EPA at the moment?

Well, I suppose if you are a smaller company, that what I mentioned previously. You know, what you can get on board with the enterprise personal analytics training. If you’ll bring an adoption of the specific innovation within the company that’s low on novelty, low on complexity. Like every company has started out like Uber, and so on, they started out as an SME, small company and they scaled. But it all boils down to the single question “Where does, what problem can EPA solve within my company?”. There’s no point in adopting this for the sake of adopting.

Is there any sort of example or analytic or metric that will be the next thing you should consider?
For example, IBM has a fantastic dashboard program call IBM social dashboard which kind of measures your eminence and each employee’s given a personal profile picture but they’re also given an overall score. That score it’s made up of four dimensions, number one is the activity, so get the score of your activity that goes up and down depending on how active you are.

It gives you a score in your reaction, so in context of likes, reads, shares and so on, across the social media. It gives the score an eminence to reflect the number of people trying to interact with you and your content, following you, sharing, but also gives you a score finally on the network and indicates how many colleagues you have. An individual can drill down into each KPI and get a clear understanding of which their actions are driving their scores and just their social activity. But that’s from a social perspective, but it is your readers just look that up, it’s called IBM  at all social dashboard measure your eminence, it’s a fantastic looking analytic personal analytics feature, although on the social context, but it can give you an overall score which can be broken down into it and send them four core dimensions.

And this is kind of a picture of what could be if you were to put it into a project management context. And we believe that if the organizations behave appropriately, build a culture of trust amongst the workers and most importantly get them acclimatised to capturing and analyzing the personal data within the enterprise setting. You going to see those employees in developing their self-monitoring skills, you will see in increased productivity, better decision-making, they will be able to communicate more effectively with co-workers.

At the end of the day, using analytics within a project team has always been to manage projects improve part of processes, you know predict project schedule delays and overruns. Where the first trial of this project may be to build up the stream of data, after successful projects you will have a pool of data on both individual and team performances from an enterprise personal analytics which would serve the company very well in the long run.

But at the end of the day, managers will also have to become acclimatized to handing over that kind of power to their own employees, so that they’ll be able to manage their employees without discouraging them also from using an enterprise personal analytics. At the end of the day, you’ve got to approach this as a long-term strategic plan within your company whether you’re small or a large company, those companies are implementing this well like P&G and Bank of America they’ve set up webinars, they set up training, they have initiated a culture that we as a company it’s, it’s driven button down and top up. If you force this course to the employees and it’s not going to work.

And the infrastructure today, something like Amazon S3 or Cloud services that are relatively cheap.
All of these services are now cloud-based and companies are using, a lot of companies are using human resource types analytics to reward employees, annual bonuses, the employee of the Month. They’re seeing this data, however, the employee’s been given you know the black and white picture when they come into the office-you’re not doing this right, you’re not doing that right. Well, imagine an employee scenario you know the IMAX 4D pictures scenario when they actually know that they’re not doing well and they need to improve.

When you’re looking for companies who may be interested in deploying some EPA strategies within their project teams, what’s involved there, what’s the next step, should somebody listening to this podcast, say “Trevor, we want to do this, we’ve been thinking about doing this” what can they do with you?

At the moment, as I said before, you know this concept of EPA is on the peak of expectations on that Gardiner technology hype cycle. And in a lot of the times, and the companies that I mentioned there are the American type companies. We are looking for organizations that have implemented an EPA strategy or are considering it and would like further help. As I said before we have conducted an in-depth analysis of this, we’ve developed and if you referred to the paper that we have, there is a detailed framework there and a roadmap to show how companies can get on board enterprise analytics digital transformation at the moment. And if you need, if you would like further information you can contact me at the LinkedIn and I will be in touch.

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