Is It Time To Move On From The Annual Performance Review?

By AgileBusiness, Culture, Leadership, Teams No Comments

Yes. A succession of large businesses (including Accenture, Deloitte, Microsoft and Adobe) have now moved away from the annual review as a standard mechanic for performance management. When GE announced a while back that they too were experimenting with replacing the annual formal review with more frequent conversations, they talked about how the increased pace of change meant that goals set annually quickly became out of date, and feedback on things that happened a year ago made no sense.

Speaking about why her company made their transition, Adobe HR head Donna Morris said:

“It’s a process that looks in the rear view mirror, that’s focused on what you’ve done a year ago. That just isn’t current with how I think we’re working and how many of the employees that we’re looking to attract or grow have been raised.”

When Accenture announced their move, their CEO talked about how an annual assessment made little sense in the modern business environment, how performance was about what happened every day meaning that it was now more about instant management feedback, and how they were not convinced that the legacy review process was actually driving better performance. The idea of ranking staff along a distribution curve was, he said, increasingly irrelevant.

Many of these companies noted the drain on management time and resources that the review process represented and whilst acknowledging the time intensive nature of feedback and performance management, the opportunity in shifting to a more frequent and incremental evaluation process is seen to be in achieving a greater return on that investment of time.

There are some not insignificant question marks around how fit-for-purpose traditional performance review systems are in achieving key aims. A public survey conducted by Deloitte found that 58% of the executives that they questioned believed that the current review process did not support either high performance or employee engagement.

Work by Dr David Rock which combines principles from neuroscience with the practice of leadership has set out some key ways in which reviews (even positive ones) can negatively impact motivation and engagement. His neuroscience-based framework incorporates five key factors (the SCARF model: Status, Certainty, Autonomy, Relatedness and Fairness) that can have a disproportionately high affect on human reactions, and which performance rankings can often negatively impact. This can leave staff feeling under-recognised, under-appreciated, disengaged, less open to setting stretching goals.

A well known study (PDF) into performance ratings by Michael Mount, Steven Scullen, and Maynard Goff (Journal of Psychology, 2000) based on a sample of almost 4,500 managers who were rated by bosses, peers and subordinates, found that ‘idiosyncratic rater effects’ (or the individual quirks or peculiarities of rater’s perceptions) accounted for 62% of the rating variance, whereas actual performance accounted for only 21% of the variance. Ratings, they concluded, ‘reveal more about the the rater than they do the ratee’.

Deloitte went as far as counting the time spent on performance management and found that each year it consumed almost two million hours of management time, much of it taken up with leaders discussing the outputs of the process rather than talking to the employees themselves. The whole thing over-emphasised the past at the expense of looking to the future.

And yet rating systems are not entirely bad. Research by management insight and technology business CEB has found that numeric or qualitative performance rating systems can still be useful in driving performance, helping with staff and management decision-making accountability, the tangible linking of performance to reward, employee engagement and the perceived quality of manager feedback (particularly with high performing staff). But there are however, some tangible ways they found to improve performance management:

  • An increased frequency of informal review – more timely, regular, ongoing feedback allows for earlier adaptation and better adjustment of expectations
  • Forwards, not backwards looking review – discussing future requirements better aligns individual strengths with business needs
  • Peer, as well as manager, review – particularly useful given the greater contemporary need for cross-functional collaboration

Deloitte’s experience is instructive. A study that they conducted comparing 60 high-performing teams with a control group showed that a few key factors that related to coworker commitment to quality work, the presence of an inspiring company mission, and the opportunity to use individual strengths on a daily basis, most highly correlated to high performance.

Their efforts to improve their review process focused on tackling the idiosyncratic rater effect whilst reducing process complexity. Instead of asking team leaders to rate the skills of team members (which leads to idiosyncratic rating), they ask them about their own future actions related to that person (which has far greater consistency). At the end of projects (or quarterly if that’s not frequent enough), team leaders are asked to respond to four future-focused statements about each team member, each of which have been tested and tweaked over time to more reliably measure performance. The four questions are (quoting from this article by Ashley Goodall, Deloitte’s Director of Leader Development):

1. Given what I know of this person’s performance, and if it were my money, I would award this person the highest possible compensation increase and bonus (answers based on a five point scale from ‘strongly agree’ to ‘strongly disagree’ measures performance and unique value)

2. Given what I know of this person’s performance, I would always want him or her on my team (answers based on the same five point scale, measures the ability to work well with others)

3. This person is at risk for low performance (simple yes or no, identifies problems)

4. This person is ready for promotion today (simple yes or no again, measures potential)

This focus on both seeing and recognising performance clearly was combined with techniques to fuel performance, most notably through more regular and informal check-ins that can frequently set expectations, give feedback and support and review priorities (‘For us, these check-ins are not in addition to the work of a team leader; they are the work of a team leader’). Regular, brief conversations that can bring clarity of direction, avoid misalignment and enable each team member to do their best possible work. All attributes that align with the expectations, purpose and strengths that characterise their highest performing teams. Deloitte have identified a measurable correlation between the frequency of these conversations and employee engagement, and so combine weekly check-ins with quarterly performance snapshots and annual compensation discussions.

In the book, we discuss the rhythms that organisations and teams work to, and how tempo can be a key driver for change. An essential part of this is the frequency and type of performance feedback and review. Agile, iterative working creates a natural rhythm and appropriate environment for more frequent, informal feedback that can support continuous performance improvement. More than ever, businesses are confronted with rapidly changing contexts: competitive, consumer and company. Performance management needs to change.

Structured but nimble, timely, and more regular feedback.

Individual.

Focused on the future, not the past.

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The Real Disruption Lessons From Kodak

By AgileBusiness, Digital Disruption, Disruptive Innovation No Comments

Kodak is one of those totem exemplars of digital disruption, often characterised as a business whose leaders ignored or failed to recognise the impending developments in (and implications of) digital technology. Yet the reality is far more nuanced and enlightening, as this account from Willy Shih, a former Kodak staffer, spells out.

Famously, it was Steven Sasson, an engineer who worked for Kodak, who invented digital photography and made the first digital camera in 1975. Management were, it seems, initially sceptical about the early prototype. But when the technology began to develop further and gain scale, Kodak management were ‘acutely aware of the approaching storm’, and continuously tracked the rate at which digital was replacing film. The disruption however, brought challenges on multiple fronts which, rather than catalysing change, contributed to inertia. Most notably:

  • Making film was an enormously complex manufacturing process meaning that barriers to entry were high, competition limited.
  • Digital imaging on the other hand, based on general-purpose semiconductor technology which had its own scale and learning curves but also broad applicability, had far fewer barriers to entry
  • The technology was well outside Kodak’s core capability, making it difficult to compete and to offer something distinctive
  • The modularity of digital cameras (any engineer could put one together with component parts) meant that you no longer needed highly specialised skills and experience (modularisation commoditises)
  • A large incumbent business like Kodak had invested over time in manufacturing and distribution efficiencies and benefitted from economies of scale – when sales and production decline, those benefits matter less, and many of the gains that you could once capitalise on work against you as volumes decline
  • The problem of declining scale and securing sufficient shelf space through its retail distribution network was exacerbated since in Kodak’s case, the cause wasn’t new competitors – the entire category was disappearing
  • Management didn’t talk about the issues publicly for fear of making it a self-fulfilling prophecy but Kodak were caught – they couldn’t abandon billions of dollars of profits when they didn’t have any new products to capture demand
  • Kodak’s entire ecosystem that had been built over decades, was one that only supported film-based photography (retail parters made large profits from photo finishing for example, which brought customers in-store multiple times). As these advantages reduced, management under appreciated the rapidity of the decline in photo printing, and retailers became less loyal to the Kodak brand
  • Kodak did actually have a separate division (unconstrained by legacy approaches) which was established to explore and develop the digital opportunity. This did see some success, achieving a good share position in digital cameras, only then to be consumed in the tsunami of smartphones with built-in cameras.
  • Kodak experienced great difficulty in managing the complex (and emotionally-charged) people issues surrounding a business in decline – thousands of staff who knew that they were managing decline but struggling with transferrable skills, managers fighting for control of diminishing resources, or feeling entitled to be reassigned, which fuelled internal politics and strife.

Kodak faced huge challenges on multiple fronts – competitive, category, operational and ecosystem – but it is too simplistic to say that their downturn to eventual bankruptcy protection was solely down to their inability to recognise that digital was coming. Yes, they failed to look ahead and anticipate the level and type of impact that the next wave of technology (and its application) would have. But along the way, there was a litany of compounding factors that made change difficult, and which are instructive for any legacy business. I’m reminded of what Jeff Bezos of Amazon said about being willing to be misunderstood:

“A big piece of the story we tell ourselves about who we are, is that we are willing to invent. We are willing to think long-term. We start with the customer and work backwards. And, very importantly, we are willing to be misunderstood for very long periods of time. I believe if you don’t have that set of things in your corporate culture, then you can’t do large-scale invention.”

Having this kind of vision and willingness to reinvent is key. Shih says that in hindsight, one approach that Kodak might have taken would be to refocus the business to compete on capabilities rather than on the markets it was in. This kind of thinking is helpful in that it might allow the business to apply it’s skills and knowledge in different ways to explore new value, but also to challenge the kind of toxic assumptions that Kodak fell victim to.

In the book we talk about how, in the age of more transient competitive advantage businesses have to be more adept at disengaging from existing advantage, and ready to reorient talent and focus around opportunity. Kodak is a salutary lesson for all.

Segments and the need to focus on empathy to improve user experience

By AgileBusiness, Customer Exprience, Digital Disruption, Digital Economy, Strategy No Comments

noodle theory and user experience

I was reading a feature on Akshay Kothari, head of LinkedIn India, where he talks of his noodle theory and user experience.

It’s not the noodle theory that’s important, it’s the story and the way he shows how this simple user experience has stuck with him ever since and how it affects how he approaches innovation.

The ability to focus on empathy with the end user results in improved user experience.

Some of what he says seems obvious, like he wouldn’t start a new project without first having spoken to the target group of users, refining key insights, having a point of view and building a prototype.

But there are some real gems here.

Having built Pulse as a college project which got snapped up and integrated into linkedin, his first move at Linkedin India was to cobble together a team of engineers, web developers, designers, and marketers and travel across four cities as part of a learning process.

He’d already decided to focus on a segment of users largely not understood by Linkedin – Students, potentially Linkedin’s future customers.
For two weeks, Kothari and his team interacted with people [students] they wanted to design products for.

“We have to think like a team of six, disrupting on our way to meet our goals.”

This reminded me of Ash Maurya, Author of Running Lean, who talks about loving the problem not your solution.…

“…most products fail — not because we fail to build out our solution, but because we fail to solve a “big enough” customer problem.”

Ash stated that energy should be channeled towards finding evidence of a monetizable problem, not towards acquiring more resources to build out your solution.

Even though Akshay at Linkedin could operate and no doubt use a large resource group from the 10,000 people at LinkedIn [or now 100,000 at Microsoft], he doesn’t.

And maybe there are “big enough” customer problems in small segments of your current and future customers as a way to innovate in a more agile fashion.

This is why looking at customer segment data is as important as focusing on what you think the big customer problems are.

Bigger isn’t always better. If we’re trying to be more agile and  think big, start small, scale fast,  maybe we need to look at customer segments (or other segments) as a way to identify big problems for small segments that can effectively be rolled out (or not) to a wider user base, effectively migrating from a small [tested] solution to a larger one.

Maybe we spend too much time looking at problems for customers as a whole rather than a segment?

Might we get more work done and improve the customer experience for a segment? Yes I know we should fix problems for all customers, but in terms of ‘innovation’ isn’t this a good place to start?

After all it is about  Jobs to be done  which can apply to a segment just as much as to every user then starting small kinda makes sense.

In the same way that Akshay built solutions at Linkedin India he initially thought were to solve India’s customers problems they can quickly roll out to the rest of the community world-wide.

 

Agile teams, Behaviour and User Experience are also key themes in our book

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On Agile Governance

By AgileBusiness, Teams No Comments

During the shift to more adaptive, agile ways of working (and particularly as agile scales beyond the tech team) questions often arise around governance and control. Concerns can be raised about alignment, control of costs and direction. People often feel uncomfortable moving away from the apparent comfort of a detailed, forecast end point, and leaders shy away from the apparent inherent risks. The irony being of-course, that many traditional approaches are built on false certainty anyway. Plans and forecasts become outdated as soon as they’re inked. Predicted outcomes quickly become obsolete and in need of updating.

So I really liked what the Co-Op digital team had to say about their approach to agile governance. If by governance we essentially mean doing the right things in the right way, then agile, iterative working actually mitigates risk rather than compounds it. The ability to be more adaptive means that we never get too far before we can switch course. The practice of working closely with end-user input and feedback. Continuous testing and delivery.

Jamie Arnold, the Head of Agile Delivery at the Co-Op details eight key components for how to do governance well in an agile context (I’m paraphrasing for brevity here but worth reading the whole thing):

  1. Outcomes are better than deliverables: the importance of orienting the team around what the product or service actually does, aligning that with the wider vision, easily measurable mid or long-term goals, space to learn what works rather than specifying the solution upfront.
  2. Measure the right things at the right time: measure a few quantitative things, make the measures visible, independently verifiable, review often. The right measures can motivate, focus and build confidence
  3. Teams are the units of delivery: small, multidisciplinary, non-hierarchical teams focused on momentum and given enough autonomy to plan, prioritise and do the work in the order that works for them
  4. Network of teams beats hierarchy: networks of small, self-directed teams with minimal inter-dependencies using data to plan and prioritise
  5. Quality is everyone’s responsibility: common agreement around what quality means, how to measure it, user feedback validating the delivery of business value, continuous quality assurance
  6. Assure as you go: improvement is continuous and supported by regular, short, challenging forums, minimal stop-start but instead the flow of value delivery
  7. Behaviours matter more than documents: less long-term documentation, more user research logs, weeknotes, verified metrics. Focus on how the team collaborates, responds to feedback, is part of a network of teams, involves stakeholders, removes blockers
  8. See delivery for yourself: not just talk, but regularly showing work in progress

Much to like about this. Yet the wider point here, and one that we bring to life in the book, is that this again speaks to principles, behaviours, and approaches that have far wider benefit than just the tech team. As Jamie says in his post agile is more of a mindset than a set of defined processes. It’s about being agile, not just doing agile.

For more like this, and for exclusive content related to the upcoming book on Building the Agile Business, you can sign up here.