Looking to the future, we will be facing new challenges and require new skills and knowledge. So what are the skills we need to shape the future, as planners, analysts, coaches, and managers? As professionals, we need to be highly skilled at learning along the way, not just in formal training or directed learning but with day-to-day learning habits. We need to learn from others who are raising their game, strong at networking and benchmarking too. If we stand still, we will find it hard to adapt in these uncertain times. We won’t keep up, let alone be ahead of the curve in the way that is needed, if we are to be really agile and rapid in our response to volatility, uncertainty, and change.

The learning pyramid

Ivan Smith, Fellow at The Forum, talks about this as like a Learning Pyramid (see diagram on the next page). We start by moving from mandated training to more self-directed learning, where we need to focus on our personal learning goals and take responsibility for our own development. Then we can explore the higher levels of the pyramid, with networking and innovation, because here we experience the real joy of learning. It is no longer just another task, but something we want to make time for because we see the value, for ourselves as well as for others. This is important to us at The Forum because we are a learning organisation and our purpose is to help you, as professionals, realise the difference you can make. So, what would enable your operation or team to be a learning organisation too? Or how might you share this if you are already seeing success? A key stage of learning is to first practice new skills, in this way we can apply new knowledge, every day. In learning circles, this is ‘conscious competence’, before eventually new skills become natural, or automatic. We see this in the world of sports for instance, or in music and arts. Here we need others to encourage and support us, and we need the time to do this. Applied learning is the key to being a highly skilled learner and this is where we can stand out as professionals. Then, with operational learning, we can embed new ways of working into playbooks or new operating models, which is just as important as personal learning of course.

Becoming improvement champions

The mark of a professional is that we become improvement champions, because if we want to be valued, and have a seat at the table for key decisions, we need to show the difference we can make, and where we fit in as an operation, team, or individual. The improvement cycle (see diagram) focusses on three phases of improvement, and we need to take ownership of this, as individuals and teams. It is not enough to just produce data or resource plans, for instance, or to fix a problem in the moment. You add value when you link the work you do, in the regular day-to-day tasks of your operating rhythm, to the
actions that these tasks drive, and the priorities of the wider business.

Take a moment to consider the impact you are making in your role. How much are you empowering changes in behaviour, for front-line colleague for instance, or key stakeholders and leaders, or even customer behaviour? We can’t really make people do anything, so there is a raft of skills we need within our teams to influence and engage. We see learning modules like Stakeholder Engagement and Telling a Story with Numbers to be really popular with members. A regular heartbeat of reports and review meetings is vital too. How do we make accountability for measures as close to the people who can actually make the change as we possibly can? How do we simplify everything, so that focus isn’t lost by too much information? If we do our jobs outstandingly, we will see many changes, and a visible move away from siloed thinking too. Consider too, how you can drive changes in process, which is increasingly important in a digital world. Back office support teams typically blend different specialist roles to support this, as we explore later in this article. So, as this style of planning and analysis becomes mainstream with growth in digital channels, think about the breadth and depth of the skills you need for creating customer, colleague and data journeys that are really well connected. Typically we see closer links too between support functions like Planning, Analytics, Quality, Knowledge Management and so forth. Whatever the change we want to drive, we need to simplify and focus on what matters most, as the opportunities to improve are infinite. If we are not careful, we end up like a kid in a sweetshop. We may be overwhelmed, or we try to fix everything at once and just make things worse.

This is where the first phase of improvement is important. So, first link what you do to your organisations strategic purpose and key goals, and then narrow down the focus areas for improvement. Then you can build a heartbeat of reporting and engagement that keeps attention on the right issues and behaviour. In all this, we need to be a trusted source of truth, as business partners, and to keep developing shared understanding and learning across the operation. We also need to be able to effectively express the benefits we bring to the business.

Confidence with numbers

Confidence with numbers is another skill that marks out successful professionals in this volatile, uncertain, and ambiguous world, as we saw in our earlier article. We need to build confidence, consistency, and clarity of expectations for the future, as this reduces the anxiety that comes with constant change. So, look for confusing or surprising numbers and become confident in how to explain them! This is a skill that’s fundamentally important for front-line teams, managers, and coaches, not just planners and analysts. But those who are close to the numbers, or creating them, have a special responsibility to build up this confidence at all levels across the operation. As part of our own development, we may need to do some mental gymnastics, to keep our brain in trim. We need to focus on understanding key numbers at a deeper level and create simple ways to explain them – as was done in the early days of The Forum with ‘The Power of One’. As part of our working practice, we need to see analysis as collaborative and purposeful. We, as analysts, have a special role in bringing the data to the surface, for the right people, at the right times and in the right ways. Equally, stakeholders, at all levels, need to engage with the relevant numbers, and ideally take responsibility for explaining them to others, as that is how they will buy in and understand more fully. Analysis is a team game in a fast-changing world!

Data needs context and validation, and any figures are meaningless if you don’t understand where they come from. For example NPS or CSAT scores depend on factors like who we survey (or don’t) and what type of contacts or channel we include in our sample. Demographics may skew data, if older people score us higher than younger, and geography, if people in the South were harsher than those in the North. Even time of day can make a difference. So understand your data before you draw comparisons or conclusions or set expectations. When analysing, designing dashboards or benchmarking, don’t jump straight to the data tables without knowing what they mean. It is good to observe people using the process. Talk to them, see what data they input, notice the data they use or see. How does this impact decisions they make?

In particular, make sure you are clear about statistical confidence and sampling. Do you calculate whether the trends or exceptions you identify are statistically significant? The descriptive statistics functions in Excel are great tools, popular in our learning modules on Insight. How do you identify underlying causal relationships in your data? Remember that correlation is not causation, a common error! Be clear about the different kinds of potential bias that impact the conclusions we can, or cannot, safely draw from data we use, and the assumptions we build into our models. If you want to read more there are some great articles in our 2021 Best Practice Guide on Forecasting with No Data and Predictive Analysis and Machine Learning, with a series of new learning modules being developed for our Learning Academy this year. These skills are even more important, not less, as AI and machine learning technology takes off. We need to be the quality assurance checkers for bots!

Understanding end-to-end journeys

The skills we need for the future are also evolving and changing as a result of the new challenges of next generation customer contact (see pg 31). For instance we need to review and design joined-up journeys, so customers can do what they want, quickly and easily. Half of all customers use three to five channels within one journey, according to data from McKinsey. Yet many customers are still ‘going all over the place’ because we don’t clearly manage the journey for them, or the process isn’t quick and easy. Often, we don’t know where they have just been or what they do next, or the information is not easy to use. So joining up data is a key challenge we face, whatever department or role we are in, and we need a cross-functional federation of insight to garner the resources and mix of skills that will really tackle this. It is often useful to think about charting data journeys and handoffs, not just journeys for customers or colleagues as we spell out what process and systems changes mean for them. At the same time, the colleague lens is becoming far more important post-pandemic, with the great resignation and the need to develop new strategies for attracting the right people and skills into the operation. This is true of support and leadership teams, at all levels, as much as the front-line, back office, field, or branch operations. To retain our hardearned right to sit at the top table, we need to be able to evolve our planning and analysis methods to focus on these problems, as we explored in chapter 3.

At the same time, we need to keep telling customer stories and put ourselves in the customers shoes. This remains as important, for analysts, planners, and other support professionals, as ever before. We don’t need to just play call recordings to bring the stories to life, but show the overall journey disconnects, the outcomes that different processes are driving, and so forth. Above all the capacity to make emotional connections is a fundamentally important skill for the professional of the future.

Shaping the future

With these developments, the skills we need are spreading and deepening. To support operations or transformation teams, these are some of the common skills or roles that we see among successful members. Clearly, it’s not realistic to expect one person to be good at everything. In a large team, this may give the chance for people to develop specialist skill sets that build on their strengths. Smaller functions may build a virtual team, to draw on more skills and perspectives.

• The Engagers. A business partner may define problems we need to solve, agree a scope of work with stakeholder and engage them throughout. Some may be active salespeople for our support products. Coaches, mentors, and trainers help people to learn and develop their skills and knowledge. A co-ordinator may keep all the parts of the team and projects on track.
• Business & customer specialists will include process designers, already key in the back office but of growing importance in the digital channels, change teams who are expert at landing clear communication in this fast-changing world, and quality assessors who draw customer insight from calls, chats, or back office processes. Knowledge managers provide relevant, accessible, and up-to-date information, for use in customer conversations on any channel, as well as on the website and automated chatbots. We increasingly use the same source information in different ways.
• Data Specialists. A data steward ensures data is accurate, accessible, up to date, clearly defined and documented, is secure and complies with all regulations. Data reporters design reports and dashboards around the needs of the user. Developers make these designs a reality and programme automation of tasks or analysis.
• Analysts of all kinds. Root cause analysts look at the key measures in the report to understand why they are what they are. Visionaries look for opportunities to innovate and improve. Quality analysts offer unique skills for understanding customer experience and planning analysts on resourcing and operating models. Predictive analysts or forecasters create the models that allow us to predict the future impact of different assumptions and answer ‘what if’ or ‘if then’ questions, as we explore in chapter 2. Investigators use scientific and statistical methods to test conclusions they may use. Data scientists will use advanced analytics or AI on large, diverse data sets of data.

Remote and hybrid working has brought to the fore the value of a truly digital workspace. Not only is this vital for knowledge sharing in the front-line, but tools like MS Teams and Slack are vital for planners, analysts, and mangers to use in sharing knowledge and collaborating better too. How much do we scratch the surface at the moment, and what could happen if we were to focus in this area for our own development?

Benchmarks: learning along the way

As we explore and network, using approaches from the higher levels of the learning pyramid, we need to be careful about the data we use before drawing conclusions, as we have seen earlier. A benchmark is a consistent measure that can be safely used for consistent comparison. Think about this when you set up your suite of diagnostic measures and performance playbooks that we talked about in the previous article. Comparing numbers measured in different ways with different criteria can be misleading. We need to think broader as the most useful benchmarking is studying what others do, comparing processes and practices to identify improvement opportunities. This can be internal, between individuals, teams, channels, and work types, or with other departments or organisations. To be most successful, focus on best practice (not just metrics), continuous improvement (not one-off fixes) and share information as learning partners (not corporate spying).

There are a number of ways to benchmark, both through The Forum or on your own, by using our online library and best practice guides, with a host of case studies and articles. Here you learn what others are doing and how they are overcoming challenges. Network groups, live case studies and learning programmes provide other great opportunities. All our award finalists have a video presentation shared on our website, many learning boxsets now including a best practice showcase and our network groups and conferences have catchup pages, if you are a member or delegate. Also, network across your organisation and partners. Award-winning work at Anglian Water in 2019, on their Insight Network is a great example to learn from. Try desk research on the internet; some topics have hosts of free material. Finally, online networking, for example using our new Forum Community App is another way to keep this going with easy, bite-sized, daily learning habits.

What we learn will depend on the quality of the questions we ask, of course. When you ask a yes or no question, you will most often get incomplete information. Instead, try some open-ended questions. Try to avoid tag questions, statements that appear to be questions, unless you are testing understanding, as these don’t allow for any kind of answer except Yes or No. Questions with “would,” “should,” “is,” “are,” and “do you think” also lead to yes or no. Whereas questions with “who,” “what,” “where,” “when,” “how,” or “why” lead to people giving some thought to their answers and provide much more information. Factual and investigative questions are especially useful for benchmarking and learning. The objective of a factual question is to get information. You may not know the immediate answer to a factual question, but you know how to find it. An investigative question is divergent, meaning that there is more than one correct answer it forces us to investigate all of the possibilities.

Finally, when reading or watching about what other members are doing, you may find it useful to ask questions like this. What were the key similarities and why do you think this may be? What were the key differences and what might be the drivers behind why each business does things differently? Look for one difference that would not work in your business and consider why this might be. Then identify one difference that would work in your business and explain the benefits you would expect to see if implemented.

Author: Paul Smedley & Ian Robertson

This article was first published in the 2022 Best Practice Guide - You Moment of Truth: Confident to Succeed

To download a full digital copy of the Best Practice Guide, click here