The Story Behind Analytical Success: Non-Technical Skills for Analysts
What are the most important non-technical skills an analyst needs in order to be successful?
The Big Skills ‘T’
One way to think about skills is to picture the letter T. The trunk of the T represents the deep, specialised, technical skills you need to perform the core tasks of an analyst.
The cross-bar represents the more generalist skills you need to, say, interface and work with others, manage your and your team’s time and resources, as well as your ability to think clearly, write clearly and speak clearly.
Note: Any list of non-technical skills is going to be subjective to a certain extent, so these are just my thoughts gleaned from my experience over the past decade or so. This is not exhaustive and I’m curious to know which skills you might add, so please reply to this email with your thoughts.
So, in no particular order, here are my top-5 non-technical skills for analysts.
Number 1. Thinking clearly.
Unsurprisingly, as an analyst, you’ll need to be able to analyse and interpret data to generate meaningful insights. Put more plainly, you need to be able to think clearly. Structure your thoughts. Get to the heart of the issue.
And Tied to analytical thinking is problem solving.
As an analyst, you’ll be confronted with and expected to solve problems, perhaps, on a daily basis.
This includes clearly defining problems, breaking complex problems down into smaller constituent parts, with manageable steps that can be worked through.
Seeing clearly via visualisation
One approach to problem solving that I’ve found really helpful is to visualise a problem to unlock new solutions.
Simple diagrams can show your team the component parts of a system or process, how they interface and come together to form a big picture perspective.
They are also really helpful in arriving at a collective view of a problem and the problem space.
And these visualisations – the diagrams you draw as well as the process of drawing them – can hold a further benefit: they can be an essential tool for keeping us motivated on smaller tasks because we can better appreciate how they contribute to a bigger, tangible outcome.
Schemas and Frameworks
Another pro tip to help you and your colleagues through the structured process of finding solutions or conducting more involved pieces of analysis, is to create a framework or schema to organise your thinking.
The benefits of creating a framework are legion.
For example, you get clearer about how things interrelate – to highlight problems and reveal solutions – as well as helping you to avoid duplication and scope-creep.
For help with how to create a framework, check out my video about the MECE concept…
A further benefit of frameworks is that you produce something that lives beyond the lifespan of the single problem or project you’re tackling today to be repurposed in the next project by you or colleagues.
If you’re looking for resources to help you sharpen your problem solving skills, some I’ve found useful include:
- The cognitive training app Brilliant – an app that features plenty of interactive lessons with examples. Delivered in a beautiful format and has about the right level of absorption to engagement ratio, there’s a paid version, but there’s loads to get started with for free. Note that other cognitive training apps exist. (And this video is not sponsored by Brilliant.)
- Then there’s games [chess], Puzzles and brain teasers like…
The Farmer’s Riddle, where this poor person has somehow got themselves lumbered with the task of shipping a fox, a chicken and some corn across a river.
Or there’s the Burning Rope Riddle where you need to precisely measure 45 minutes but only have to hand a couple of ropes that unhelpfully take an hour to burn through but do so at uneven rates.
Or there’s the Konigsberg Bridge Problem in which you seek a route across Konigsberg’s (modern-day Kaliningrad) seven bridges without crossing any bridges more than once.
(Spoiler: it’s not possible). But, in a curious footnote, explaining why it’s not possible confounded mathematicians for years and even spurned a new field of mathematics (now known as graph theory).
- Crosswords are another option. Examples include the New York Times Crossword, which started in 1942 and gets progressively harder throughout the week.
Or even older, the Guardian crossword published Monday through Saturday, the first one appearing on the 5th of January 1929, see if you can solve it for yourself https://www.theguardian.com/theguardian/from-the-archive-blog/2013/dec/17/crosswords-centenary-first-guardian-1929
I’ve already mentioned frameworks, and would add heuristics (i.e. rules of thumb) and concepts that you can throw at a problem.
- the kipling method. I Keep Six Honest Serving Men They taught me all I knew Their names are What & Why & When & How & Where & Who.
- the “5 whys” which burrows down into the heart of a problem. “But why? But why? But why?…”
- if your problem is about which decision to make, you could try a decision matrix
List your options, set out your criteria, weigh your criteria to capture their importance, score your options against your criteria; tot-up the final scores on the doors. And tah-dah! Your decision is taken.
Of course, you’re not bound by the output, and like any other conceptual approach it’s simply a way to get you to think through options and justify your decision to yourself and others.
- break down a problem into smaller constituent parts;
- redefine the problem;
- bring in a facilitator;
- bring in new information;
- work backwards to seek out a problem’s root cause; or
- just take a break and come back to it again refreshed.
Ok, let’s move on to the next non-tech skill…
Number 2. Operating in Ambiguity and Uncertainty
We live and work in highly turbulent times. So, analysts need to be able to handle ambiguity and uncertainty.
Aren’t they the same thing? Well, no. Ambiguity is when the item of consideration is unclear and difficult to determine.
A good definition for ambiguity is:
“existing in a state of having more than one meaning, interpretation, or path to resolution”
The Time Between Dog And Wolf
For example, take the old French saying about the time “between dog and wolf”. This is a reference to the time of day when failing light means you can’t quite see clearly enough to tell what approaches you: friend or foe), it’s not clear whether the creature that approaches is a dog or a wolf.
Here are some other classic examples that illustrate ambiguity:
Uncertainty, however, is when something is not known beyond doubt, and is estimated based on probability or personal experience.
9 times out of 10 the creature that emerges is a dog, so don’t worry.
How to approach ambiguity and uncertainty
Given that an analyst’s job is to make sense of evidence and uncover insights, it is essential to be able to work through ambiguity and uncertainty comfortably – (by asking probing and clarifying questions) and (by gathering information).
But more than that, it’s also imperative to help others understand the limits of what we can and sadly cannot parse from available information, and work with what we’ve got.
For example, I’ve advised colleagues and stakeholders about lines to take based on a piece of analysis – and how far the evidence can support certain statements and conclusions, and where to draw the line and say, it’s too ambiguous or uncertain to say that. It’s about having confidence in your lack of confidence.
I think it’s also worth remembering that people react to and ‘feel’ uncertainty and ambiguity in different ways.
Some recoil from it, seeing risks that need to be managed and eliminated.
Others embrace it, if not even race towards uncertainty seeing it as an essential condition for opportunity. For these people, the “unknown”, is something more akin to the “uncharted”: Territory to be explored and conquered.
Contemplating how people feel about the unclear, the unknown and the unknowable can help you to share your findings more effectively with different audiences. For example, you might want to present subtly different messages using different language when talking to members of the audit and risk committee, as opposed to a gathering of entrepreneurs.
One further point is related to a skill I’ve not included here but could easily feature in an even longer video about essential non-technical skills and that’s business acumen. Understanding the ambiguities and uncertainties as they apply to your sector – be that regulatory, operationally, politically, financially – is really important and that requires a sharper sense of how the business of getting things done .
Number 3, time and project management.
There’s a bundle of skills that you need to keep the show on the road and keep your projects running smoothly. You need to know something about time and resource management.
Individual time and project management: Analysts need to be able to manage their time efficiently to meet project deadlines and keep track of their workload. You also need a mechanism of letting others know how your projects are progressing – both as a way to give others assurance that you’re advancing as planned, but also to flag up to management if you’re encountering issues that need more resources or their advice to resolve.
Friday Flash Reports
To communicate how things are progressing to others inside and outside my organisation, I picked up a great idea from a colleague called a Friday Flash Report.
It’s an message (could be an email or slack comment or update to a visible Notion Page) to all of a project’s key stakeholders that provides a quick “flash report’ update on the work that had been completed this week, what remains outstanding and what is coming up the week ahead.
Simple and succinct: a Flash Report it is a really powerful way to keep people up to speed, flush out issues by making them visible to all and encourage questions as a project progresses. It quickly becomes part of the machinery of project management that I’ve found to be indispensable – and highly valued by clients, which brings us onto…
Number 4. Know something about people & working well with others.
Collaborating with others, be that working with team members and other stakeholders in order to deliver the best outcomes. I talk a little about my approach to getting the best results using something I call “mutually assured construction” whereby you engage with people inside your organisation (colleagues to lend assurance and credibility to your work) as well as outside your organisation (for example, sharing with a client the assumptions and inner workings of your analytical models and methods) and to do this early and often.
Of course, Interpersonal skills oil the wheels of collaboration. The aim is to be someone that’s a breeze to work with. How? Patience, politeness and professionalism tend to go a long way, coupled with being open to new ideas and perspectives.
Number 5. Writing and Speaking Clearly.
Whether it is talking to internal stakeholders, writing formal reports for clients, or simply sharing your work with colleagues via email; strong communication skills are a must-have for any analyst.
Just ask yourself this: what use is any of your technical prowess if you aren’t able to engage others with the insights that you’ve worked so hard (or effortlessly, if you’re lucky) to produce?
Ultimately good communication boils down to:
Being able to express yourself clearly and concisely, using the language of your sector and organisation which is then tailored specifically to your audience and provides them enough context to engage meaningfully with what you’re sharing.
Not sure what the language of your sector or even organisation is? Well, try this: copy text from your organisation’s annual report or external reports, perhaps from your organisation’s website, and paste it into a word processing document (word, google docs, pages, etc). Next, put these into a word cloud generator. You’ll get an immediate feel for language and priorities.
A final point on communication is about a skill that’s gaining increasing prominence and importance: Telling stories with data. So important is this skill, that, according to Harvard Business School, some companies are either including “data storytelling” as a required skill for analyst positions or, in some cases, they’re bolstering their analytical teams with dedicated data storyteller positions.
Some might think that Storytelling with data sounds a bit grandiose and detached from the rest of your analytical process. Isn’t it simply data visualisation with a bit of narrative sprinkled on top?
I think that’s mistaken, but that’s something for another post – let me know if that’s something you’d like me to write about.
Thanks for reading.
Until next time,