Why we should all aspire to be enterprise analysts - a riff
- Summary:
- Josh Bernoff's recent piece on 11 key analyst skills got me thinking: what are the key skills of an enterprise analyst? And why should we aspire to them? Here's my riff, sure to offend someone.
All enterprise professionals should aspire to be "analysts." We should all strive to add value to our employers/projects through our ability to interpret and act on data, as filtered by mastery or specialization.
How we do that, how we assemble the range of soft, analytical, software, and presentation skills to pull this off - that is another matter entirely.
I've been planning an enterprisey piece on this, but for today we'll settle for a riff, inspired by Josh Bernoff's 11 key skills of a true analyst.
Defining analysts - without ticking the professional analysts off
The enterprise has a well-known profession called "analysts."As I've learned the hard way, they get pretty miffed if you call anyone an analyst. So let's not do that, eh?
Professional analysts come in all stripes, from boutique firms to Gartner/Forrester/IDC types to independents. The lines between analyst, blogger, and journalist are blurring in ways good and bad - mostly good if you ask me (diginomica, for example, is invited to events for all three groups in any or all combinations).
I define the profession of enterprise analysts as those who conduct quantitative research and issue reports on that research. That doesn't mean such research is good research. We've all met outstanding and mediocre analysts. In the enterprise, independence is a difficult commitment, not an employment status.
Josh Bernoff's 11 key analyst skills
I'm not talking about becoming analysts in the professional sense, but in the data-informed sense. And Bernoff's piece is a good kickoff. His eleven characteristics are as follows. I've picked one highlight from each, but please check his piece on withoutbullshit.com for the full definitions:
Conduct research. "This requires research: not just reading stuff on the Web, but reviewing data and interviewing people."
Identify patterns. "Unless you see trends, you’ll have no platform on which to build your analysis."
Reason logically. "Without clear reasoning, you can’t tell what the patterns mean."
Draw conclusions. "Unless you take reasoning to its conclusion, you’re of little value to decision-makers."
Fight bias. "If you’ve already decided your conclusion, why conduct research?" Biased reasoning to predetermined answers has no relationship to the truth. True analysts always wonder if they’re wrong and seek information to disprove their conclusions.
Concentrate. "To truly understand a market like travel or a phenomenon like cloud computing, you need concentrated effort over time."
Be quantitative. "There is truth in data; it is your job to find it."
Build frameworks. "Frameworks make meaningful thinking both more powerful and easier to communicate."
Communicate insights. "Thinking alone in a room is useless".
Correct your course. "You’ve drawn conclusions. You may be wrong."
Persevere. "Every insight leads to new questions."
Here's Bernoff's graphical breakdown:
My take - elaborating and nitpicking on Bernoff's analyst skills list
I don't see obvious holes on Bernoff's list. I'll rattle off some refinements and see how they trace back.
Disclosure - perhaps this is more an attribute than a skill, though Esteban Kolsky's epic disclosures border on skill. In some cases, there are legal requirements for disclosure, but I'm referring to the ethical side. Or, if you like, the reader trust side. We're all funded by someone. Disclosure is not important when it is self-evident, for example if you are an employee blogging on your corporate blog, but most times, it matters.
Disclose your agendas also - disclosure in the formal sense is sharing the relevant financial interests of that post. But readers like to know your agendas beyond finance. Example: I am a big advocate for independent experts on enterprise projects. I don't believe that customers should put absolute trust in one analyst firm or one systems integrator. Yup - that belief also aligns with my commercial interests. I'd feel the same about independent views if I worked at a large firm, but the fact remains - I don't. It's for the reader to take that into account and assess the content. The more transparent I am, the more likely a reader is to find a foothold. Reader trust stems from that also.
Build a discerning network that puts your views through the truth grinder - Bernoff's right - we need concentrated work, but we should also put our work through the BS detector of our networks. The smarter our networks, the better our work will be. This is not about amount of followers. It's about cultivating those who give you unsparing feedback from topic authority. The best analysts, reporters and bloggers I know don't crash in their hotel rooms early. They are out in the bars and restaurants, getting the real story on what is going on inside the industries they cover. And no, that is not a commercial for alcohol; you can do this with seltzer and lime. (Ties into Bernoff's research and communicate insights skills).
Forget objectivity, take an opinionated position - objectivity is a pursuit, not a reality. It's more important to take strong positions that elicit feedback and provoke fresh thinking. I like the idea of taking data-informed positions, while trying to be ruthlessly fair to all sides. (Ties into Bernoff's draw conclusions skill).
Constantly create and destroy your industry narratives - narratives are super-important. Readers need a rooting interest and a frame to hang facts on. But narratives become legends, obscuring new information. A narrative might be "multi-tenant cloud is the best way to deliver software value", or "cloud vendor X is the market leader and legacy vendor Y is the laggard." Narratives work until they confine. So you build a narrative suggested by the data you have, then revise or discard that narrative as soon as it shows weakness. Bernoff talks about fighting bias and correcting course, both of which apply here.
Pursue topic mastery - without topic/industry mastery, it's hard to advance the data conversation. We've had diginomica debates on pursuing skills mastery and being a "polymath" across categories. The point is you need some originality and mastery to affect outcomes. (ties into Bernoff's concentration skill).
Cultivate diverse viewpoints - at most trade shows, I see folks sticking with their peers - analysts with analysts, customers teams with themselves or other customer teams. Stir the drink. It's the culmination of viewpoints that adds up to a nuanced perspective. To me, that includes the Uber/taxi drivers on the way to airports, who often give me sharp/profanity-laced takes on the local economy, regulatory struggles, or how their mobile tech affects their workflow (ties into fight bias).
Develop intellectual property - professional analysts are good at this, but we all need to do it. Having an intellectually-defensible method, algorithm, book, or software product adds to your credibility /visibility in the industry convo (ties into be quantitative skill).
Master analytics tools and techniques - this is a whole other column, but we need to master the tools that clean, crunch, identify and visualize useful data patterns or results. Data storytelling is visual.
Oh, and I can think of one more: try not to be an insufferable, pretentious a-hole. That's the old "stay humble" principle. We can also call this one "learn to shut your trap and rediscover listening." The enterprise can be so bean-counting serious. There is something to be said for having a good laugh, sometimes at our own expense. (You know, like throwing up an old photo of you that folks aren't expecting in a serious blog post). Satire might not be an analyst requirement, but maybe it should be. That's it for my riff - any others to add?Updated, evening of March 16, 2016 - added some resource links and the pic I was looking for. Deleted some text as I wandered off topic - this was supposed to be a riff, not a noodling jam session.