AMA: HubSpot Director, Data & Analytics, Revenue Operations, Josh Chang on Revenue Ops Skills

Honestly, I believe revenue operations leaders need soft skills more than hard skills. Hopefully they are coming from a background where hard skills like data analysis and visualization and Excel/SQL were needed, but broadening this question out to general skills - data analysis, storytelling, and communication and collaboration are the most important. * Data analysis: Revenue operations leaders and teams are working with and responsible for the data that supports their stakeholders, so leaders should have a strong skillset in taking that data and using it to answer questions and solve problems so they can support stakeholders as well as help their teams do the same. * Storytelling: This is kind of an extension of data analysis, but all the best data analysts are also outstanding storytellers. The CEO of your company is often not going to want the nitty gritty details of an analysis project, and so revenue operations leaders and professionals need to be able to distill complex topics into simple stories and narratives that someone who is not in the weeds will understand and take action on. * Collaboration: This is obviously important in MOST jobs, but revenue operations leaders are constantly working to align different teams and stakeholders across business functions, as well as help their own teams make the right strategy decisions. For example, Sales and Marketing are so reliant on each other, but oftentimes aren't collaborating nearly as much as they should be. A RevOps leader needs to be able to quickly identify those gaps and drive action based on aligned data, priorities, and initiatives. 

There obviously is not a one-size-fits-all approach here, but the way I think about this boils down to a few things: * Create and foster a culture of learning and collaboration amongst your team, and enable folx to solve interesting problems together without someone constantly looking over their shoulder. When your team is learning and growing together with autonomy, that can sometimes be a tough thing to recreate somewhere else. * Expanding on that, top talent will always value autonomy and trust in their work. I lean towards giving my team almost too much autonomy - the best way for them to learn is to learn from mistakes and figuring things out on their own, but it's also an important skill to know when to ask for help. * Advocate tirelessly for your team and your top talent - that can apply to comp/promotions, visibility and exposure at a big company, or giving frequent positive and constructive feedback. I've been really lucky to have worked for managers who have advocated tirelessly for me and as an employee I really valued that. Working with a manager who knows your skillset and body of work well is super valuable so make it clear to your team how much you value them and then execute on that.

One of the most important RevOps skills that could be applied across an organization would be familiarity and expertise with data specific to teams that are being supported (i.e. Marketing or Sales). Folx working on those teams are obviously experts in their field, but they don't know what they don't know, especially from a data perspective. RevOps professionals or perspectives can help to uncover new insights that teams didn't even know existed in their datasets or tech stack, or even just help identify new problems to solve and opportunities to grow the business. I'm constantly trying to work with stakeholders to identify new "What about..." questions that my team can help them solve, that would make their day-to-day easier and most importantly, their work more impactful.

This varies depending on the person, but here are some general ideas! * Try to get a different perspective, if possible from someone who can be neutral, and is familiar with both you and your work and your boss. Depending on your relationship with your boss, sometimes it can be helpful to hear someone else give similar feedback to you so it doesn't seem like it is just coming from one place. * If you're not getting this already, ask your boss to give you specific examples or things they would like to see as a result of their feedback. And, try to identify what type of support you need in order to do those things. For example, maybe scheduling a regular async check-in so that you can get more real-time feedback so you know if you're moving in the right direction or not. 

Sometimes going straight into revenue operations isn't necessarily the best path to be successful in the field. Not to say you CAN'T go straight into RevOps, but I think it can be extremely beneficial to become a subject matter expert in a particular area that you want to support from a RevOps perspective. Some of the best RevOps analysts/strategists I've worked with were experts in Marketing, Sales, etc. first, and then moved into an operations role after gaining experience in the function. This gives you a ton of perspective and most importantly, empathy for the folx and business functions you will be supporting from a RevOps position. Personally, I first worked as a Marketing generalist, and then in Acquisition and Demand Generation for 5+ years before moving into revenue operations full time, so I feel pretty strongly that this is a great path towards being successful in RevOps!

After many years focused on demand generation from a Marketing perspective, I realized that I wanted to be part of a team that helped to drive decisions across the whole organization, rather than focused on a specific team or area like demand generation. I also had a data and strategy oriented skillset that helped me naturally gravitate towards revenue operations. Coming from a demand generation background, felt I had enough knowledge of other functions where I could have a bigger impact on the business helping to connect siloed teams instead of continuing to just focus on one area, and really advocate for connection across teams to align individual KPIs to the north star KPI of revenue. 

It can depend on where you're coming from, but I lean towards it being better to come in with the soft skills, although there will always be a baseline level of hard skills you need depending on the role. For example, for a data analyst or data engineer, SQL might be a baseline hard skill, but I don't necessarily care about what flavor of SQL they know. In that case, I'd value soft skills like data analysis and interpretation, stakeholder management, growth mindset, and distilling complexity more.