Sid Kumar

There are four key foundational pillars to a RevOps strategy: 1/Talent, 2/Process, 3/Systems, 4/Data. I'd start with Talent and Process changes in the near-term, while starting to build your plans and roadmap for your Systems tech stack and Data architecture. In my experience, you need all these capabilities to operate a world-class RevOps function which can scale with your organization. However, each of these areas have different time horizons to impact. For example, Systems and Data investments are foundational capabilities that will take a longer time to yield a return (18 to 24 mos) whereas you can start to make Talent and Process changes that can have near-term impact to show near-term impact and drive sustained momentum for your strategy. One area which I've found to be high leverage is getting your organization entirely aligned around a single view of the customer journey with clear North Star success metrics and organizational owners who are accountable for driving success at each stage.

I'd encourage you to partner with your sales leadership to align on a shared vision around your reporting and analytics roadmap and get the buy-in and sponsorship that these views will be valuable and enable them to do their jobs more efficiently and effectively (e.g. focus on the right opportunities at the right time, understand where pipeline is stalled). If they buy into the vision and what you are trying to build and rollout, then I'd suggest asking for their help in reinforcing the guidelines around deal hygiene and calls to action for the sales team. If sales leadership and reps can have a clear understanding of how they will get value from these dashboards, then they are much more likely to contribute towards ensuring their accuracy. Since this is a new approach for the organization, it will take some time and continued reinforcement and communications to drive this behavior change. 

I'd consider a format that is easily accessible and that is easy to keep up to date. As such, I'd suggest something like a company wiki and/or link directly from your BI tool or whichever platform teams across your company access data and analytics. When creating this data dictionary, I'd spend the time upfront to get alignment from all the key stakeholders across the company that touch data that this will be the single source of truth and align on the process, timing and owners for updates to maintain the relevance of the content.

As a RevOps leader, a key capability that I rely on is conversational intelligence to complement a data-driven quantitive approach. The B2B SaaS market and buyer preferences are changing at such a rapid pace and it's super important to stay plugged into what is on the minds of your prospects, customers and partners. I regularly leverage conversational intelligence to listen into calls and get aggregated insights into market sentiment, emerging use cases and identify any friction points that may exist across our customer journey. Conversational intelligence allows us to get into the minds of our prospects, customers and partners and understand what problems they are looking to solve and how they want to solve them. When combined with a data-driven and analytical approach, these insights give me inspiration to proactively launch new plays and initiatives to drive continued customer value.

The specific answer here will depend on the type of organization (e.g. B2B/B2C), target segmentation (e.g. Enterprise/SMB) and go-to-market model (e.g. Product Led Growth, Sales Driven). I'd suggest looking at this through teh framework of of leading indicators (input metrics) and lagging indicators (output metrics) which are aligned with your buyer's journey and then determine over which time period it makes sense to evalute these metrics. Factors such as sales cycle will play heavily into these decisions. If we decompose revenue, it's comprised of # of deals * ASP + recurring revenue from your installed base (taking a simplistic view) which are all output metrics. To look at the underlying health of the business in the short-term, I'd look at the input metrics that drive the # of deals, ASP and installed base health and ensure that there are clear drivers aligned to these metrics within the organization. For medium-term to long-term, I'd look at diagnostic metrics to look at the composition of your output metrics (in this case, revenue) and look at what channels and demand sources helped to generate this revenue (e.g. BDRs, Marketing Leads, Partners, eCommerce, PLG, Services). You might look at this on a trended or quarterly basis and assess the relative efficiency or effectiveness of these channels and work with your leadership team to discuss what pivots or shifts you should consider making to accelerate sales velocity.

I would recommend closely partnering with and advising this new individual to start with a listening tour of sales managers, sales reps, prospects, customers and partners to develop a deep understanding and appreciation of the current state of affairs before making any pivots to the strategy or tech stack. It is important to understand 'what you are solving for' before making changes to strategy and a tech stack that may have worked at a previous company. If you do this together, you will both have shared insights around what's working / areas for improvement and you can work together on refining and updating the strategy to solve for: 1. Company objectives, 2. Customer needs, 3. Sales manager and rep productivity. Essentially, slow down to speed up. It's more important to get it right and build a scalable model for the long-term than moving too fast for the sake of taking quick action. I would also consider bringing in other stakeholders that have been at the company for longer tenure to help you and managing expectations with this new leader.