Cisco is one of the leading IT companies in the world, and works very hard to work with our customers to help solve their greatest business challenges. To do this Cisco must continually transform itself to align with what our customers needs are and where the markets are going. When William took on a new role driving engineering services and operations, he quickly learned that as much as a companies products must change, a companies operations capabilities need to continue to improve to match the speed and agility needed in today’s markets. He call this capability for his team, a data driving operations model.
Today’s presentation highlights my success and challenges his experiences over the last 18 months, the role of data, the need for scale and security, the opportunity for new technology to make magic happen to accelerate business, the new role of IT to help guide and partner, and the mind shift and cultural changes along the journey. William hopes his experience till now, as this is still very much work in progress, will help others accelerate their organizations toward operational models needed to compete in the fast changing markets we have today.
William lead the Global Development Services team at Cisco. This is a centralized engineering team of over 1000 people working across all of the Cisco businesses. It is responsible for all of the Cisco’s engineering technical communication and documentation, compliance testing, lab operations and planning, power engineering, and open source compliance, i.e. a number of functions where it is critical to partner with each of the Cisco businesses and optimize for product delivery. This means huge amounts of communication and touch points, which immediately highlights the need for strong data story, both for a “what is going on”, “what is it costing me”, “when is it done” perspective, but then also “how can we make this better”. Given the GDS team was formed by moving a number of people from each of the businesses doing like work to this centralized team, there were many different ways of doing things. All in all, a great opportunity to drive a data driven operations strategy and model. Very very target rich.
So here they are 18 months later, and here is the story.
Key points to cover.
1. Key starting point: really understanding what problem they’re trying to solve, what questions they’re trying to answer, what they’re trying to optimize for.
2. Identify the key questions to answer to further refine those problems to specifics. With a diverse services and operations team, the initial problems and use cases we worked on (can discuss some, all, other, of these)
a) For overall engineering services operations and governance, providing the visibility of what is going on was absolutely loved by the businesses. On line Tableau visualizations of data from multiple data sources and drill down set example for other business operations teams to tailor. Linkages to other cross Cisco tools and processes, tying together specific business needs to overall corporate systems kept the GDS data in support and aligned.
b) For technical documentation and communication, understanding the www.cisco.com usage to further understand our customers needs, better optimizing what we are spending our time writing and creating to what our customers are using, help to create a better customer experience for cisco technical communications. Great use what we have story, IT web data into Oracle BI dashboard, filter, data dump to Tableau visualizations highlight “what is going on”, even if older data
c) For compliance testing, the goal is optimizing the delivery of product through both greater transparency and program update data flow between the businesses, partners and compliance team, and also driving greater people and infrastructure utilization. Great example of use what we have, change a few tools, tie in to larger business intelligence capability and enable where engineer provide online updates, data and info propagated to N variety of status, schedule, forecast views.
d) For engineering lab operations and planning, extending business intelligence dashboards and data into the hands of the various of each of the businesses to help both optimize space and energy cost, as well as creating the self service financial fixed asset data and asset location capability. Call it “self service and user friendly”ing financial tools and controls. Huge success moving towards 95% fixed asset location audits across over 1M sqft lab space in 55 metro areas. Huge success moving to common case management tools to support 28K engineers, allows lab operations team to trend the who what where on case work to project future needs
3. Understand and leverage what data and capability already in hand. Yes you can start a big expensive IT project to create more different, etc, but in fast moving markets that in itself is huge risk. Plus, operations teams don’t have much extra money.
4. Build a small diverse team of both data scientists and the people who had the expertise and context critical in understanding the data to work together in establishing data architecture, tools, plans. Key here is leveraging others expertise to help move forward. This is great example of team relying on IT for their Hadoop systems and database skills so our data scientist and technical writers can focus on “what questions to ask of the data”.
And that is where they are, probably about 20% there, and now ready for the next stage now that we have some “basics’ established. Next is both to leverage each of those further, and to also start understanding from the data the next level of data driven operations intelligence. Specifically, which projects move the fastest and why, what technical documents are helping the most and why, etc.
This is an exciting time in the industry, an exciting time with the acceleration to data capabilities, tools and strategies, and an exciting time in accelerating ability to respond to the challenges for our customers and markets.