Big data and data visualization have become overwhelming for some, and an opportunity for others.
I spoke with Yen Yen Siu to get her thoughts data, story telling and curiosity.
How do you turn data into stories?
Think about the classic fairy tales: Little Red Riding Hood is not just about a little girl escaping from a wolf.
The story is about a little girl in the role of being a granddaughter and the wolf being a predator. Each of them have roles and responsibilities which drove them to their particular actions. So if I can get users to think about their roles and responsibilities and what key moments form their storyline in the company’s tale, it’s then a matter of choosing the right data to describe those moments.
Data is both generated by and influences human actions. A story is compilation of select actions and their results as focused on key characters.
A sales analyst’s story point can be about how their forecast accuracy led to improved inventory turns which contributed to reduced stock expiry and resulting in improved gross margins. Go back and define the standardized calculation of those key metrics and there’s the data story!
How does data visualization influence corporate storytelling?
I have a graphics design background so I always think about symbols and visual language. Most of us learned basic graphs like lines and bar. Then we had an a-ha! moment when we discovered combining a line chart to show trends and bars to show performance.
Suddenly a whole new way of communicating more information in the same space came to be. Then we added multiple axis and it became a point of excellence to be able to cram as much data onto a PowerPoint slide.
But does the audience really understand what the story is beneath 10 multi-axis charts? Does the storyteller?
If you can show your key KPIs in a clean and intuitive manner, it’s a much more impactful call to action than burying the message under lots of charts. Our energy should be spent on improvements and developing answers. Complicated charts require detailed explanations and arguments — I expect them to be in academic papers or books.
On a corporate dashboard, where the goal is to monitor company health and get reads on trends, the message needs to be clear and concise.
What is the most challenging part about the rising amount of data within organizations?
With rising amounts of data, we have an increasing need to be able to curate data for particular purposes. Modern ERPs are designed to capture transactions on a highly granular level.
Growing data volume means that we need to evolve our speed in processing data for meaningful connections. Let’s share our collective wisdom in setting useful filters and analytical paths to shape data.
But if we are trying to understand our ability to satisfy customer demand, as represented by perfect order fill rates, who needs to know how many edits a line went through? Or that an order required hundreds of work transactions to complete it? Why are these data points important? To whom are they important? How would you recognize that they are important or that there could be correlation?
How do you promote curiosity about data across departments?
I personally prefer showing that if we use data to tell a common story, it will lead to faster and more cohesive decision making. It’s useful being able to get people interested so as to further or protect their self-interests, but the goal is to have people proactively and naturally work cross-functionally. To do that, we need to use terms that have common definitions and references to the same reality. A company’s data is its empirical reality.
When I was an international demand planner, I would need to align forecasts from global sales teams against a centralized category’s product roadmap and also consider production planning’s constraints. To support the roadmap and sales forecast, it meant having to pre-build “excess” stock because of line capacities.
This resulted in higher than acceptable inventory levels which was a KPI for which my inventory management team was responsible.
If they didn’t know that the reasons behind the spike, they may feel resentment about how I “messed up” their performance. But because they understood my reasons which was presented with data, they can speak to their performance more effectively.
Why is it important to have clarity on how KPIs cascade through an organization?
Clarity makes it easier for members of all levels to understand their purpose and contribution, which in turn makes it easier motivate and manage people.
Cascading KPIs, if clearly communicated and cascaded, should align to a company’s business processes. People perform processes and KPIs are both a comment on their value and the effectiveness of the process.
How do you define cross functional communication and why is it important?
The standard definition would be “Communication across different business areas such as Operations and Sales.” However, any department or group of like-minded people will often have developed their own jargon, with context and subtext to which non-members have limited if any access — like team sub-culture. Added to this, business functions may have conflicting agendas even if they all share the same strategic goals.
Cross-functional communication isn’t simply about being able to speak to other areas about defined issues — it’s about learning and teaching each other your language and sub-culture and combining to form a common version of reality.