Joining forces and data sources: Morphean, Snowflake, and Panintelligence combine for a hackathon
All the best things come in threes: the Bronte sisters, Harry, Hermione, and Ron, and even the pieces of the Triforce in The Legend of Zelda.
Last week, it was a trio of software companies who gave strength to the “power of three”. Morphean, Snowflake, and Panintelligence collaborated on a hackathon day that showcased the capabilities of all three companies and their three core products.
Before we continue, who are Morphean and Snowflake?
Snowflake is a modern solution to data warehousing – being a cloud data platform that allows secure and easy access to data, while scaling alongside your business.
Right, back to the hackathon
The setting was a typical Mancunian day – a grey-slate sky filled with the constant threat of drizzle. But in contrast, the air inside the venue for Morphean’s hackathon was as vibrant as the shade of yellow which ran across their banners.
Morphean’s staff had one working day to complete a single challenge: using a Snowflake database containing Morphean data, they had to build a solution in Panintelligence which would facilitate the monetisation of that data.
Staff were jumbled up and split into teams – with each group containing a range of professionals with various skill sets, including sales personnel, developers, and marketeers.
What did the teams achieve in Panintelligence?
The first group created a series of dashboards that sought to gain insight into several different areas of the business, and bring that data together in a central hub to offer one view of the truth.
They focused on:
- Optimising facilities
- Saving energy
- Planning resources
- Improving marketing services
- Connecting customers
Overall, Team 1 used they data they had to analyse how each area of the business could be improved, and focused on making company-wide marginal gains to ultimately save the business money.
The second group had a different approach to using Panintelligence – to really drill down into one business function in particular – sales!
They wanted to know:
- What their sales personnel were working on
- Where the potential lies
- How they could adapt sales better
- How they could analyse use cases to create a blueprint
- How they could guarantee success
By using Panintelligence to mine and refine their data, they saw that multiple business benefits could be achieved. They could see what was working well in their sales process and look to repeat this, by tracking KPIs, aligning internal teams better, and training staff effectively.
Through this process, they could also outline their ideal customer profile, helping to tailor their sales and marketing activities to winning more of the type of customer that will be more profitable for the business.
Team 3 went a step further and monetised their data by creating a brand-new product offering through using Panintelligence. The “Sherlock Tools” project was aimed at simplifying a complex helpdesk to offer a proactive service and increase efficiency.
The wanted to solve problems like:
- Reducing the cost of operations
- Being able to deliver a proactive service
- Improving reactivity
They created a dashboard in Panintelligence which was designed for businesses with a complex helpdesk, containing various charts which told them:
- The status of devices
- Cloud storage capacity
- Connection statuses
- Firmware statuses
- SD card capacity
- Devices in maintenance
… and more.
The fourth and final team created a dashboard that would help to monetise their data by searching out upselling opportunities for their customers and their businesses.
Their dashboards centred on using data to learn five key aspects of an upselling opportunity:
- Understand the customer’s costs
- Understand what they are selling
- Learn what they could be selling
- And learn the value of their connections
Ultimately, the Morphean hackathon was a great way for us to see the technical fit between our software, Snowflake, and Morphean – all collectively working together to become the tools required for the teams to theorise four separate ways to start monetising their data for business gain.