I recently read a great McKinsey article that had clear and simple advice for companies building data analytics platforms. I thought it was a great template to align the article from a big business context to a practical K-12 school context, morphing the same 5 steps into a game plan for building a great data analytics platform in schools. Thank you McKinsey!

The wholesome messages around building a data platform are the same; focus on a problem, take incremental steps and take people with you on the journey. In many ways, the data journey schools embark on and follow actually defines the destination they arrive at. There is no big bang data analytics process that anyone can or should recommend for schools. 

If you don’t have internal data expertise, you really have to work with a partner who can take your team on the data journey,  coaching your team on the types of questions they could ask and how they can explore data. Don’t buy a BI solution in a box. Look for cost effective, extensible platforms that are designed for use by teachers and leaders, rather than IT people.

  

Step 1 – Make sure that everything you do delivers an impact measured in months, not multiple months or Terms.

In 5 seconds –  Aim to make either a rapid return on your investment or fail fast. The best way to do this is to pick an opportunity to use data that will make the biggest impact in the shortest time. Can you access data that is complete and come up with a way to leverage the information contained within, quickly? 

In developing and prioritizing use cases for your data and analytics platform, the single most important criterion is speed to impact. Schools that obsess over value from the start and constantly push for high-impact, quick wins are those that do best at winning over skeptics and keeping up the momentum of change.

Many analytics platform programs share a common problem: value is only seen at the end, after all the pieces are in place. Don’t wait for long term big wins, you have to win quickly or fail fast, learning from each result.

 

Step 2 – Use the data you have to build in bitesize progressions

In 5 seconds – Build data capabilities one data source or segment at a time. Additional data should build incremental value and clarity piece by piece.

Two common obstacles hold schools back from building data and analytics capabilities.

The first obstacle is the analysis paralysis that sets in when schools over think what it’s going to take to achieve something. In our experience, there is no need to start with a big bang “ mindset. Success comes from building capabilities piece by piece and connecting each step you take directly to teachers who will benefit the most from the outcomes

The second obstacle is the perceived need for a massive amount of data and ETL ( extraction, transformation and loading) time before any meaningful insights can be created.  Beware the ETL / BI consultants. School data is in voluminous supply, yet relatively simple in structure.

Many schools just don’t realise just how much good data they have in an analysis ready-state. Others just get stressed about what it is going to take to mine the data they have. There is vast amounts of school data collected by third party assessment products. These platforms should supply structured data downloads that can quickly be consumed and added to existing analytic capabilities.

Quite often schools assume their data will require thorough cleaning before it can be used. The most common data conundrum in schools is what we call nom-de-plume syndrome. This is when one students is known across multiple systems with a different name per system. These are really just silly annoyances that make combining data in schools more frustrating than it should be. This does not qualify as expensive data cleansing and when these issues are found, they need to be fixed in source systems.

 

Step 3 – Use data analytics to solve real teaching and learning problems

In 5 Seconds– Aim to solve a problem, within a Term. The believability index will lift, people will grow in confidence and the momentum you make will continue. 

Don’t lose sight of the problem you are trying to solve. Don’t let data people create another complex data silo. The data team must work with the people who have the problem, to solve the problem.

Three things to remember :

  1. Use your platform capability to augment and improve on something that you are doing now or trying to do now. At least people will be invested in the challenge if the challenge is underway. EG. Looking at diagnostic data to find skill gaps that are impacting on current learning in Maths.
  2. Make sure you embed your new data capabilities into existing processes. There are teachers out there every day. What about getting alongside what they need and making an impact there. No-one needs more systems to learn. Teachers want data to come to them rather than look through a pile of charts.
  3. Help people to adapt to new capabilities to find an opportunity for impact. Be it an ah-ha moment, clarity on what is happening or directing more targeted teaching to where it is needed, impact is the target outcome.

Step 4 – Invest $2 in professional development and support for every $1 spent creating data analytic capabilities.

In 5 Seconds :– Ensure you focus on people and processes, not shiny new tools. No matter how advanced the tool, it will be worthless without the talent and structures needed for managing and maximising its impact. Charts are really overrated.

Introducing data capabilities is an investment in cultural change and so “seeing how it goes” is the wrong packaging and message from the start.

It really is important not to roll out a shiny new toy without some good use case and early achievement wins under your belt. Take small steps, experiment with quick turnaround cycles and work in a context with a group of teachers and leaders. You have to understand what it takes to make a difference. Under promise and over deliver is the key to success.

The more agile you make the process, the more believable it will be. Make sure there are people who can articulate why you are doing this and the benefits they find.

Importantly , you must nurture internal champions and build data into a PD context where teachers are enhancing their impact and effectiveness using data.

 

Step 5 – Democratise data access to continue innovation from within

In 5 Seconds – Gear your platform to democratizing data. Make data available to all your employees, teach them how to use the data, and see what unsuspected value they can unlock for your school.

  1. Crowdsource ideas across your team – work with teacher hunches as use cases for analytics discoveries
  2. Seal data sources as stable and ready. As you build in new sources of data, certify where they are, the quality and get on with it
  3. All data should be visible by everyone. Self service tools need to be flexible per user rather than structured to the point of useless
  4. New ideas need to be quickly implemented and shared – if the use cases get stuck, the usefulness will die. Let teams suggest improvements and get them done quickly , keep data flowing to the frontline of the school where it can make the biggest impact on teaching and learning
  5. Wins need to be shared and celebrated

Not that long ago, there was a choice to be made – Start a project offline – kind of a big buck and bang process or do something that was more agile. Terms ‘skunk-works’ came into play because it was covert usually and could be trashed at any time.

Neither of these approaches are viable anymore. If schools want to get going with data, and have a result , take note of the 5 steps that make the biggest difference to success. The key to success is to win quickly or fail fast.