Telling our Story - 1

 It is good to be back from vacation feeling rested and refreshed. One of the joys of vacation is having that "ahaa" moment when something you have been puzzling over in your mind suddenly becomes clearer.  It seems like taking time away from the desk and computer, letting the mind relax and letting go the synapses suddenly line up and you get the new moment of clarity.  For me, coming off this vacation the clarity moment was about how we tell our performance stories in the public sector. 

It was one of those moments as a facilitator/trainer that I knew would come, but never expected when it happens.  I was doing a two day seminar on results-based performance measurement.  We had learned the basics of building logic models and designing relevant indicators. One of the participants then asked The Question: if you only had two indicators to report on - which would you choose?  It was one of those moments where I could weasel out ("It depends!") or I could do the hard work and really try to answer the question with some insight.  I took a deep breath, paused for a moment ("Great question, thank you for that!) and thought about it. 

As senior managers of public sector programs and policy, we take tax payers money to invest in activities and produce outputs that contribute to outcomes and impact.  In the final analysis there are only two things that matter: efficiency (did we use the resources wisely - did we do things right) and effectiveness (did we do the right things) that contributes positively to the impacts we are looking to enhance.  

If we are restricted to just two performance indicators to tell our results-based performance story then those are the two: an efficiency indicator that helps explain how well we used our resources and and an outcome indicator that tells us how well we contribute to desired impacts. 

So often we get caught up in designing several dozen indicators for a program. We know full well that we do not have the time, capacity or the data available to tell a full story on all of those dimensions.  If we just started with two indicators: one on efficiency, and one on outcomes we would have 80% of the performance story we need to tell. That makes live a lot easier.

Taxpayers and our elected officials want to know how well we are using their money.  We have a responsibility as public sector senior managers and executives to use the resources given to us wisely.  We also have a responsibility to measure the contribution and impact of that investment - so that if the results are not positive that we can make better policy and investment decisions to ensure that the expected results can be produced. The ability to get the resources we need to make a difference in our work is totally dependent on our ability to tell compelling and authentic performance stories.  Efficiency and effectiveness is the foundation of that story. 

Luckily, it was a good answer!  It resulted in a valuable discussion with the participants on focusing on the relevant few indicators, rather than the comprehensive many. Looking at the projects and programs under your management - if you could only have two indicators - one efficiency and one effectiveness - what would they be.  In future posts we'll explore how to use Service Delivery Models to identify the best indicators. 

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Feel free to contact me by email or follow me on LinkedIn.  For further information on data driven impact and data driven government, visit my website at www.datadrivengovernment.ca.

Building a Data Culture

"I had come to an entirely erroneous conclusion, which shows, my dear Watson, how dangerous it always is to reason from insufficient data."  Sherlock Holmes (The Speckled Band - 1892)

Our goal here at Data Driven Impact is to promote the use of data to promote better policy decisions, program delivery and service to stakeholders. McKinsey suggests 70% of digital projects fail.  IBM says it is closer to 84 or 85% of digital projects fail.  Given that governments and public sector agencies are amongst the most active data collectors, we need to find better ways of using data as a strategic asset. In my experience, the biggest hurdle to effective data and digital transformation in government is the data culture. 

Data culture is the recognition that having data is not enough.  We need to transform that data into information, knowledge and insights that inform decisions, policy and impact. That requires a transformation of our organizational data culture. Data culture includes the values, behaviours and attitudes of executives and employees about the use (or nonuse) of data in our day to day activities. We already have an existing data culture that may dismiss data as a key strategic asset or as a critical input into decisions and discussions.  We need to transform our data culture into one where data is not just seen as a key strategic asset, but is used as a key input into creating effective policy, decisions, impact and outcomes. 

Tableau has created a framework to help organizations do just that. Having spent several years working with customers to improve their data strategy, the company identified five elements of a successful data culture: 

• Trust: Leaders trust their people and people trust the data.
• Commitment: People treat data as a strategic asset, and they fully commit to realizing the value of their data assets. 
• Talent: To effectively analyze data and use it to make better decisions, agencies must invest in their employees: a data culture, after all, is ultimately composed of ‘data people.’ 
• Sharing: Data requires collaboration: Most problems can’t be solved by one individual or team. They rely on collaborative teams to share ideas and insights with one another.
• Mindset: People prioritize data over intuition, anecdotes or rank. A shared, data-first mindset creates an environment where ideas lead to innovation and impact. 

Transforming a data culture is a key step in driving data driven impact in the public sector.  I believe that understanding and fostering a positive data culture is 80% of a public sector data strategy.  The technology is easy!  Building the culture takes time, listening and understanding - it is the people side of data transformation.  We will have lot's more to say on this subject in the future.

For more information on data culture see the Resources section at datadrivengovernment.ca

Please share your data culture experiences in the comments below.  

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Feel free to contact me by email or follow me on LinkedIn.  For further information on data driven impact and data driven government, visit my website at www.datadrivengovernment.ca.

Challenge 2: Data is Hard to Share

Recently, I was working on a data analytics project and needed to get confirmation on some of the data I was working on. I contacted my subject matter expert and we needed to exchange data.  He was using one kind of software and I was using another.  It took a few minutes to figure out how to export my data into a format that he could use.  Luckily, data formats are more easily exchangeable than in years gone by, but it highlights the ongoing issues of sharing data and the hurdles we need to go through to share our data. 

Sharing data is really important to the value of data.  Data is like money - in many ways data is the new currency - the value of data goes up the more it circulates. If I have a data set that works for me - that is good. However, the value of that data goes up exponentially the more it is shared and referenced.  This is a crucial component of creating impact, especially in public sector science based organizations.  

In the areas of climate change research, public health, food safety, and so many more, the ability to collect, analyse, publish and share data is a key success factor to increasing the impact of data to contribute to positive outcomes.  

The COVID-19 pandemic has been a perfect example of leveraging data and increasing the value.  Never before have so many scientists and health experts gathered so much data and shared it so quickly to be able to hasten the response to COVID-19.  The ability to rapidly develop vaccines was due to the rapid sharing of the virus genome.  The ability to rapidly enact social measures to limit spread was due to the ability to gather and share infection data and trend analysis.  As it seems that COVID-19 mutates and evolves quite rapidly - this ability to gather, analyse and share data will be essential in the ongoing management of the public health response over time.  

What are the key success factors that made the pandemic response so effective;

• data was gathered quickly
• data was shared in repositories that made it easy to access, download and use
• data was shared in open formats that allowed ease of use in different analytical packages and processes
• analysis results were also shared in open repositories for use by others
• data analytical processes were also shared in open repositories and the analytical methods were easily copied and replicated for use with local data

All these open data approaches continues to contribute to an enhanced ability to make data informed decisions and contribute to data driven impact.  

Imagine if we took the same open data approaches and applied them to the data we use every day in our organizations and with stakeholders.  The value of our outputs and the value of our impact would increase tremendously.  What's stopping you from sharing your data?

Let me know how you use these key success factors in the comments below, and any additional key success factors you have observed.  

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Feel free to contact me by email or follow me on LinkedIn.  For further information on data driven impact and data driven government, visit my website at www.datadrivengovernment.ca.

Driving Data Driven Decisions

So in the spirit of transparency; I snore.  Apparently, I have snored for a long time.  My snoring was the cause of some deep relationship issues in previous lives!  About 20 years ago I went to a sleep lab and started using a CPAP (continuous positive airway pressure) machine that keeps my throat open as I sleep and lowers the incidence of snoring and related medical side effects tremendously.  It has improved my personal relationships remarkably as well.  A positive impact any way you look at it!

Recently, I came to the conclusion that I need a new sleep machine.  Mine is now over 5 years old and the progress in sleep technology is amazing.  About a week ago I called my sleep machine provider and we met to review my needs.  The Ontario Government provides grants to offset the cost of these machines, but I need a prescription from the sleep lab to get a new machine.  

In the past, I would have had to book an overnight visit to the sleep clinic where they would monitor my sleep through several dozen electrodes and provide me with a diagnosis on my sleep patterns and behaviour.  It often took several months to get an appointment. With COVID there are no overnight sleep tests being done.  Instead they are using advance digital technology. This is where the data part comes in.

It seems that the current generation of sleep machines now have "smart" technology. The CPAP units now have a built in microchip that tracks your sleep patterns, an ability to automatically monitor and adjust air pressures and have a wireless cell phone chip to allow remote access to the data.  The machine has sufficient onboard memory to record your sleep data over multiple nights. 

To get my new sleep machine, I will be loaned one of these "smart" CPAP machines, use it for two weeks, have the data remotely accessed, analysed by the sleep lab and a prescription given for a new upgraded machine.  In other words, the prescription decision is being driven by remote data gathering without the need for an inconvenient overnight lab visit.  Furthermore, that data is aggregated into longitudinal studies on sleep patterns experienced by patients over time, contributing to better diagnosis and better health outcomes. 

The lesson here is that processes that used to take high levels of dedicated infrastructure and personal inconvenience, have been completely transformed through data and digital technology.  The ability to contribute to better health outcomes at the individual patient level has major implications for enhancing health in general.  How many processes do we interact with on a daily basis that could be enhanced through data collection and analysis that would contribute to more positive impacts?  What processes are we working with today that we need to examine and improve with data driven decisions?  

Next steps: look around your world and find three areas in your life and work that could benefit from better data analytics and contribute to better decisions and impact. 

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Feel free to contact me by email or follow me on LinkedIn.  For further information on data driven impact and data driven government, visit my website at www.datadrivengovernment.ca.

The Nature of Measurement

Curiosity 

I have always been curious.  If curiosity killed the cat - I have been dead a long time! I now think that curiosity is linked to a desire to learn and I have been a proud life long learner.  It was with some excitement that a few months ago I signed up for Curiosity Stream as part of my Prime firestick subscription. Curiosity Stream is an online streaming service that specializes in documentaries from around the world.  This past week I was watching a BBC commissioned series on the history of measurement called Precision: The Measure of All Things.  It is a fascinating three part series on how we have developed greater precision in our core measurements and the tremendous impact such increasing precision has had on economic and social development. At one point the host says; "Without measurement, there is chaos."  It stopped me cold and may become the motto of this blog.  

Without measurement there is chaos.

What is so incredible about this thought is how true it is.  We need standards of measurement in all facets of life to be able to guide our activities, produce consistent outputs and contribute to outcomes that have impact.  Imagine trying to follow a recipe if we did not have standard measurements?  The recipe would not come out at all if we don't have consistent and standard messages. 

In Chaos there is Measurement

I shared this measurement quote with a colleague, who is a specialist in public sector performance measurement reporting, to get the reply; "In government it is the opposite: in chaos there is measurement!" How true in so many cases.  In the public sector we use a plethora of measurements to report on what we do.  Government is expected to be accountable and transparent - yet the measurement systems we use are anything but.  When we go to evaluate government programs and policies, how often does the report read that there is insufficient evidence or data to support any conclusions about the effectiveness or efficiency of an initiative?

Data, data where's the data?

The fact is that government is awash in data - it exists everywhere and is growing at an exponential rate. Government lags other sectors in the economy in understanding and analysing that data. Furthermore, because analysing data is sometimes hard to do, we tend to focus on analysing the data that is readily available and hope that will suffice.  Government is amazingly good at measuring outputs - the stuff we produce - but has greater difficulty measuring the impact on society and stakeholders an intervention is designed to achieve.  We need to do a better job and move from "in chaos there is measurement" to mastering the chaos through effective measurement and data analytics.

Feel free to contact me by email or follow me on LinkedIn.

Challenge 1: Data is Hard To Find

 Ever had one of those days....

The other day I was looking for a report that had impressed me about a year ago.  I knew that I had downloaded it and kept it but I wasn't sure where to find it. I ended up doing searches through my computer hard drive, my external hard drive and my cloud storage.  I found it after about 10 minutes of work, but the experience reminded me of some statistics I have read about how much time employees spend looking for data. More recently the increasing use of datasets on cloud storage has created a whole new level of data access challenges.  I recently discovered that my data analytics tool could not connect to a Databricks cloud storage because the enterprise VPN would not let the connection go through.  I had to disconnect from the VPN and then connect to the data store through plain Internet.

This comes from a 2019 Forbes article: 

Numerous studies of "knowledge worker" productivity have shown that we spend too much time gathering information instead of analyzing it. In 2001, IDC published its venerable white paper, "The High Cost of Not Finding Information," noting that knowledge workers were spending two and a half hours a day searching for information.

Since then, we have seen the rise of the cloud, ubiquitous computing, connectivity and everything else that was science fiction when we were kids becoming a reality — including the imminent emergence of AI. Yet in 2012, a decade after the IDC report, a study conducted by McKinsey found that knowledge workers still spend 19% of their time searching for and gathering information, and a 2018 IDC study found that "data professionals are losing 50% of their time every week" — 30% searching for, governing and preparing data plus 20% duplicating work.

If approximately twenty percent of time our working time is spent searching for and gathering information that translates into one day out of five.  If you sum up the total compensation cost for your organization and take 20% of that total - that is the financial investment you (and your organization) are making to find and discover information. We need to do better than that.  

The causes for this include data silos - data being held by one office or individual with limited access by others.  Other causes are lack of integrated data inventories - we don't even know what we have so we cannot find it. Multiple data stores where we may have different information in different places.  Difficult to use document management systems.  It is great to have an enterprise document management system, but if the user interface and the document storage structure is too complicated - it takes forever to find a relevant document. Cloud data adds a whole other level of data silos. 

So what's the solution? Here are some things we can do:

1. Recognize that we have a data silo issue.
2. Evaluate the cost of finding data - check with your team members on their experiences in locating data. 
3. Identify the key data bottlenecks - where is it the hardest to find and retrieve data.
4. What data governance issues like metadata, data inventories, search tools are necessary to resolve the bottleneck?
5. Do it, fix it, try it:  change something, have a test or trial to see what works and then deploy. Often it is a small change that can make a big difference. 

Ultimately, data is one of our most strategic assets.  Helping our teams and analysts get to the data and documents they need quicker is going to help everyone do their job better.  We can do this!  Ultimately the fixes are not technical - often they are about better use of what we already have. 

What has been your experience in data bottlenecks and data silos?  What solutions have you seen work?  Feel free to share best practices in the comment section.

Feel free to contact me or connect with me on LinkedIn if you want more information on solutions and options. 

The Importance of Impact

Photo by Nadir sYzYgY on Unsplash

Impact is the recognition that our activities contribute to some enhancement of the community and the world around us. As humans, and within our organizations, there is a fundamental desire to make things "better".  We want to make a difference from our contribution to the world around us; at home, work and in the communities we belong to.  While getting paid is important - the ability to see that what we do contributes to the greater team effort is an important motivator.  

When I was in business school we talked a lot about the difference between efficient and effective.  Efficient was doing things right.  Effective was doing the right things.  Impact is all about doing the right things well.  Results-Based Management uses a tool called a Logic Model that articulates the effectiveness and efficiency connection really well.  The logic model is a hierarchy that takes Resources (people, money, data, etc.) and converts those resources into Outputs through Activities.  The outputs have a technical name; we call it "stuff".  That stuff contributes to Outcomes or Expected Results.  A Logic Model can have several levels of Expected Results.  

Efficiency is the capacity to convert resources, through activities, into outputs/stuff.  The better able we are to do that - the more efficient we are.  That being said effectiveness is more important.  It doesn't matter how efficient we are if we are not being effective! The Logic Model gives us the ability to understand both of those dimensions and how they connect. 

Impact is the correlation between our planned expected results and what we actually realize. Impact is a journey, not a destination.  Impact can happen at the personal, professional and organizational level. The role of data driven impact is the ability to use data to inform our capacity to be both efficient and effective. Data driven impact uses key metrics that help give us the insights we need to understand our impact. We need data to provide the feedback evidence to make informed decisions on our next steps, our strategy and activities.  We need data to help us understand our world. 

The good news is that there is data all around us and it is growing at an ever increasing pace.  The other good news is that there are now software and data analytical tools that allow virtually anyone to utilize that data without being a computer or data scientist.  The democratization of data is upon us.  On other words, all of us can experience data driven impact.