Powering transformations with real-time data

Powering transformations with real-time data

How much of your company’s resources are spent searching for answers to day-to-day operational issues and writing reports, looking inwards rather than focusing on your customers’ needs? While technology has dramatically changed our world in many ways, the way organizations work has not always kept pace.

This was illustrated in one study conducted by Boston Consulting Group (BCG) in 2018, which determined that over 60 years the complexity within organizations had risen at a rate nearly six times faster than the complexity of the business environment in which the organizations operated [1]. When the world around you is changing at a rate faster than your own businesses, it’s no wonder that customers turn to more nimble competitors.

During my time as president of Aisin World Corporation of America, I saw this dynamic firsthand. Economic and marketplace challenges, supply chain disruptions caused by disasters such as the 2011 Japanese earthquake and tsunami, regulatory changes, multiple initiatives to grow the company, and our own desire to continuously improve drove the need for better answers faster. Despite improvements in technology and the vast wealth of data that Aisin had accumulated, we still relied on people manually searching for data and writing reports. Our own complexity was creating an inertia that did not allow us to react quickly to changes in the world around us.

This is a pattern I see repeating itself in many organizations I talk to. With cloud technology and its ability to consume, process, and visualize data now ubiquitous, why do so many organizations continue to lose the struggle to keep up with the pace of change demanded of them?

Well, change is difficult. Changing long-established operational methods and company cultures can be particularly painful as it requires more than a directive from the CEO or a new mission statement. Mechanisms that support change are key to making change possible. Many of the changes I have lived through started with improving the use of data. Increasing people’s confidence and skills in using data and then steadily improving the ability to use real-time data to drive real-time action helps facilitate innovation by creating a higher level of situational clarity. Knowing what happened in the past is key to understanding why it happened, what will happen in the future, and how to change this outcome. However, from a people perspective, knowing what is happening right now can drive more immediate action and better decisions. Creating broad visibility of real-time data has many benefits including democratized decision-making based on the objective use of data, reduced time searching for answers, and the ability to drive decisions down into the organization with confidence that decisions were being made the right way. Making real-time data broadly available throughout an organization can also stimulate meaningful, and in many cases heated, discussions crossing divisional or other organizational lines, helping break down those siloes that so often slow down decision-making.  Doing this can stimulate what I like to call an organic intercompany peer review.

In academia, the peer review process is used to assess the validity of research by having multiple knowledgeable reviewers provide feedback and challenge assumptions. In the business setting, a peer review process based on the same data can help cross-functional collaboration by creating a common understanding of opportunities across departments. Doing this with real-time data prompts more immediate action than waiting for quarterly or monthly reporting meetings. It can positively disrupt the status quo by getting people to stop and ask not just themselves but their peers the important question of “why?” at a point where meaningful action can be taken.

The automotive world relies heavily on the Toyota Production System (TPS), as I’ve seen during my long career in that world. One key tenet of TPS is that each process and its link to the subsequent process is constantly monitored to ensure the highest levels of manufacturability, efficiency, and quality in order to produce the best overall end result. In the office environment though, these links between functions are often ignored, with individuals focused on perfecting their own process. Consolidated reporting is most often only viewed by upper management and less often shared back to those who are in the best position to do something with the information.

In my experience, this cross-functional visibility of real-time data coupled with the peer review process drove not just speed of decision-making but also data quality and accuracy. This came about as people learned more about how their contribution and their department’s data impacted the business on a broader scale than they were previously aware of.

Opening up real-time data to all employees, rather than just leadership, promotes broader awareness and discussion about improvements that can be made against KPIs at a higher frequency, accelerating the feedback cycle, which is key to enhancing efficiency, breaking down barriers, and promoting transformation.

Getting started

I found one of the simplest ways to get started is by creating space for people to adapt to the desired changes. To do this, aim to automate reporting that is today done manually. Eliminating repetitive reporting will free up individuals to focus on understanding and using data rather than creating reports.

This is more than a technology project though. While the technology to automate reporting has existed for years, the corporate culture and individuals within an organization can often resist changes to how they operate. I know from my own past that this was difficult to overcome. I was conditioned to receiving and making reports, and through these reports show my value. Many within my organization expressed the same concern.

I overcame this by engaging in a learning journey, allowing myself and those around me to see how their roles could be enriched, rather than diminished, through automation. Over time we saw the benefit of having real-time data for faster decisions, which in turn increased our individual capabilities and ability to collaborate and cooperate better.

Capitalize on this opportunity by also reevaluating your KPIs and your reporting in general. Like me, you may discover that many reports are no longer pertinent to your current business, often generated only because of past needs that have been deprecated or met in other ways. Review each process, its purpose, and the reports and data used or generated by the process to understand how steps can be removed, or even whole processes eliminated, if they no longer support a valuable company workflow. Consider where manual data inputs or interventions are needed and how these can be simplified or eliminated. Manual steps can be one of the most difficult areas to identify and overcome when automating processes due to the lack of documentation.

Consider too how the resulting data is distributed and made visible. There are many dashboarding tools available that can be implemented rapidly to great effect. However, I have one note of caution: avoid falling into the trap of thinking that the creation of the dashboards is the end goal. The ultimate goal is to turn the dashboard’s data into quick action. Investing in training, communication, and monitoring of the use of the data are critical activities to ensure the ongoing relevance of the data, how it is presented, and to whom.

Bring data together

I found that setting up a data lake on the AWS Cloud allowed me to rapidly turn my goals of automation and real-time data into reality. It gave my organization the building blocks to quickly implement a secure, flexible, and cost-effective centralized data store. Doing so has become even more straightforward since the release of AWS Lake Formation in 2019, enabling the creation of a secure data lake in days rather than months.

Even prior to this, the process was so simple—and that’s what led me to make a critical error in judgment. In my desire to create a real-time data-based “people transformation” as president at a previous company, I was frustrated with what I perceived to be an IT department that was blocking the company’s ability to influence. I saw an opportunity to make what was traditionally innovation gate-kept by IT more accessible to non-technical individuals in the lines of businesses. What a great opportunity to bypass IT! I quickly realized my error in judgment. While we were able to make some progress, we came to recognize some of the challenges that the IT team were uniquely positioned to overcome to enable a sustainable level of innovation and agility.

In my AWS role, I often see the opposite error being made within organizations where responsibility for transforming an organization is placed solely on the IT department. Transformation is a company-wide responsibility; the Cloud and the ability to provide real-time data to all are enablers, as is having shared business outcomes. Transformation needs to be treated as an ongoing effort, not a one-time project. As your real-time data transformation progresses, your need to iterate and innovate based on peer review means many across your organization must be involved and brought into the change.

John Clark

[1] Morieux, Yves. 2018. ‘Bringing Managers Back to Work’. BCG

Other recent blogs from Enterprise Strategists containing powerful insights that I wish I had when I was leading a company transformation and think will be helpful in your cloud journey :

Learners lead, leaders learn: The case for technology fluency in the C-Suite

Measuring the Success of Your Transformation

Tracking the Effectiveness of Cloud Adoption

A guide to making your AI vision a reality

Taking Pole Position in Your Industry: Agility in Formula One

Executives as Pilots