Are CEOs Really Necessary Anymore?

StrategyDriven Editorial Perspective Article |CEOs|Are CEOs Really Necessary Anymore?It seems like a ridiculous question to ask, somewhat like wondering whether cars really need drivers. Just imagine all the things a driver does every second in order to reach a specific destination: taking in vast amounts of inputs about current conditions of the vehicle’s motion, receiving thousands of changing data points from all the visual clues about lanes, traffic, signs, pedestrians and all the other moving vehicles in the vicinity, then comparing all this information to a previously set route, and making all the complex choices necessary to arrive safely.

You could almost think about that driver as being on the receiving end of a firehose of data, sorting out the most important patterns, and then turning all of that into a best course of action — the very definition of Intelligence. And that’s why we’ve come so close to going from data that one human can process, to Big Data, which requires dozens of sensors to process.

With increasingly vast bodies of knowledge about experiences, one can see how business Intelligence, with enough computing power, became Artificial Intelligence. And, so, before too long, the taxi you’re about to hail in Phoenix, shows up; Poof! No driver necessary.

Which brings us back to those folks in the corporate driver’s seat — the CEO. Doesn’t much of a CEO’s job consist of being on the receiving end of ever-increasing floods of data that can now be gleaned in real time from inputs around the globe? The tick of every sale quickly contributes to a pattern revealing how the marketplace is receiving our products at every given moment. Supply chains are linked to these inputs, as is every other variable the CEO needs to be concerned about, from available corporate resources to stock price.

And as AI begins to make choices based on mining Big Data, the role of the CEO as patchcord between data input and decision output seems destined to become smaller and smaller until, at some point, an organization is going to run autonomously. As futurist Ray Kurzweil observed in 2005, in the near future, machine intelligence is going to exceed human intelligence. He named that moment, the Singularity. Will there be a moment when the Singularity arrives in the C-suite? It seems inevitable.

AI or Human Agency?

Or maybe not. Maybe great organizations are not really machines, like some automobiles or even spacecraft, that can complete their journeys without human intervention. To find out, it may be worthwhile to make some sharp distinctions between what Big Data driving AI can do, and what it cannot. BDAI (for short) is excellent at making sense out of the current state. It’s also pretty good at making predictions about trajectories, given no black swan or other -unforeseen circumstances. So BDAI is pretty useful for management to be able to see where we are and where we might be headed.

But, what about agency, or intentionality, or what today we generally call strategy? If we have enough past information of competitive successes and failures, BDAI is capable of helping leaders develop options. In some instances, in a large consumer products organization, for example, it is not difficult to imagine letting BDAI decide the optimal number of versions of a toothpaste brand, which will maximize performance in the marketplace, and even continue to optimize those decisions over time.

Yet, what happens when there is a genuine disruption in a marketplace, when new inventions shuffle the whole deck? If BDAI had been in place at Olympus Camera on the day that Steve Jobs introduced the iPhone, would the company’s management information system have warned leadership that the pocket camera industry, at that moment, was entering an irreversible swoon?

CEO’s Role- Wisdom and Innovation

Finally, we come to the two basic responsibilities that a CEO can perform that, as yet, BD and AI together cannot. The first is to make wise decisions over time that express a coherent vision. The second is to lead innovation. Famously, Steve Jobs had no interest in market research when imagining where Apple needed to go next. He thought in broad terms about what human beings might do with powerful new tools, and went about creating them. Sometimes, it took a while for people to get what Jobs was giving them, but eventually, he re-ordered the world.

Same for Elon Musk. Musk’s long arc in guiding Tesla from highly-ignored sports car, which financed the luxury Model S, which, in turn, made possible the 3, is now crushing an entire global industry. And, underneath it all, still not widely-perceived, is that Musk is also transforming the global electrical grid with a complete infrastructure of vast battery capacity.

Jobs, Musk and other disruptive founders built their organizations to maximize the value-creating potential of their visions. Those organizations are no less than the living, breathing manifestations of their founders’ identities and are as unique as the founders themselves.

After the Founder

Once the founders have departed, subsequent leaders, in order to maximize the quality of their decision-making, will always need to be aware of the identity that still pulses at the heart of their organizations. Without this essential understanding, the dangers are ever-present that the easy persuasiveness of Big Data, married to the seemingly incontrovertible direction supplied by Artificial Intelligence will, eventually, lead even the most successful organization astray.

So, are CEOs really necessary anymore? Yes, if they realize that their main job is to ensure that the identity of their institutions provides the center of gravity around which Big Data and AI are reliably deployed. Otherwise, companies are in peril of becoming driverless, autonomous vehicles, subject to an uncertain future fraught with potentially lethal hazards.

About the Author

StrategyDriven Expert Contributor | Gerald SindellGerald Sindell is a partner of The Identity Dynamics Institute. He was the CEO of two New York publishing companies, Tudor and Knightsbridge. He has been instrumental in developing enterprise operating systems for EOS Worldwide, Accenture, and The Balanced Scorecard Institute.

Today’s Battle for Data – in the Wind and the Cloud

StrategyDriven Organizational Performance Measures Article | Today’s Battle for Data - in the Wind and the Cloud | Big DataData is the new currency and often the point of strategic control in many industries. Companies are attempting to control data in order to monetize what the data can do for them. Take this example from windmill technology as an illustration:

Windmill technology has dramatically improved over the past few decades. For example, GE has developed blades and rotors that sense the wind direction and adjust a windmill’s tilt/shift in order to optimize its ability to catch the wind. In addition, many windmill “farms” optimize the way they work together since one windmill’s direction and tilt affects the downwind performance of all other windmills. Because a group of windmills operating together is more efficient than individual windmills operating separately, when one windmill fails, the efficiency of the entire farm can be adversely affected.

Industry leaders, including GE and Siemens, have developed their own optimization and monitoring services that use the data coming off the windmills to remotely monitor performance and proactively do repairs to maximize windmill uptime. However, the market for windmills is fragmented with a few large players and a series of smaller players — many of whom are lower-cost manufacturers from Asia and don’t have the scale and/or capabilities to develop and maintain such services.

In response to GE and Siemens’ control of this space, a few ingenious companies are in the process of installing – for free – sensors in both new and existing windmills. These sensors monitor motor vibration and temperature so that they can predict motor failure before it happens. The data are broadcast to the cloud in real time and predictive failure analytics are conducted on the data. Once a motor’s spec goes out of tolerance zones, a team is dispatched to repair the motor before it fails – not only to maximize the “up time” of the windmill, but also to provide peak efficiency for the entire farm.

This enables the smaller players to compete effectively with the larger firms. For example, for smaller Chinese manufacturers trying to compete with GE and Siemens, being able to provide this service is often the difference between making the sale and losing it.

So, how do you make money installing sensors for free? The key is owning exclusive access to the data generated via the sensors and leveraging it by selling higher-margin maintenance contracts back to windmill manufacturers (for newly built windmills) and to farm owners (for retrofitted, existing windmills).

The smaller players are more than willing to allow the sensors to be installed to grant access to the data and pay for higher margin maintenance since they can’t efficiently do this themselves (due to their size and scale). Meanwhile, they gain the ability to compete with the GE and Siemens of the world on services while simultaneously maintaining their cost advantages. In addition, they can eliminate downtime risk via offloading this to its sensor supplier. Therefore, it’s a win-win arrangement for both parties.

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Indeed, this is the modern-day equivalent of the “give away the razor and sell the razor blade” story. Today, the razor equivalent (the sensors) is only of value because of the system’s necessity to interoperate and the ability to monitor it remotely via the cloud and predict failure before it happens. In today’s world, it’s often beneficial to give away the hardware but own the data.

As you design a way to monetize your data-collection system, keep these key principals in mind:

  1. Benefit.The offering needs to provide a clear benefit to both you and your customer.
  2. Incentive.The giving away of the hardware to access the data can’t be for the purpose of simply selling the data to a third party. Rather, access to the data has to enable you to provide better service at a higher price point than rivals. Your unique access to the data makes it so that your customers want to buy from you since, even at a higher price point, you save them money, time and/or resources.
  3. Don’t negotiate the “back end” on the “front end.”In the windmill example, had sensor manufacturers attempted to require maintenance contracts before installing the sensors, they’d likely have received substantial pushback for anything that cost them more. However, once the sensors were in place, the added benefit or performance-based maintenance was clear.

About the Author

StrategyDriven Expert Contributor | Dr. William PutsisDr. William Putsis is a Professor of Marketing, Economics and Business Strategy at the University of North Carolina-Chapel Hill, and a Faculty Fellow for Executive Programs at Yale University. He is also president and CEO of Chestnut Hill Associates, a strategy consulting firm, and founder of the software company, CADEO Economics, which automates his data modeling-based strategy development processes. His new book is The Carrot and the Stick: Leveraging Strategic Control for Growth (Rotman-UTP Publishing, Feb. 3, 2020). Learn more at or

Stop Drowning In Data And Create An Optimisation Plan

StrategyDriven Organizational Performance Measures Article |Data Management|Stop Drowning In Data And Create An Optimisation Plan One thing is certain – Big data is big business. As the ways in which we can gather information have expanded almost infinitely, so the data we have stacks up and up. We’ve been promised the earth by understanding our customers better – enhanced profits, more repeat sales, higher average transaction values, loyal brand advocates. And while it’s true that data can deliver all of that, for most businesses, it doesn’t. Because data is a tool like any other, and when it’s misused or not used to its full potential, you’re not likely to see the results. Most businesses collect data without any clear idea of why they are collecting it, and their marketing strategy gets stifled under the sheer amount of available information. Instead of driving the data and mining it to find the relevant parts, it drives them. Learning how to effectively use data is highly individual to each company and their operations and KPIs, but there are some building blocks for good data hygiene and usage that work across all sectors and business types. So, how can you stop drowning in data and start using it to your advantage?

Closing The Feedback Loop

Often we believe that we should be coming up with a lot of colourful looking reports covered in pie charts and bar graphs that we can point to as concrete evidence of macro trends affecting our operations or changes in customer experience. But what do all those colourful reports actually show? Data in and of itself is literally just a bunch of numbers, and all the reporting you like isn’t going to make much of a difference to your bottom line. The most important output is actually the insights that only shrewd analysis can show, and this is the single most important function of the modern marketer. Seeing meanings, patterns and stories is the important part, not the raw data itself. Knowing what all these metrics mean for your business and what action should be taken is the only thing which makes data collection worthwhile.

Make Sure You Measure The Right Thing

The symbiosis between overarching business strategy and analytics can be a tough balance to get right, because both should feed off the other. What you measure should be dependent on what you want to optimise in line with the wider goals you have for your business. But equally, what your goals are should be at least partially dependant on the customer feedback that you amass through your data. Skew the balance too far one way or the other and it’s not going to work in your favour. Setting good metrics for your business is absolutely key to the success you’ll get. Look at things such as which channels drive the most conversions for your business, which landing pages on your website have the lowest conversion rates, what your average order value is in different segments of customers. Underpinning all of these metrics need to be two important things – a great CRM system which can allow you to use these insights to create dynamic marketing campaigns which really respond to individual customer preference and history, and a strict attention to data hygiene and legal practices. Ensure that you’re on the right side of the law when it comes to data collection and storage, and seek out advice from experienced professionals with a track record of legal matter management. The penalties and the damage to your professional reputation can be majorly severe if you get this wrong, so make it a matter of good practice.

Use Segmentation Effectively

Taking action on your data should all be driven by customer segmentation. Not only understanding your customers and their different backgrounds and preferences, but even allocating groups a persona to bring their journey to life and help you see how better to help them. Your knowledge of the goals set out in your business plan should guide which group of customers you look at first, but try to use the data you request to enhance your understanding of each group. This approach allows you to dig a lot deeper and come up with far more creative solutions.

Remember To Add Context

Data is never an island, and if you insist at looking at very narrow ranges of statistics in isolation, the picture that emerges is hopelessly skewed and will never give you an accurate base to work from. A better understanding of context can help you to make much more informed decisions. Make the connection between the figures you’re seeing and what they really mean for your business. Interpreting data badly can be very harmful to your operations and in many cases it would have been better not to collect it at all!

Pull Together Your Optimisation Plan

With the insights you have managed to gather, putting them into some form of actionable plan is the most important part. Six Sigma has a particularly useful concept which can be directly applied to using data insights in this way. The Define Measure Analyse Improve or DMAIC process can be very instrumental in shaping your approach. First, you define the problem that you are trying to solve, known as your hypothesis, set out your relevant stakeholders and the scope of your analysis. Then, you can measure the relevant data fields and use basic analysis to spot any anomalies. The third step is to analyse correlations and patterns within your data set using your visualisation skills to bring it to life. Improvement then corms from using these insights and coming up with a few options to explore. Finally, you control the change by using strategies like multivariate testing and monitoring KPIs to see the impact of what you’re doing. It’s then possible to make responsive adjustments in real time to ensure that your campaigns are fluid and provide a shifting technique to overcome any barriers and generate the best possible return on investment. With a little more careful planning the feeling of being overrun by statistics will be replaced by a focus on only the most relevant metrics to get you to where you need to be.

Using Big Data in the Classroom

StrategyDriven Organisational Performance Article | Big Data | Using Big Data in the ClassroomBusinesses the world over are leaping into the use of big data. The analysis of the vast amounts of consumer data is helping business to create more effective marketing strategies and streamline their business process. However, it’s not just businesses that are using this valuable tool. Big data is starting to make its presence felt in the classroom, and the results are proving to be worth it. As the next big step in the transformation of the modern classroom, technology is at the forefront, and big data could be the key to improving the education levels of a whole new generation. Here’s how.

Better Results

The real-time analysis of the performance of each individual student is now possible through data tracking. This enables teachers and educational centers to have a more accurate view of how well a student is performing. Traditionally, student performance has been judged according to the results of an exam or test, but this is not always effective. By highlighting the strengths and weaknesses of each student, it is now possible to create more effective and beneficial learning schedules, and even allow for better group work when complementary skill sets are combined. This can help improve a child’s learning skills, and create a more effective learning curve for every student in the classroom.

Reduce Drop Outs

There are an estimated 1.2 million high school dropouts in America every year. This is a huge issue for educators, and can have dramatic long-term effects on the future of every one of those children. Data analysis could be the key to tackling this issue. Modern software is able to use predictive analysis of data in order to create education programs that suit each student, and with college retention software it is possible to identify those students most at risk of dropping out. Many of the reasons for high school or college drop out can be tackled if they are identified early, which is why tech-savvy educational facilities are integrating these software models into their classroom management.

Education Customization

Blended learning, where students use a combination of online and offline resources, allows students to have much greater control over what they learn. For those with clear advantages in some areas, this allows them to tailor their lessons to their skill set. This is now possible even in large classes, with teachers able to oversee what students are doing in real time. By allowing students to work at their own pace and in areas that interest them, teachers are better able to tailor their offline lessons to those students that need extra help. This can not only help with student engagement, but it also means that those students who excel are not being held back by their peers. For those students that are slower to learn, customized lesson plans can help to keep them on a level playing field.

Data is being used by corporations and businesses in a wide variety of ways. As the full impact and potential of big data continues to expand, the classroom could end up being the most important user of data analysis, and the education of the next generation looks set to benefit from those changes.

Ways Data Analytics Can Boost Your Business’ Growth

Big data is here to stay, and although that can present a few challenges to business (storing it, keeping it safe, etc.), for the most part, it is a boon, which if used correctly can easily boost business growth.

If you’re still skeptical about the use of data analytics, take a look at these very real ways it they can boost business. They’ll have you convinced in no time:

It Can Improve Ordering

If you collect and analyze past sales data, you can identify trends in your company’s sales so that you can order exactly the right amount of stock for your needs. This will help to ensure that you don’t run out of anything, thus helping to keep the customer happy, and it will ensure that you don’t end up ordering too much and spending money on something that will just go to waste.

It Makes for Better Product Management

Analyzing sales data is also a good way to find out which of the thousands of products that you could be selling are the most popular so that you can stock more of the things that are likely to sell in big numbers and fewer things that are unlikely to make you very much money at all.

It Can Improve Your Marketing Strategy

If you’ve ever spent a small fortune on advertising only for it to fail and not bring in as many customers as you would like, there is a good chance that you simply were not targeting the right people or you had the right audience in mind, but you weren’t targeting them effectively. If you were to do what the digital marketing agency MyOptimind do, or even hire them, and use data to improve your marketing efforts, you would be able to spend less money and get greater returns because you would know exactly what pushes your target audience’s buttons.

It Can Help You Train Your Staff

If you collect data on your staff and how they work, then you can use it to identify undesirable patterns in their work or areas in which they aren’t as productive as their peers. Why is this important? Because once you know what your employees’ strengths and weaknesses are you can tailor future training packages to target them, thus saving you money while improving your business from the inside out.

It Can Help You Cut Costs Everywhere

Of course, if you collect data, with Zoho, for example, on every aspect of your business from ordering to time spent fielding calls, you could work out where your time is being well spent and where it is being wasted, as well as identifying where you’re spending too much money and by analysing this data, you would be able to make changes to save money and boost productivity.

You Can Find Upselling Opportunities

If you can use data to identify when certain products are bought in conjunction with others, you can start offering cross-promotions that are likely to appeal and which could be pretty lucrative over the years.

You see, data really is important – time to start collecting it!