Planning has long been one of the cornerstones of management. At the beginning of the 20th century, Henri Fayol defined the work of managers as planning, organizing, directing, coordinating and controlling. The ability and willingness of managers to plan developed throughout the century. Management by Objectives (DPO) became the height of business craze in the late 1950s. The world seemed predictable. The future could be planned. So it seemed sensible for managers to identify their goals. They could then focus on managing to achieve those goals.
It was the capitalist equivalent of the five-year plans of the communist system. In fact, a management theorist from the 1960s suggested that the best-run organizations in the world were the Standard Oil Company of New Jersey, the Roman Catholic Church, and the Communist Party. The belief was that if the future was mapped out, it would happen.
Later, the MBO evolved into strategic planning. The companies created large corporate units dedicated to this. They were deliberately detached from the day-to-day reality of the company and emphasized formal procedures around numbers. Henry Mintzberg defined strategic planning as “a formalized system to codify, develop, and operationalize the strategies that companies already have.” The fundamental belief remained that the future could be largely predicted.
Now, strategic planning has fallen out of favor. In the face of incessant technological change, disruptive forces in one sector after another, global competition, etc., planning seems like a meaningless illusion.
And yet planning is clearly essential for any business of any size. Look at your own organization. Having a workplace equipped for it, and having you and your colleagues work on a specific project at a specific time and place, requires some planning. The reality is that you have to make plans about the use of a company’s resources all the time. Some are short-term, others extend into an imagined future.
Universally valuable but desperately old-fashioned, planning waits like an old maid in a Jane Austen novel for someone to recognize its worth.
But executives are wary of planning because they find it rigid, slow, and bureaucratic. Fayol’s legacy persists. A 2016 HBR Analytics survey of 385 executives revealed that most executives were frustrated with planning because they believed speed was important and that plans changed frequently anyway. Why go through a slow and painful planning exercise if you won’t even stick to the plan?
The frustrations with current planning practices intersect with another fundamental management trend: organizational agility. Reorganization around small, self-managed teams – enhanced by agility methods like Scrum and LeSS – is emerging as the route to the organizational agility needed to compete in the changing business reality. One of the key principles underpinning team-based agility is that teams autonomously decide their priorities and where to allocate their own resources.
The logic of long-term centralized strategic planning (done once a year at a fixed time) is the antithesis of an organization redesigned around teams defining their own priorities and assigning resources on a weekly basis.
But if planning and agility are necessary, organizations have to make them work. They have to create a Venn diagram with planning on one side, agility on the other, and a practical and workable sweet spot in the middle. Therefore, the search for a rethinking of strategic planning has never been more urgent and critical. Planning in the style of the 21st century must be reconceived as agile planning.
Agile planning has a number of characteristics:
- Frameworks and tools capable of facing a future that will be different
- The ability to cope with more frequent and dynamic changes
- The need to invest quality time for a true strategic conversation rather than just a numbers game;
- Availability of resources and funds in a flexible way for the opportunities that arise.
The intersection of planning with organizational agility generates two other overriding requirements:
A process capable of coordinating and aligning with agile teams
Agile organizations face the challenge of managing local squad autonomy (bottom-up input) consistent with a broader vision represented by tribe goals and interdependencies between tribes and communities.
strategic priorities of the organization (top-down vision). Controlling this tension requires new planning and coordination processes and routines.
Consider the Dutch financial services company ING Bank. It restructured its operations in the Netherlands by reorganizing 3,500 employees into agile squads. These are autonomous multidisciplinary teams (up to nine people per team) capable of defining their work and making business decisions quickly and flexibly. Squads are organized into a Tribe (of no more than 150 people), a set of squads working in related areas.
ING Bank revised its process and introduced routine meetings and formats to create alignment between and within tribes. Each tribe produces a QBR (Quarterly Business Review), a six-page document outlining priorities, objectives and key results at the tribe level. It is then discussed in a large alignment meeting (called the QBR Marketplace) attended by tribal leaders and other relevant leaders. This meeting addresses a fundamental question: when we add everything together, does this contribute to the strategic objectives of our company?
The alignment within a tribe occurs in what is called a Portfolio Market event: representatives of each of the squads that make up the tribe meet to agree on how the set objectives will be achieved and to address opportunities for synergies.
The ING Bank example shows how the planning process is still necessary and essential for an agile company, albeit in a different way, with different processes, mechanisms and routines.
As more and more companies transform into agile organizations, agile planning is likely to become the new normal to replace the traditional central planning approach.
A process that uses both unlimited hard data and human judgment
Traditionally, planners have been obsessed with collecting hard data about their industry, their markets, and their competitors. Soft data – networks of contacts, conversations with customers, suppliers and employees, use of intuition and the vine – have been practically ignored.
Starting in the 1960s, planning was built around analysis. Now, thanks to Big Data, the ability to generate data is practically unlimited. This does not necessarily allow us to create better plans for the future.
Soft data is also vital. “Although hard data can inform the intellect, it is to a large extent the soft data that generates wisdom. They can be difficult to ‘analyze’, but they are indispensable for synthesis, the key to developing strategy,” says Henry Mintzberg .
Businesses need to imagine the possibilities first, and choose the one with the most compelling argument second. To decide which is the most convincing argument, they must take into account all the data that can be obtained. But, in addition, they must use qualitative judgment.
In an agile organization, teams use design thinking and other exploratory techniques (in addition to data) to make quick decisions and change course on a weekly basis. Decision-making is carried out by a team of people, thus compensating for the possible biases of a single person who makes a decision based on their individual judgment. To some extent, an agile team-based organization allows the ability to leverage qualitative data and judgment – combined today with infinite hard data – to make better decisions.
Relying solely on hard data has undoubtedly killed many would-be large companies. Take Nespresso, the pioneer of coffee pods developed by Nestlé. Nespresso took off when it stopped heading to offices and started marketing to homes. There was little data on how households would respond to the concept, and available information suggested a consumer perceived value of just 25 Swiss cents, compared to a company-required threshold of 40 cents. The Nespresso team had to skillfully interpret the data to present a better case to top management. Because he firmly believed in the idea, he forced the company to take a higher risk than usual. If Nestlé had been guided solely by quantitative market research, the concept would never have taken off.
The traditional approach to planning needs to be revised to better serve the purposes of the agile business of the 21st century. Agile planning is the future of planning. This new approach will require two fundamental elements. First, replace the traditional obsession with hard data and the numbers game with a more balanced coexistence of hard and soft data in which judgment also plays an important role. Second, the introduction of new mechanisms and routines that ensure alignment between the hundreds of self-organized local autonomous teams and the general objectives and directions of the company.
January 2021
Ariel Gonzalez Guerrero
The pandemic caused by the COVID19 virus surprised us all, both human beings and business organizations.
COVID19 and its aftermath, becomes a fact not contemplated or planned within the plans of the organizations, which forced in a short term, most companies to close their doors to the public and their employees to stay in their houses.
At the beginning of the pandemic, the impact of the pandemic began to be distinguished based on the business turns of the companies. A large part of the companies had to completely cease operations, another part was partially operating and a minority were fully operating. The sectors related to health, food, security, public services, technology, among others, were within that minority.
From the confinement measures, a stage of accelerated digital adoption / transformation begins both by companies and by most human beings.
As for organizations, those that were in areas that allowed to operate, strengthened or developed digital media to maintain their services. Assistance centers (call centers), online services, home deliveries, collection services at the establishment (pick up) were enabled, the use of software hosted in the Cloud (cloud) was increased, among other aspects . While probably everything that was done or strengthened was in development plans, it is no less true that as a result of the pandemic they became a priority and to be carried out in the short term.
As far as people are concerned, the vast majority have experienced an accelerated digital upgrade as well. Let’s exclude those who live with digital services in their day-to-day lives. This huge strip of the population has had to use digital tools for their daily work, family and personal tasks.
At the work level and if it is within the group that could operate, they went on to “work at home or work remotely.” To achieve this, connectivity tools and internet services were needed, and prominent players such as virtual conference tools (Zoom, Google Meet, Skype, Microsoft Teams, among others) appear.
The consulting firm McKinsey expressed in the middle of the pandemic. “Companies that make the right investments now could build a lasting advantage in serving customers and employees.”
On a family and personal level, he did not escape this reality. Purchase services in supermarkets for home delivery, mini markets, pharmacies, retail stores, hardware stores, among others, promoted digital media.
With regard to education, it has been one of the areas with the greatest impact; Virtual education systems and (LMS, Learning Management Systems) had to be implemented in an accelerated manner. A challenge not only for students but for all educational centers. Unexpectedly the system or teaching medium changed.
This accelerated digitization not only had an impact on work and educational aspects, but on interpersonal relationships. With the spread of the pandemic and confinement, there was a need to share with friends and family and the only existing way was virtual communication or conference tools. The majority of the family nucleus, regardless of age or social status, began to use Whatasap and ZOOM mainly for their family and personal gatherings.
“The term ZOOM practically became a generic one for virtual meetings.”
From the human liberation of the Pandemic, what will remain?
There is a great desire to return to the normal routine of life. However, during this period many lessons have been had and we understand that from the point of view of digital services, several of the aspects that we carry out today will remain post COVID19.
On a social and family level:
a) Services using digital platforms will continue to grow. There is no turning back. Now it will be a constant to incorporate innovations to these services.
b) The processes of sanitation and personal and environmental protection will be maintained. It has been seen how viral processes other than COVID19 have decreased as a result of the protection that we have had to implement.
At the business level:
Many of the changes that have occurred will remain.
a) Working from home or remote work will already become a viable option for many organizations. Of course, it will depend on the conditions of each employee. Starting from normality, the option of working at home is incorporated without this representing a lost day or leave. Even being in the country or out of the country.
b) The meetings will have radical changes. Most of the meetings will be held virtually, not because of distancing issues but because of their productivity; and only those of greater importance will be carried out in person.
c) Innovation in digital services will have to maintain the same pace as of post COVID19. There is already a more demanding consumer market, more informed and with greater command of technological tools. This market will demand agile and quality digital services.
d) It was possible to recognize that there are many similar needs and problems in all countries. Now with digital services the global market has narrowed even more. The offer should no longer be for local markets but global markets.
In summary, this year of confinement and global health crisis has led to an accelerated process of changes, fundamentally in digital services. Possibly changes and knowledge that were going to require 5 to 10 years have had to be acquired in a single year. COVID19, with all its negative and sad sequel, has abruptly pushed digital services for the benefit of society.
By Maria Korolov
August 04, 2020
Encouraging employees to learn data can benefit any business. Read on for some of the benefits and resources that can be leveraged in building those skills.
Research shows that data-driven organizations are more successful, but employees often lack the skills to handle data.
According to a 2020 survey by Sapio Research, 80% of decision makers considered that opening access to data has a positive impact on their organizations and 74% said that employees have access to data what do you need. But 53% of those surveyed reported employee reluctance to use the data.
Meanwhile, research has consistently shown that data-driven businesses are more successful. A 2019 survey by McKinsey & Company, a management consulting firm, found that companies in which employees consistently use data in decision-making are 1.5 times more likely to report growth in revenue. income of more than 10% in the last three years.
The difference comes down to data literacy.
“It’s crucial in today’s world where data is ubiquitous,” said Shreeni Srinivasan, director of business analytics and application delivery at Sungard Availability Services. “Data literacy can empower employees to make fact-based analytical decisions that are more grounded in reality than those made by instinct or intuition.”
According to the same McKinsey & Company survey, the proportion of executives in high-performing organizations who understand data concepts is 44% higher, the proportion of managers who understand data is 39% higher, and the number of employees in first line that comprise the data is 12% higher than that of other surveyed companies.
However, there are significant obstacles to understanding the data.
According to Gartner, 50% of organizations lack sufficient knowledge
on data to achieve business value, and 35% of CIOs said
that the lack of knowledge about data is one of the main obstacles to the
effective use of data and analysis, right behind cultural challenges and lack of
resources and financing.
What is data literacy?
Data literacy is the ability to write and understand data in a way similar to how we view literacy with reading. This may include understanding where the data comes from, communicating the information derived from the data to others, and knowing where to use different analytical tools and methods.
“When companies have more data-savvy employees, they understand that data is no longer just the domain of the data team,” said Andrew Stewardson, data manager for Farm Credit Services of America, a provider of credit to farm operators. and ranches based in Omaha, Neb. “Having a higher level of knowledge of the data means that we can better serve our customers.”
Stewardson’s organization took an unusual approach to data literacy training by creating an internal person, Walt, to answer data-related questions from employees.
“The key to fostering the data literacy training was getting Walt to connect with various people within the organization,” said Michael Meyer, data engineer for Farm Credit Services of America. “We also created a blog where users could ask questions about everything related to data.”
That took the pressure off data teams to drive change, he added.
“Simply putting data in the hands of individuals in an organization does not automatically increase knowledge of the data and build an organization on it,” Stewardson said.
In fact, launching data projects without paying attention to data literacy can be a costly mistake. “
For example, Penny Wand, chief technology officer for West Monroe Partners, a Chicago-based technology and management consulting firm, was working on a project for a manufacturing company to deploy pricing strategy analysis.
“People just rejected it,” he said. “They didn’t understand the results.”
The project was a failure, and the company not only wasted the time and money it spent creating the analysis, it also lost millions of dollars in missed opportunities, Wand said.
“It cost them money because they couldn’t optimize their pricing strategy,” she said.
“They lost money by not being able to put into practice what they learned from the data.”
Many people have been out of school for a long time, and their math and data analysis skills are not on a level playing field, Wand said. And this not only hurts basic analysis projects.
“Forget AI, without a certain level of knowledge of the data, it’s not going to get there”,
said.
Who is responsible for data literacy education?
Unfortunately, there aren’t currently many best practices and guidelines to follow when it comes to teaching employees in data literacy, Wand said.
“We are in the infancy of formal data literacy programs,” he said.
One approach is to make education specific to the role the employee has in the organization, he said. That is what Coursera is doing with its Academy of Data Science. Another approach is to get education to people as they need it, as they are using their data tools, rather than a formal training program.
Then there is the challenge of measuring success.
Many companies are tackling the challenge of data literacy by moving data scientists out of data science departments and into business units where they work closely with end users, said Bryan Coker, senior data and analytics consultant at AIM Consulting Group, a Seattle-based management consultancy.
“I think that’s a trend almost everywhere,” he said.
Another approach is to provide specific, hands-on workshops for employees, focusing on the specific analytical tools used in the business and the specific business challenges around data that the business and its employees face.
These workshops can be led by tool vendors or independent consultants, said Justin Richie, director of information science for Nerdery, a technology consultancy.
“I firmly believe that people learn best by doing,” Richie said. “So having the ability to get your hands on a keyboard or laptop and do something is about creating that contextual awareness of doing it yourself. It’s better than sitting in a college-sized auditorium and listening to someone speak for eight hours.”
Or, these days, the equivalent of the Zoom, he added.
How can companies promote literacy of data?
Not everyone wants to run off to learn math.
“That would be a good day at work for me, just taking math classes,” said Jeff Herman, a data science instructor at the Flatiron School in New York.
Other employees may need some support.
In Herman’s previous job at a railroad company, data scientists led training sessions for other employees on data and how to use it to do their jobs better.
“We were talking about basic statistics,” he said. “We were talking about different databases:
Here’s a locomotive database, here’s where the trains go, here’s the finances, and here’s how to access the data. ”
Companies looking to do something similar should look for communication skills when hiring data scientists.
“People who can communicate with non-technical stakeholders and are comfortable conducting the training,” Herman said.
“Data literacy is not only a benefit for the company, but also for you. It will open more doors for you, it will make you more marketable. Jeff Herman Information Science Instructor, Flatiron School ”.
Flatiron School also has a free information science prep course in addition to its regular information science curriculum, he said. Khan Academy also offers many free courses that cover everything from basic statistics to data analysis.
But it’s not just about making training available, Herman said.
“Companies need to talk about what the benefit is for the employee,” he said. “It is not only a benefit for the company, but also for you. It will open more doors for you, it will make you more marketable.”
Plus, data literacy starts at the top, with the executive team.
“They have to be comfortable with the idea of making decisions based on the data,” Herman said.
Benefits of improving data knowledge
When the only people looking at the data are data scientists, important insights can be lost. For example, at the railroad company where Herman used to work, a key indicator was the downtime of the locomotive.
“We thought it was a waste of fuel,” Herman said.
But when other people in the company outside of the data analytics teams started using Power BI, they were able to see the same data from a different perspective.
“The people closest to the locomotive operations knew there were specific reasons why it sometimes had to idle,” he said. “They were able to make a dashboard for when a locomotive was idling, when it shouldn’t be, and focus on where we could really save fuel.”
Not surprisingly, in a recent Forrester Research survey, 90% of respondents and analytical decision makers saw increasing the use of data in business decision making as a priority.
But with only 48% of decisions based on quantitative information and analysis, there is plenty of room for improvement.
