Change is scary. But with a little risk, a lot of planning, and some extra effort comes an opportunity for growth and reward. That’s what makes change management so important.
As a manager, department head, or executive how do you know when it’s time for change? How do you invoke change within an organization, and how do you get others on board?
Studies in what’s known as change management have shown that there is no one single answer to what most influences and leads to successful transformation initiatives.
In recent years, change management strategies have focused on soft factors like culture, leadership, and motivation. Each of these play a key role in a successful transition. But, for change to truly take hold, it’s also important to focus on the hard factors like duration, integrity, commitment, and effort.
In this article, we’ll discuss the definition of change management, address corporate responsibility during the process, what you and your team need to do to be successful, and show you the best ways to implement transition skills and best practices into your organization and projects.
What is change management?
Change management is a big, daunting term, let alone task. It’s a rather condensed way of explaining the process when an organization takes on projects or initiatives to improve performance, address key issues, and seize new opportunities. These endeavors may require companies to shift their methodologies, roles, organizational structures, and perhaps even the types of and uses for technology.
Successful transitions dependent upon four core principles. These principles are important to understand before undertaking a large shift in processes or anything else, no matter what the context:
- Understanding change – Understand the questions that need to be asked, the why, and the “ins and outs” of the change.
- Planning change – This looks different for every organization, but can include achieving high-level sponsorship, identifying stakeholder involvement, and motivational techniques and establishing a team responsible for managing the change.
- Implementing change – Roll out the change, ensure everyone has been trained on the new process, technology, etc, knows what their role is and the importance they play in affecting change.
- Communicating change – Tools to help everyone understand why the change is happening, the positive effects that will come and the steps to required to ensure success.
Now, that’s just a brief overview. Here’s an in-depth review of these four principles, and how each of them help you work toward successfully-managed change in your organization.
Understanding change management, implementing best practices
Understanding change management begins by understanding its three important levels.
According to Prosci, a change management solution, the three levels are:
In this model, enterprise change management is therefore dependent on both successful individual change management and organizational change management. Each of these aspects build onto one another to enact lasting, ingrained change across your department, team, or organization.
Individual change management – This will require tapping into the mind of your employees. It requires understanding how people experience change and what they need to handle it successfully, and thrive post-implementation.
ADKAR is a great acronym created by Prosci founder Jeff Hiatt that represents the five tangible and concrete outcomes required for individual staff.
The acronym stands for:
A – Awareness of the need for change
D – Desire to support the change
K – Knowledge of how to change
A – Ability to demonstrate skill and behaviors
R – Reinforcement to make the change stick
For success at the individual level of change management, companies need to be able to communicate these five ADKAR elements to their employees in order for them to understand why the necessity of the change, where the change is coming from, how they can support the change, and how they will be impacted from it and the benefits the change represents.
Organizational change management – These are the steps and actions taken at a project level to support the individuals impacted by the ongoing change process. It starts by identifying the groups or people who will need to change, and in what ways. Once identified, successful organizational change management requires a customized plan for each individual to ensure that they receive the awareness, leadership, and training they need to be successful going forward.
Individual employees are at the center of successful change management processes; their success or failure will determine the success or failure of the processes that are changing organizationally.
Enterprise change management – This is the ‘final’ level of change management and essentially means that effective change management is embedded into your organization’s roles, structures, processes and leadership competencies. When it comes to enterprise change management, newly-implemented processes are consistently applied to initiatives, leaders will have the skills to guide their teams through the change, and staff will know what to ask for to be successful.
When embedded into your structure, enterprise change management capability means that individuals embrace change more effectively, and the organization itself is able to respond faster to market changes, embrace strategic initiatives, and adopt new technology much more rapidly.
Now that we’ve established the benefits and principles of managing change, how does it work, exactly?
Learn more about how MindBridge can help you sample less, and discover more.
How does change management work?
Change management relies on cohesive effort between management and employees to lead a successful transition. If leadership is not able to create a solid plan, and if employees are unable to “embrace and learn a new way of working, the initiative will fail.”
Take transitioning financial technologies and processes, for example. As technology improves and data sets increase, financial professionals and their departments are feeling the pressure to do more in less time. The trouble comes when the quality of work suffers as a result of the attempt to marry efficiency with quality. This is especially true of risk management and discovery.
Platforms like MindBridge help organizations discover the known and unknown risk in their financial data sets. They can analyze 100% of transactions, provide insights to better communicate analysis with stakeholders, and ultimately produce higher quality work in a fraction of the time.
But, all of this requires a solid, well-executed change management plan. While new technologies are increasingly turnkey, unlocking their full potential takes buy-in at all levels of an organization, and investment in the principles of change.
At MindBridge, we strive to enable our customers with the tools, resources, and support they need to successfully transition their financial processes. But, for the organizations themselves, there is still work to do.
When it comes to changing any process or technology, the status quo is always simpler. But, those who are truly committed to growth and the future of their organizations aren’t content with the easy way out.
By integrating proper change management in the deployment process, companies and departments will be able to get employees on board and involved in the process to ensure as smooth a transition as possible. There will be headaches, and you may be uncomfortable. But that’s how change management works. If it were easy, everyone would be successful.
How to plan for transition
To help plan for the transition process, Harvard Business Review discusses the hard factors that need to be discussed more (along with soft factors like culture, leadership and motivation) when implementing change management strategies. These factors allow companies to measure, communicate and influence elements quickly to affect transformation. Before they start, companies need to understand the time allotted to complete the change, the number of people required to execute it, and the financial results that intended actions are expected to achieve.
To help lead a successful change management operation, there are four specific factors companies can use to determine the outcome and create a path to success:
Duration – The length of time it will take until the change program is complete, and the length of time between reviews built to measure success
Integrity – The ability to select the best staff to lead the program. Look for problem solving skills, results & methodological oriented individuals
Commitment – The level of enthusiasm and resilence from both management and employees to affect this change
Effort – Calculate the amount of time and effort beyond existing responsibilities, resources that are over stretched may compromise the change program or normal operations.
For future transitions
Change management requires focus, organization, and motivation. Not everyone will be willing to accept and help to invoke this change at the same time. The source of resistance is often individuals or groups, but it can also be systems or processes that are outdated or that fail to fit current business conditions.
Ways to mitigate these obstacles include rewarding flexibility, creating role models for change and repeating the key messages and goals of the project throughout the entire change program.
This is where the message of the “bigger picture” becomes crucial, if employees feel separated from the goals they will question their motivations. But by showing the concrete benefits of change for them, their department, and the organization more largely, you can demonstrate how all this added effort will lead to gains in the future.
For more on creating an effective transition strategy, watch our webinar, Change management 101: Strategies for leading change when adopting AI.
For more articles and resources like this one, visit our blog.
Well, it’s finally here. According to an article from Forbes Magazine, we have reached the age of automation. From AI and machine learning to financial automation and robotics, we’re officially an automatic civilization. Please, be kind to our new robot co-workers.
Okay seriously, this is important stuff, even if we did all see it coming. Especially when it comes to the ever-expanding world of finance.
In every industry, every business, and every firm, finances and how they are managed are vital to the growth and development of a company. Whether you’re a business owner, CFO, or part of the finance department, the role of automation in the future of finance is vital to your role, growth, and the evolution of your organization.
Financial automation doesn’t just mean automating payroll, although it doesn’t hurt to do that as well. Automating financial processes incorporates much more, including risk assessment, audit, and compliance among many other aspects.
An article from DigitalistMag outlines the capabilities of today’s financial automation services, describing the ability to “gain new insights from existing data to optimize credit decisions and improve financial risk management, automating business processes that previously required manual human intervention, and improving the customer experience.”
Financial management has evolved rapidly since the advent of computational technology. As this technology evolved, financial experts and professionals soon recognized that process standardization and centralization are absolutely necessary to increase the efficiency and effectiveness of modern organizations. As efficiency grew into a central tenant of management processes, financial automation became the next logical step for businesses and organizations.
In 2016, McKinsey estimated that 60% of all occupations have approximately 30% or more capabilities that can be automated with existing technology. Moreover, there has been a significant change in the understanding of what can be automated and what should be automated, which has become increasingly evident due to the unprecedented effect the COVID-19 pandemic has had on work.
For businesses looking to hire and outsource their financial processes or professionals who want to simplify and streamline internal processes, it may be time to look at automating them instead. For many, this has already begun, as “CFOs around the world heavily invest in financial automation software as a next step in the evolution to enable enterprise transformation.”
In this way, financial automation could lead to a complex or fundamental shift in how an organization’s core business is conducted.
Taking the first step toward financial automation can seem daunting. However, with more businesses adopting automation into their day-to-day financial practices, it’s clear to see the power this technology holds.
So, what exactly is financial automation?
What is financial automation?
For us mere mortals, financial automation can be as simple as automatically depositing your paycheck, paying bills, or saving a portion of your income per month. The concept is similar for businesses and corporations, but at a much larger scale, and with a lot more moving parts.
Financial automation is the process of utilizing technology options to complete tasks with minimal human intervention. These tasks would normally be accomplished by employees, which, in theory, frees up time for them to perform more complex tasks.
According to another automation study from the McKinsey Global Institute’s automation research, current in-use technologies can fully automate 42 percent of finance activities and mostly automate a further 19 percent.
While many still consider financial automation and intelligent software to be on the horizon, organizations have already started to utilize cutting-edge tools and technologies such as advanced analytics, process automation, robo-advisors, and self-learning programs. A lot more is still yet to come as technologies evolve, become more widely available, and are put to innovative uses.
Levels of automation
The initial forms of automation were (and still are) macros and scripts: simple rules-based automation that repeated simple work with highly structured data – things like general accounting operations, revenue management, and cash disbursement have an over 75% fully automatable ability with already existing technologies.
Robotic process automation (RPA)
RPA is the basis (above macros and scripts) to understand the capabilities of automation. An example of an RPA would be simple software that can perform repetitive tasks quickly with minimal effort, like some of the rote tasks mentioned earlier.
According to the 2017 McKinsey research (also mentioned earlier), about a third of the opportunity in finance can be captured using basic task-automation technologies such as these.
Artificial intelligence (AI) and intelligent automation (IA)
On the other end of the spectrum is artificial intelligence. Artificial intelligence is theoretically achieved when software is able to make intelligent decisions while still complying with controls using algorithms or machine learning.
Machine learning algorithms demonstrate the ability for computers to take in a constant stream of data, analyze that data for patterns and recommend solutions to problems humans can’t even see, proving vastly positive results in improving a company’s financial proficiency.
Once a dream for financial professionals and business owners, this form of financial automation software is becoming a reality, shaking up the way that tasks are performed, and even introducing other aspects such as forecasting into the mix.
Improvements with financial process automation
The umbrella of finance – from payroll to predictive forecasts can involve menial and repetitive tasks which leave limited time and resources to focus on value-adding activities to grow your organization. When financial process automation is added, it serves as a pivotal support to free up needed resources and time.
As these technologies can cover more ground and more deeply analyze company financials, many organizations are finding that AI and automation technologies are actively improving their bottom line. According to a survey from the Association of Certified Fraud Examiners via the Harvard Business Review, “organizations lose 5% of their revenue every year due to fraud. The typical fraud case causes a loss of $8,300 per month and lasts a full 14 months before detection. And lack of internal controls contributed to nearly one-third of all fraud cases.”
Risk discovery is just one aspect of financial automation, but a growing one.
As AI, RPA and IA continue to use machine learning to do more and perform more intricate tasks, offering insight into finances, we are seeing how this can be incorporated into an organization’s long-term organizational strategy. MindBridge, for example, has developed AI technology for risk discovery, a complex financial task that incorporates not only transactional analysis, but offers broader insights into financial health and integrity.
Want to learn more about how auditors are using AI?
By automating certain financial processes, “finance professionals can not only provide real-time insights into the current status of the business but, with advanced predictive algorithms, they can look into the future and proactively steer the business.”
Financial automation and its capabilities are excelling at a fast rate. With the help of AI, RPA, and IA, standard automation practices can be enriched beyond simple pre-programmed controls and scripts. From McKinsey & Company once again, AI algorithms can learn from historical datasets and the interactions of the financial professional with the system, thereby improving the matching rates tremendously. In this context, matching rates refer to the ability at which an AI system is able to tag users to certain data sets based on their profile of demonstrated usage. Furthermore, the AI technology allows automatic extraction of unstructured information from documents, such as emails.
Of course, return on investment is always a concern. It can take a lot of time and effort to implement new technologies, and savvy business leaders need to know that the tools and processes they put their money behind will work.
According to Gartner, “AI augmentation will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally.” Basically, they define this term as the combined work of humans and technology, with the people at the center of the operation.
If these forecasts are correct, executives should be clamouring for AI and automation investment. Even a small piece of this pie can level up your office, department, or organization writ large.
What financial process automation could mean for work structure
One of the biggest concerns associated with exploring financial automation and therefore implementing financial automation software is what happens to the employees and the roles formerly associated with those finance objectives.
There’s no doubt that introducing financial automation will change the roles of many employees and even the manner to which employees are trained or progress toward career objectives. One thing is for sure though, automation will replace low-value, simple, and time-consuming tasks, thereby giving staff the flexibility to expand their roles, and spend more time on value-adding activities to help drive a company’s competitive advantage.
In an article from PWC on change management, they outline five steps that can help firms adopting financial automation make the transition as smooth as possible:
- Prepare for human capital risks like you’d prepare for any other risks
- Help people find their way
- Create organizational support for success
- Expect changes to jobs, compensations, and structure
- Learn new ways to develop your team
To unlock financial automation’s full potential, managers must be willing to re-engineer processes, and redeploy resources to optimize efficiency and output.
Another consideration for anyone looking to adopt automation and AI technology is assurance and verification. This verification work ensures that the technology in place is doing what it’s supposed to do, at the level of work required to meet compliance requirements and quality assurance standards.
Internal teams can “test” automations by utilizing what are known as “Test Frameworks” for applications. Some examples of framework tools come from SmartBear and Selenium. However, it’s a lot of work, and unless you have dedicated developers that can help your team test automation tools, you’re sort of stuck. For many businesses, it’s much easier to work with platforms and tools that have done this testing themselves by utilizing a third party.
A future with financial automation
Although IA and machine-learning algorithms are still considered in their infancy, that doesn’t mean finance leaders should wait for them to mature fully. According to McKinsey, many automation platforms and providers that struggled a decade ago to survive the scrutiny of IT security reviews, are now well established, with the infrastructure, security, and governance to support enterprise programs. “Where a manager once had to wait for an overtasked IT team to configure a bot, today a finance person can often be trained to develop much of the RPA workflow.” The exponential growth in structured data fueled by enterprise resource planning (ERP) systems, combined with the declining cost of computing power, is unlocking new opportunities every day.
MindBridge is a great example of a pioneer in unlocking the expanded capabilities of AI and RPA within the finance sector. With AI-embedded risk discovery, MindBrige can risk-rate 100% of the transactions in general ledger and sub-ledgers to produce an aggregated risk profile of the data that makes up the business’ financial statements, facilitating laser-like focus on the areas that matter.
The future of financial automation seems bright, already beginning to reshape the way in which financial services are performed in organizations large and small. Incorporating AI, RPA, and other forms of automation can seem daunting at first, as there are many tasks and organizational changes that go into implementing new technologies and processes.
By empowering your finance team with AI co-workers, they reduce the time spent on mundane tasks, enabling your team’s human intelligence to shine operationally. Financial efficiency and accuracy means happy stakeholders, and a growing business. What’s not to love?
For more articles like this one, visit our Resource Center.
MindBridge is proud to sponsor this year’s virtual Digital Accountancy Forum. The forum brings together leading accounting firms, industry bodies and regulators, advisors and consultancies, law firms, and tech vendors to discuss and challenge key issues impacting the sector.
On top of providing an opportunity to connect and network all day through the virtual booth, the event will also see MindBridge’s Founder and Chief Impact Officer, Solon Angel, present on how AI can help auditors keep companies out of trouble in a session at 3:00 pm BST.
Packed with valuable takeaways, the session will give real examples of how AI-based data analysis, planning, assertion testing and more can drive better client conversations and give auditors the evidence they need to back them up.
Solon adds: “From Carillion, to Patisserie Valerie, to Wirecard, the audit profession is being blamed for fraud schemes, scandals, and financial collapse. At the same time, the industry is slow to consider radically different ways of performing audit, and has instead focused on automation of the old ways of doing audit. It’s time to enable auditors to do their best, by giving them the knowledge and tools they need to uncover the truth behind an organization’s finances and visualize data in a way that empowers leaders to take action.”
But how can this be put into practice and how can AI really help?
Join Solon as he explains how machine learning works to augment human judgement, providing a clear understanding of how firms, regulators, standards bodies, schools and technology vendors can work together to restore trust in auditors.
At the end of the discussion, you will have heard:
- Why AI offers much more than automation
- How data science augments an auditor’s experience and judgement
- How data analytics enables new ways of thinking and services for clients
- Why restoring trust must include everyone, from regulators and firms to schools and technology companies
There will also be the opportunity to hear our Director of Growth Europe, Stuart Cobbe, join industry experts on the closing panel discussion. This session will explore the future of the accountancy profession, touching upon:
- If globalisation will have an impact on developing the next generation of accountants
- How the industry can ensure the accountancy profession remains attractive to the younger generation
- What future technological changes are needed to increase the automation of accountancy
We look forward to seeing you there! Register your attendance here. You can also meet our UK and product teams at our virtual booth!
If you’re looking for tips on how to make the most out of attending a virtual event, take a look at these do’s and don’ts to get you started.
I have had an email signature for many years which has a cheesy quote at the end. It reads “never doubt that a small group of thoughtful committed people can change the world.” The actual quote is longer than this, it is attributed to Margaret Mead who was an anthropologist, the full version is “Never doubt that a small group of thoughtful, committed citizens can change the world; indeed, it’s the only thing that ever has. ”
A colleague of mine recently asked me if larger teams was the key to success in a large company. I wondered if this colleague had ever read to the end of one my emails. Were they trolling me?
The core sentiment of the quote is that only small, thoughtful and committed groups of people succeed in making significant change. If you work in a tech company this is important because it applies most of all to the technology disruption around us today. Cloud computing and Artificial Intelligence are changing the face of many industries. Its not the older, larger and established companies who are necessarily leading this change, its often the smaller nimble organizations who have the focus to figure out and lead this disruption.
Quite a few years ago now I founded a small high tech startup that was fairly quickly acquired by Cognos who themselves were acquired a year or so later by IBM. Code I wrote in my basement in West London ended up 10 years later being a core piece of technology in tens of thousands of installations. Large scale tech companies are great for scaling ideas but my most important lesson working in small startups and big corporations was that ideas themselves and solving hard problems is not necessarily about big teams. In fact, its almost never about big teams.
Why is this so?
The first reason is quality over quantity. The adage in the industry is a great developer is three times faster at delivering software than an average developer. While this is true in my experience there is a little more to it. In small teams it is possible to handpick team members with the right mix of talents. With the right people with complimentary skill sets and respectful of each other’s expertise you can create collaborative teams that can easily out pace much larger groups.
Small teams with diverse and complimentary skill sets also foster something called the Medici effect. It relates back to team collaboration. Diversity in thinking and the connection of ideas through close knit face to face communication is often what leads to new innovation.
As teams grow they can impede themselves as a result of having too much overhead in communication. Its very hard to effectively have a discussion with 25 people, let alone 100. This is why effective software teams rarely are this big, and instead are divided into smaller mission focused groups.
The core point is, if you think you need a bigger team to solve a difficult problem, you are most likely wrong. Think again. This type of thought process leads to inaction and if you are in a startup this may result in failure. Sometimes constraints create the best solutions, so keep working at it. Time and again I have seen hard problems solved by small groups, often with simple approaches. My hopeful message to entrepreneurs and startups is not only can you solve hard problems that big companies may not be able to solve but you have the capacity and ability to disrupt entire industries.
Keep thinking you can change the world. Remember *only* small teams can do this.
Becoming a CEO is like becoming a new parent, there is no true user manual to guide you through the unique challenges you will face along the way. You can read a multitude of books about “how to” raise a child, however, there will inevitably be unexpected curve balls beyond what you already know and what you have read.
Ultimately it is your responsibility to ensure the safety and well-being of your child, under all conditions, 24/7, irrespective of the situation. So, let me start by defining the type of CEO that you are going to be. There are three models to choose from: the “plate spinner,” the “one-man band” and the “conductor.”
The “plate spinner” CEO generally does not have a full management team and by necessity has to rely upon themselves to juggle all, or nearly all, of the functional activities that must be executed by the team. The key drawback is that some tasks may fall between the cracks. It is similar to the “plate spinner” who must run back to the first plate once he has completed spinning the last plate to ensure that the plates do not drop to the floor.
The “one-man band” CEO has a more balanced management team but chooses to address and resolve most functional tasks by themselves. As with the “plate spinner,” this model does not lead to optimal execution or maximize the company’s success.
A great “conductor” can achieve melodious results from the members of their orchestra just by hand motions and facial expressions and without the need to speak a word. Similarly, a great CEO will have their management team working harmoniously. The “conductor” model is the optimal approach in creating an environment inside the company that fosters balanced execution by all members of the team. While the team remains under the guidance of the CEO, this approach leads towards sustainable and predicable growth.
Now that you are familiar with the CEO models, some of which you may be emulating, let me outline the actions that, I believe, a CEO must carry out to be highly successful.
Build the team –The top priority and most fundamental task of the CEO is to find and hire the best management team. The strength of the team will determine the degree of success of the company.
Work on the business, not in the business –This is a very simple notion, to spend most of your time managing and less time doing. Your role is to create an ecosystem for your management team to operate within by defining the vision and setting objectives. Then, create the infrastructure necessary to measure the team’s performance in meeting these goals.
Lead by example – People in the company will follow you if they believe in your vision and your actions. It is as they say that actions speak louder than words. The process is simple; initially, people will award leaders a certain amount of “respect and trust credit” but as time progresses, there could be a drop in the original “trust” level. A leader must build up and maintain his or her “respect and trust credit” by their actions which will earn additional “trust credits”, just as a battery loses its charge overtime and requires recharging. Be mindful that as the battery discharges to lower levels, it may be more difficult, or highly unlikely, to reach full charge again.
Listen – A great leader will do less talking and more listening. After all, you have two ears and only one mouth for a reason. People have the basic need to feel that their voice is heard and as a result will be more engaged and vested in the company’s well-being.
Make decisions – The most basic function of a CEO is to make decisions. A CEO must conduct a proper evaluation and analysis of the actions of their team and company performance even when there is only partial data available before making final decisions. Please remember that “no decision” is a decision in itself.
Think strategically – Wayne Gretzky, arguably one of the most successful hockey players of all time, coined the phrase: “I skate to where the puck is going to be, not where it has been.” Companies have to continuously assess their market position by assembling available data from competitors, current and future product capabilities/performance and market trends. With this data, the team must create scenarios and plan ahead. Based on this strategic thinking the organization then has a guide for tactical execution based on the merit of the potential outcome.
Ultimately, the question is whether these attributes can be acquired, or are they inherent as part of the DNA of the individual. In other words, nature versus nurture. The good news is that most of the above traits can be acquired over time. Given sufficient and consistent practice, an individual can acquire these traits and evolve as a true leader.
Note: Above blog post was earlier posted on Eli Fathi’s blog.[/vc_text_element][/vc_column][/vc_row]