Mitigating Transformation Risk with Executive Buy-in

Mitigating Transformation Risk with Executive Buy-in

Mitigating Transformation Risk with Executive Buy-in

There is a lot of hype around Artificial Intelligence (AI), Robotic Process Automation (RPA), and related emerging technologies.   Unrealistic expectations, poor understanding, and internal resistance are just a few of the challenges we face.  And yet, there are methods for how we mitigate this risk.  We know that many IT projects and or company projects fail without executive sponsors.  This is especially true when it comes to leveraging new or “unproven” technologies and solutions.  So, what is the best approach?

Despite the hype, Intelligent Automation technologies are becoming mainstream.  VentureBeat noted that in 2019, global private AI investment was over $70 billion, with startup investment $37 billion, M&A $34 billion, IPOs $5 billion, and minority stake $2 billion.  This investment is a sign of the early stage adoption life cycle (as described by Geoffrey Moore in “Crossing the Chasm”).  AI has been in the early stages for years with recent advances in technology moving to the Innovators and Early Adopters stage.

This discussion looks at the key points for senior management to understand the value in leveraging AI, RPA, and Machine Learning (ML).  Let us narrow it to four key talking points below:

  • Focus on Targeting the Objectives for Business Outcome

One of the most essential tasks an executive team carries out is to meet or exceed defined business objectives. These objectives will generally include a few key areas of focus around achieving pre-defined metrics. These stated outcomes are not only oriented around financial objectives but often include business growth and or optimized business targets. One can include softer objectives, for example, promoting or reinforcing adoption or instilling a ‘company’s Core Values with all employees.  The side effect of this enables employee buy-in for the change.

An executive team typically has short term objectives as well as long-term goals. One of the best ways to assure the success of your AI or RPA implementation is to do your homework to understand these objectives and goals. Then select one or two of the objectives and establish a plan to show how your project can leverage emerging technologies to help achieve or exceed these objectives.  It’s best to select some small wins first while also showing a path to achieving some longer-term goals. 

  • Leverage Best in Class Products / Solution

The intelligent automation industry is growing extremely quickly.  There are many intelligent automation products / solutions available today.  Important to the success of any project is to leverage partners to help achieve success. When selecting software, hardware, and or utility tools it is extremely important to select a partner with keen focus on and broad knowledge of the Intelligent Automation industry.  It is also important that partners understand your business,as it will greatly improve your chances of selling them as a part of your solution.  Finally, partners not only need to understand your vertical business, they need to take the time to understand your company, your core values and your business drivers.

When available, review case models of previous successes, including examples from your vertical line of business.  In addition to case studies, an experienced consulting partner can demonstrate how their Best Practices can assure you hit the agreed-upon timelines and objectives.

  • Focus on the Numbers

One of the best ways to succeed is by identifying a key metric or Key Performance Indicator (KPI).  A KPI can be very specific to a line of business productivity measurement or a broader focus such as a division’s bottom line.EBITDA (Earnings before Interest, Taxes, Depreciation, and Amortization) is a vital indicator of the overall profitability of a business.  One should also consider less direct measures such as cycle time, error rate, and cost of time to correct errors.

A great way to demonstrate project success is to show a path to success in achieving a KPI.  A best practice is first to study the vertical nature of the business to understand the most important KPI’s and pick one to focus on that you are comfortable you can measure.  It is important to assure you can measure a KPI so that you can agree upon an established baseline before your project.

You may be able to identify this quickly.  If not, take the time to ensure you identify a KPI and a means to establish a baseline.  KPI’s can only be achieved with effective measuring of progress.  For example, consider selecting a common denominator to the business.  For inventory, it could be “Piece Count” or “Inventory Accuracy”.  Given you’re in a services business, I would look to leverage “Time” as a common denominator (like “Time to Task” or “Paid Utilization”).

The key points being that you select an important measurable task to automate or improve, establish a baseline and measure against that baseline with set objectives to help achieve quick wins.

  • Learn from the Past and Plan for the Future

We all strive to learn from our past.  This includes what we have done correctly and what we might have done differently.  For a strong case to leverage technologies like RPA and AI, utilize these lessons learned from earlier projects.  Don’t assume that RPA or AI can be successful on its own.  There is much published now on the successes and failures of RPA and AI and the important role they play in digital transformation. 

RPA can be leveraged to streamline critical processes.  This can often extend the life of an existing process or system.  Think long-term when developing an intelligent automation roadmap and strategy.  Like any other project that was successful in the past, RPA and AI require a loop of planning.  This includes design, testing and leveraging a PMO program (some partners refer to this as setting up a center of excellence).  Be sure to set objectives with a clear understanding of success. 

In summary, Intelligent Automation is heating up!  Companies that focus their efforts on key business objectives, leverage best in class partners and solutions, manage by metrics and effectively plan their attack will be the most likely to successfully take advantage of these emerging technologies and reap the associated benefits.

AI – Artificial Intelligence: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

RPA – Robotic process automation is the application of technology that allows employees in a company to configure computer software or a “”robot”” to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems.

ML – Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.

PMO – Project management Office focused on managing the progression, milestones and success of implementing a program across multiple disciplines. 

KPI – A Key Performance Indicator is generally focused on the measurement of a given area of business. A KPI is not only at the center of setting clear financial objectives but they are critical in establishing base line performance, productivity targets, and group/individual performance.