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January 3, 2022
This post has been adapted from the A Leader’s Guide to Working with Consultants paper by Josh Atwell, Elizabeth Donaldson, John Esser, Ron Forrester, Ben Grinnel, Jason Hobbs, Courtney Kissler, and Jessica Reif.
Disruption of change is the balance of business process impact and complexity of change. Often organizations will attempt to take on too much change at once versus starting small, learning, and then scaling. Also, the number of individuals impacted is a factor, but not the primary indicator of the potential change disruption. It is important for organizations to understand the business process impacts in addition to the impact radius of the change. It is also important for internal team members to be engaged and see the value of leveraging consultants. The figure below shows the disruption of change quadrants, ranging from most ideal in the top-right quadrant (safe to try) to least ideal in the lower-left quadrant (big bang delivery).
We will go through each quadrant in the post below. To find out where your company lands in the Disruption of Change quadrants, download the full A Leader’s Guide to Working with Consultants paper and take the free assessment.
Consulting engagements that require large transformations and span multiple parts of the business run the risk of highly disruptive failure. Organizations in the “safe to try” quadrant have successfully mitigated much of this risk by reducing the complexity and scale of the engagement. Specifically, they have likely designed it as an experiment involving a limited but committed group of internal stakeholders who can validate whether the consulting engagement should expand beyond an initial pilot.
The advantage of framing a consulting engagement in this way is that it enables the organization to test a seemingly radical transformation at a non-radical scale, making an otherwise potentially risky path “safe to try.”
Consider the example of American clothing retailer Kohl’s, which was pursuing mechanisms to reduce its operating costs. In 2013, they worked with a consulting firm to complete some analysis. One recommendation was that they cut morning store hours on Monday through Saturday.
The executive team was split on the matter. On the one hand, reducing store hours might lead to a significant drop in sales. On the other hand, early morning customers might just do their shopping later in the day.
Instead of immediately adopting the recommendation across their full chain of 1,100+ stores, they implemented the reduced store hours at just 100 stores to test whether it would work. This both reduced the human complexity (i.e., the number of store managers and personnel involved) as well as the potential scale of the disruption (i.e., loss of sales). This made the recommendation “safe to try.” Ultimately, the advice proved that it did indeed reduce operating costs without a significant drop in sales, and Kohl’s implemented it at a larger scale.
You’re on the right track if you have already de-scaled your consulting engagement such that it involves a limited portion of the organization and does not have the potential to have unmitigatable business impact. While the “safe to try” quadrant is by far the most likely to achieve the stated outcomes of the consulting engagement, it does not come entirely free of risk.
One potential risk is a smaller engagement can encourage optimizing within a particular silo and discourage a cross-functional view—what may be optimal for just one team may not be optimal for the larger team-of-teams. Additionally, another drawback of a small-scale experiment is that you run the risk of not getting the appropriate organizational attention and resources. To mitigate these risks, we recommend three actions:
In a big-bang engagement, there are risks of failure due to a high-degree of organizational complexity and the widespread business impact of that failure. This is the riskiest profile of a consulting engagement. It occurs most often when the engagement’s success hinges on the adoption of new behaviors or mindsets among a wide employee base, but this group has not yet bought into the change initiative.
A major hospitality organization had different consultants using B2B leverage to drive conversations with the C-level executives. The most notable was influence from one executive at a large software vendor who was friends with the CEO of the hospitality organization as well as another major software company.
Two large consulting firms flexed their muscles. As two of the largest customers of the hospitality organization, they felt they should be awarded some type of business. This kept the large software vendor in the door as well. Whether it was good or bad advice didn’t matter.
One relationship allowed one of the consulting firms to oust a managed service provider within the hospitality organization and also influence the direction of technology. This included introduction of the software solutions from the company where the CEO sat on the board—clearly a conflict of interest.
Additionally, the consultancy was willing to put their specific team on the efforts that they thought the company would listen to and buy from . . . no matter the cost. That meant that if you seemed like a VMware-swaying customer, they would put the whole team and a specialist on it and tell you exactly what you wanted to hear, specific to that agenda.
The hospitality organization had a period where IT was greatly outsourced, due to consulting influence saying, “internal IT is expensive and not right for enterprises,” which led to pushing major and minor products to RFP stages with vendors all of the time.
This created churn—vendors would win contracts by underbidding (there was not a strong corporate process in vetting these proposals, and the technical teams that used to be able to do it were all pushed out by the outsourcing), so consultant companies found ways to get the organization to waste money with consultative gigs to “evaluate and assess,” which went on for four years.
The hospitality organization woke up (by chance) by establishing a cloud team after one of the major software vendors won the cloud contract (leveraging business relationships, not capabilities or track record), and it had been failing miserably for multiple years.
During this time, a strong leader was hired and established what she described as “world class enterprise DevOps.” She was able to stop the revolving door of consultants looking to “discuss how we can bring DevOps,” as those RFP business deals always resulted in desperate attempts for the companies to find ways to drag out the contracts past initial agreement to keep the money flowing. Money was being lit on fire, and the massive project was approximately $24+ million over budget. However, with the small assembled team, delivery was corrected and everything was set back straight.
To mitigate these risks and move toward an engagement with a greater chance of success, consider the following options:
The “controlled chaos” quadrant represents large scale change, but that change has been designed to be iterative. Iterative at this scale is hard and requires a huge amount of change management. Don’t find comfort in an iterative plan unless you are clear on what you are iterating toward (not a destination but a direction), and you have reliable feedback loops that will demonstrate success or failure and provide learnings. Iterative transformations use these learnings to build understanding and confidence as they progress. Without them they are blindly meandering into failure.
Disrupting the whole business with a series of iterative experiments is rarely the right approach. Maintaining leadership alignment and shareholder value is extremely difficult. Books like Geoffrey Moore’s Zone to Win describe a number of approaches successfully taken by large organizations to transform the business while maintaining cash flow, revenue, and profit. Check how well-versed your consultants are in these approaches as you validate their proposals.
Some potential risks in this quadrant include:
A CEO at a large software company engaged consultants to help with introducing value stream mapping to the organization. He intentionally identified internal team members to learn from the consultants in a “train the trainer” model so he could build the internal capability. The engagement included validation that the internal team members could successfully teach value stream mapping and evolve the process without dependency on the consultants. In order to validate that the engagement was successful, the CEO brought in an additional external advisor to assess the health of the engagement and the outcomes. This enabled a healthy, productive conversation about the progress the consultants and the internal teams were making.
In a second example, a director at a large retail organization was asked to bring in consultants to help with a strategy for improving order delivery. Once the agreement was signed, the COO of the organization delegated to the director to partner with the consultants to deliver the outcomes. Because this was a complex topic, the director wanted to make sure there was a cross-functional leadership team steering the engagement. She recognized that the consultants were going to require some ongoing guidance and input from a broader group. She assembled the cross-functional steering committee with business and technology leaders, the consultants, and an outside advisor. The addition of the outside advisor created a platform for candid, direct feedback about the progress the consultants and organization were making.
It can be challenging to practice the discipline necessary to not have multiple experiments and iterations happening at once. If you find yourself in that situation, pause and adjust to make sure the changes are being managed in a thoughtful and intentional way. One path you can consider is using the A3 problem-solving method with your team, including the consultants to ensure that each change is being well thought through and has a measurable outcome. With A3 problem solving, it is also important to only have one experiment/iteration in flight so you don’t sub optimize the system.
In the radical change quadrant, organizations are likely seeking what appears to be a small change but has the potential to be disruptive to the entire organization or business. The change may be small in the number of people it affects, or it may involve a very limited set of processes or systems. In other words, the scale of the resulting change may be much larger than the scale of the effort to bring about that change.
In this case, organizations should be ready to prepare for how potential new ways of working will result from this disruptive change. Don’t allow the relatively small size of the effort prevent you from planning for and communicating the expected larger disruption to the culture and ways of working of the organization.
Failure to plan for how your organization adopts this disruption holistically will almost certainly prevent the organization from reaping all, or any, of the intended benefits of the change. Reliance on consultants to understand the broader impact of disruptive change across the organization puts them in a difficult position and, worse, removes ownership from the organization for operationalizing the resulting changes.
The CTO of a large retailer recognized that her organization did an excellent job of capturing a significant amount of data on customer interaction with their e-commerce site, but the use of that data had been relegated to traditional analysis to bolster the gut instincts the organization has about why their customers behave the way they do. She realized that the amount of data they had gathered could facilitate some deep machine learning (ML) capabilities to drive hidden or otherwise nonintuitive insights.
She engages a consultant group to bring in some ML expertise while she hires a small team of subject matter experts. Together, they model against the existing data and experiment with driving customer behavior insights from a small part of the site: the cart. She knows that this is only the first step and that preparing leadership and other stakeholders to shift decision-making from instinct to high-fidelity data will take months if not years. She socializes this consulting engagement with her leadership and stakeholders, and uses that as an opportunity to describe the ultimate outcome of shifting to a truly data-driven decision process.
For organizations in this quadrant, the most important things to keep in mind are:
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In summary, our intent with this paper is to honor the reality we are all facing: we need healthy, impactful consulting engagements. We know this is a critical component to accelerate transformation and to deliver business outcomes. However, many organizations want quick answers and look to external parties to deliver those answers without thinking through the implications.
As shared in the book Sooner Safer Happier, “Even installing a third-party application, such as an ERP system is novel: that code has never been installed in that context with those data feeds, those people, and those processes before. Minimizing time to learning is key; fast feedback loops de-risk delivery and enable optimizing for outcomes.”
With this assessment and guidance, our goal is to provide the community (both companies and consultants) with a mechanism to understand the structure of the consulting engagement and to optimize for the intent of the engagement, reducing risk and maximizing delivery of the outcomes.
You can download the full paper and assessment here.
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