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When considering getting a hand on a “portfolio” of work or initiatives, most organizations are looking at change – either through the array of work or how they do the work or how they manage the work. Or even some combination therein. The bottom-line is there is a call to action driving the need to deliver this portfolio of investments and committed outcomes to the business. Looking at this list of initiatives holistically as an ongoing set of investments, portfolio governance is central to effectively delivering change. Otherwise we fall back into the trap of making short term, isolated decisions, in granular initiatives, losing the real potential of executing across our strategic commitments.
So where to start? How do to know if I am focusing on the right levers? Thinking of governance as an “operating system” might help. And this system could land anywhere between lean and comprehensive, depending on the demands of your function/PMO and maturity. Still, there are basic components worth considering ensuring launching with a solid foundation. First, defining the drivers behind the “call to action” and related impact to culture. Aligning on mechanics and KPIs or data points. Lastly, laying out the process and related discipline so it runs effectively and does not just become another bureaucratic distraction.
DRIVERS AND CULTURE
Of course, we are speaking of the drivers of change (to stand up portfolio governance) and the behaviors to support these drivers. Example drivers are as simple as understand all the work going through the organization, closely monitor for rapid course correction, ensure all investments deliver the committed results. These are the north stars objectives that must be embraced and supported in the culture through leadership. Leadership models this mindset shift and cascades the culture down through their teams. Modeling the shift may be actively participating in the Governance process or setting up new incentive criteria in their organizations tied to portfolio performance.
MECHANICS AND METRICS
There are core mechanics for portfolio governance to stand up the leanest possible system, that can then be enhanced with additional features as the organization matures. Similarly, key performance indicators or metrics have a baseline set with many more to suit the organization’s capability, bandwidth, and desire for data. Basic mechanics align with the governance process and KPI’s with the associated reviews or decisioning consistently across the portfolio. Mechanics are things like candidate project intake, scoring model, initiative hierarchy, and alignment to strategic elements (pillars). Also, the logistics of capturing data, reporting, formalizing key decisions, tracking changes, and switching phases (Intake, Execution, Benefit Capture). KPIs and/or metrics are the minimum set of data to effectively evaluate and track initiatives “apples to apples” across the portfolio planning lifecycle.
PROCESS AND DISCIPLINE
Outside of culture, the process across which the portfolio of invested work is governed serves as the glue. The mechanics, data, and people come together in the process. The process through which the portfolio is governed typically spans three (3) phases: intake, execution, benefit capture. However lean or complex, these phases have common objectives that sew together across both initiative and portfolio lifecycles. Intake focuses on the description, prioritization, and acceptance of initiatives into the portfolio for a given planning cycle. Execution is that familiar phase where initiatives are funded and performing their work. And Benefit Capture focuses on the transition from Execution to start measuring the results of the work delivered.
Running this process with the associated mechanics, data, and people takes discipline to stay the course, leverage the data, and ultimately realized the outputs of the portfolio investments. With so many moving parts, it is crucial to establish governance in a framework that clearly supports the linkages and visibility throughout.
We often see a fourth phase where optimization is employed to enjoy lessons learned and further tailor the framework to the organization for maximum benefit production and minimal risk.
What is the most important component? Obviously, every team and organization is different, but it is safe to say culture. The hearts and minds of leaders, then their teams, need to be committed to the changes that portfolio governance can usher in.
Many organizations are exploring a more structured governance of their investment and transformation portfolio (critical programs and projects!). With the ongoing demand for rapid change and modernization, these portfolios of work have become more and more unwieldy for even the most competent teams. Implementing Portfolio governance can drive huge results by (1) structuring initiative approvals, (2) visualizing portfolio health in execution, and (3) tracking results. But where to start?
A financial portfolio gives you an overall picture to manage risky investments against or offset by conservative investments to meet goals within given risk tolerance. Similarly, launching strong portfolio governance across an organization’s book of work creates strategic linkage, business discipline, visibility, and line of sight to results. Taking a holistic view upfront, the concept of portfolio governance takes into account the overall strategic aims of the company and compares it with proposals at hand.
If your organization is committed to launching portfolio governance, it starts with aligning on the objectives for governing the portfolio of work. Is it to meet strategic objectives, is it to meet and hold the line for a budget value, is it a combination? Once alignment is in place as the leadership level, then there are really two dimensions that shape the design and launch of Portfolio Prioritization:
the mechanics of how managing the portfolio will function
the leadership culture to support the discipline
Some teams feel that they need to re-evaluate the current or in-flight inventory of initiatives. Others simply “grandfather” in those investments and work with what remains in the budget. The decision really should just tie back to the overall objectives of prioritization. Does one way or the other significantly dilute the business case?
The next step in launching is establishing intake and scoring of candidate initiatives against strategic criteria set by the company to establish a whole process of portfolio governance. After the total budget “line” has been set and the scoring criteria established, heads of each business unit should sit together to review qualifying candidate initiatives. A competent, consistent structure is the key to successful portfolio governance that can make an empirical decision to fund a project based on how closely it is related to the strategic aims of the firm – as defined by the scoring mechanism. This uniform procedure of evaluation can identify proposals of any overlapping projects, limit the attention to initiatives with poor business cases (also high risk), and help in alignment between projects from varying sectors of the firm. In this first cycle, it is important that the leaders are involved in this pressure testing of the intake process.
The next step in launching portfolio governance and prioritization is setting the portfolio (based on prioritization). Again, it is important leaders are at the table throughout this process and engaged in the decisions. Rich discussions happen here where we have ties between equally qualified initiatives in different business units and where “puts and takes” are determined as initiatives move above and below “the line” – the budget limit. This horse-trading exercise needs to happen quickly, be data-driven, and involve all leaders so everyone is committed to the final portfolio.
As you may have gleaned, throughout the initial launch steps we are looking for leaders to potentially change their mindset and participate in a different, structured, and cross-functional culture. Included in this change thinking is the fact that approved initiatives are accepted into governance as opposed to disappearing into the PMO (program/project management office), and therefore be tracked through execution to results delivery.
Much more on that later, but hopefully this launch summary triggers some thinking about how it might work in your particular organization and culture.
More and more the world depends on technology, and business success can be measured by how well you keep up with the (ongoing or inevitable) digital transformation – especially in these trying times with Zoom relationships and distance everything. No matter what industry your business belongs to, the sales organization must thrive and accommodate digital solutions to stay ahead of the competition. One such category delivering innovation into the Sales domain is CPQ: Configure, Price, Quote.
CPQ platforms provide you with the end-to-end digital transformation in sales processes. CPQ acts as an effective vehicle for configuring the products and pulling out the right prices matching the needs of consumers along with assigning accompanied discount policies of the company to then generate quick, accurate quotes. CPQ can digitalize the processes of sales in such a thorough manner that it is no more an optional aspect for the business. You are too slow to move with the world if you are still on the typical spread-sheet approach. CPQ solutions are often delivered by subscription SaaS model software to rapidly automate your sales department liberating it from latency and mistakes that kill deals while enabling exponential growth or capacity.
In the data-driven age, CPQ processes the digitalized information of products in terms of product metrics such as numbers, weight, size, prices and other defined attributes for each particular product. Each completely configured product combination is then broken down into components and connected with business rules in the CPQ platform. CPQ intricately interlinks each component, evaluating every option against others and enforces rules of sales available in the viable quote configuration. All the processed data and rules are analyzed by CPQ to design the price of the product and generate that valid quote matching to the consumer needs – ideally in a guided experience.
As business accelerates and consumer get more savvy, modern CPQ solutions must keep pace with multi-channel access, mobile experience, built-in AI and cloud infrastructure to enable a broader community across the competitive landscape. Even now, CPQ runs on your smartphones integrating with the other complementary systems such as sales-force automation (SFA) and customer relationship management (CRM). The biggest benefit CPQ can offer, making it a key pillar of digital transformation, is the end-to-end automation of critical processes enabling every member of the sales team – from laptop screen of the CFO to the mobile phone of sales manager, thereby streamlining quote and contract creation.
Although there is no silver bullet in Sales, CPQ makes sure you guide your prospects to the right offerings with best approved pricing so the only work remaining is getting that signature!
Robotic Process Automation (RPA) is the latest technology to mature in the area of digital transformation and cost optimization for companies. Before launching RPA in your organization, it is important to develop a strategy that best leverages the software to deliver tangible results tailored to your organizational priorities. Most organizations prefer to experiment with RPA in contained areas before driving an enterprise-wide launch. When organizations are serious about launching an RPA program, this proof of concept or pilot approach can work best if you model sample areas that model common scenarios across the organization.
Before launching RPA, the best practices the companies can inculcate for the preparation and then operations of RPA include working actively with your IT team to install RPA software successfully and constructing the platform controls for enterprise automation, training human capital for effective adoption of ‘bots, creating a ‘bot “manufacturing process” for defining, configuring, designing and testing automated processes and monitoring the RPA platform for ongoing improvements.
Once you have begun defining how RPA will roll out across the enterprise, it is important to identify the candidate pipeline for automation and, ideally, frame up an intake, prioritization, and governance process to qualify candidates. These days there are many best practices that help define RPA ‘bot success factors – such as processes that are rule-based, well defined with repetitive steps, require minimal human intervention, etc. More on that later, but the goal is to discover all qualified processes to realize the ROI of RPA while avoiding the distraction of those processes that will not deliver comparable value through automation.
To that end, performing an analysis of ROI is an important step in launching RPA. It is advisable to calculate all kinds of costs both non-monetary and monetary along with the time taken for completing processes and compare it with the cost optimization offered by RPA – just as would be required of any company initiative. In addition to creating structured intake and governance, launching RPA also involves putting infrastructure in place and procedures required to develop then support the ‘bot development. Lastly, enabling the tracking the results is also crucial in this new paradigm of “snackable” or bite-size projects called ‘bots. We need to take the investments seriously and realize that the success of RPA in your enterprise requires a system that can systematically identify, approve, deliver, and perform at a high-volume, granular level.
Launching RPA can work efficiently for your enterprise if you take the proper steps to prepare, organize, launch, and then track specific results to the business.
Robotic Process Automation (RPA) is the maturing trend in the businesses because well, it involves robots and robots are awesome! As fascinating as the concept sounds, it may be that “all that glitters is not gold” in some situations. The main idea of RPA is introducing software that handles repeatable human interactions and mundane tasks with software application instead of humans.
The good side is, of course, it reduces the human effort, and therefore cost, in un-important areas of business management. RPA deals with various applications performing tasks such as opening email attachments, filling e-forms, recording data, re-keying information, etc. eliminating long hours of copy-pasting and data entry stuff. It is especially useful while dealing with the old legacy applications creating the continuous flow of digital data instead of accumulated large data pools in corporate sectors and it is definitely money-saving as well.
The downside however of RPA is based on the fact that it automates the same rules and repetition of processes and is not able to adjust like humans. If there is any change in the application’s data, user interface, or some other aspect of the business process, the deployment of a “’bot” is faced with major complexity and ultimately is broken down. The downstream and upstream mutations can considerably delay the process even in the duration of bot configuration. The truth remains that even the slightest of changes that could easily be dealt with the manpower can cause months and months of lagging in the corporate infrastructure.
Then there is the economics. While change management and adaptive capabilities are challenges for RPA (and its robot army), there is the cost and effort of buying a software stack, building human capabilities and culture around RPA, and pointing automation in the right areas of the business to drive results. These dimensions are all part of the business case that must be considered for RPA. Simply put: RPA is not point and shoot.
And The Good
RPA still offers quite a bit of value in large organizations and/or across processes with high volume, repeatable steps. The mantra remains: free up your expensive resources (labor) to focus on high-value work like exceptions or innovation.
Also, companies are already enhancing the RPA systems with Artificial Intelligence (IA) – also described as RPA systems with cognitive abilities i.e. CRPA (Cognitive Robotic Process Automation). This software is more resilient and smarter than the ordinary RPA, detecting changes, and making intelligent decisions. But the debate remains the same as some cons outweigh the pros in this situation too. The CRPA technology is still not mature and is functioning in its early days where you cannot rely on it completely for your corporate data. The fact that RPA makes use of the UI (User Interface), can make it brittle to use. Some modern apps are offering APIs (Application Programming Interfaces) which makes RPA somewhat resilient to the changes but this capability is still emergent in the market.
RPA technology is recommended if you are dealing with legacy system-driven processes but need to succeed in the modern digital world. RPA can provide a valuable bridge to keep these legacy business processes moving while both re-focusing knowledge workers and preparing for more strategic automation of a digital enterprise.
Everyone (we know) is challenged to do more with less, faster. Even in this agile world with a “fail fast, learn fast” mentality, there needs to be a lean structure to progress toward agreed outcomes. And left unaddressed, every request, initiative, or investment is priority 1, mission critical. As result, there is no predictabilty to succeeding against the objectives at hand. Establishing prioriization in planning and portfolio execution helps get stakeholders aligned and supportive of the greater strategic goals.
When we engage around process improvement, typically two common, yet opposing, perspectives surface with clients: eliminate waste or release potential. The beauty of process work is you can really do both, but it starts with mindset.
Enterprise and division-grade cost optimization is hard because there rarely a handful of clear or quick wins. Instead, we find there is often a complex prescription of medium potential programs that need to be managed tightly to deliver close to expected. At the same time, there must be a balance between necessary oversight without debilitiating overhead.
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