Do the merits of Agile as a build approach for software development equally apply when implementing standard software?
For many years Agile has been successfully used in software development projects. Its merits are most obvious when having to build something that hasn’t been done before and when the user or client is unable to picture the desired end result with all requirements specified at a sufficient level of detail.
The iterative approach in the Agile methodology addresses that fundamental problem by parallelising the phases of design, develop, and test that are distinctly separated in the classical, incremental Waterfall approach into a series of iterative Sprints. This allows for the user to understand what they really need while the developer learns how to best build it. The very same concept also provides for much more flexibility when having to deal with frequent changes on the way. More so, Agile is able to facilitate frequent changes in scope and/or requirements whereas Waterfall avoids the same once the design is signed off.
The below picture shows the fundamental difference between the incremental approach in Waterfall versus the iterative nature in Agile:
Given the obvious advantages of Agile in software development it is no wonder that projects implementing standard software like SAP started to look at Agile some 10 years ago. But then, the very benefit of deploying standard solutions is that there should not be a lot of developments to be done in such projects in the first place.
And there is the challenge. For too many years customers implementing standard software have spent a lot of time and money to make their solution as specific as possible, often with lots of add-on developments and even modifications. This has contributed to a perception that SAP implementations are complicated, take long, and are expensive. Interesting to note that I never heard any customer complaining about Waterfall being so resistant towards change whilst scope control discussions are a constant in any given project.
Today’s organisations want fast implementations with tangible business impact. They are looking for cloud solutions which naturally come with more restrictions for custom-build enhancements or even modifications. At the same time many prefer sticking to an incremental approach towards deploying their solution in order to remain in control of the expected and predicted outcome. No need to say that every customer also needs flexibility in terms of responding to changing business conditions. The latter has not been more prevalent than now.
All of that requires a specific approach when looking at the implementation of standard software solutions like SAP. On the one hand clients like the fact that Agile produces useable solutions quicker and the flexibility it provides. On the other hand, clients often don’t like the notion of Agile being so tied to software development when they just want to leverage the benefits of a standard software solution. Also, not every organisation is ready for an Agile approach as they feel they have less control over the final outcome or key individuals cannot be dedicated to the project as needed.
Fortunately, the best of both worlds can be blended to successfully deliver implementation projects leveraging standard software solution be it on premise or in the cloud.
I have used the following approach when discussing the best way to achieve both speed, user acceptance, minimal enhancements and add-ons whilst allowing for flexibility when having to adopt changing circumstances.
Assess the general Agile readiness of the organisation
Understand Agile specific roles and responsibilities, ground rules, and success factors
Agile project governance and project setup
Lean Blueprint approach to create the Product Backlog
Breaking down the Product Backlog into User Stories
Story Mapping from a first feature set of a walking skeleton to full functionality
Definition of Done
High level estimation and release planning
Organise realisation of the first release in Sprint Cycles
Final preparation and Go-Live of Release 1
Obviously, the first point is critical in understanding whether or not Agile can work and be beneficial for a given project in a specific organisation. If this check shows more No’s than Yes’ or if the score is below 50% than a Waterfall approach is likely to be the better option. Where the scores indicate a better general readiness, it is prudent to ensure the client understands how Agile can be used successfully. Going through points 2 – 10 of the above with various key stakeholders will do exactly that.
In my own experience I have seen Agile working very well in standard software implementation projects. This is particularly so when there are many unknowns like new technologies or new (business) solutions at play. If an organisation is ready for Agile, I would always recommend going for it. The benefits of better-quality results, early visibility into what the project is in fact building, and the ability to cope with change in the project are simply too valuable to be missed.
Let me know what you think and what your experiences are in using Agile in standard software implementation projects. I am also keen to hear about how your Agile projects have fared in times where most if not all work is done remotely.
S/4HANA is SAP’s next generation business suite. Mainstream maintenance for the existing SAP Business Suite 7 (ERP 6.0, CRM 7.0, SCM 7.0, SRM 7.0) has just been extended until end of 2027.
S/4HANA has tremendous innovation potential like the HANA in-memory database, Fiori UI, S/4 Analytics, Internet of Things, Big Data, business networks, and mobile-first. Simplification is the name of the game. Much has changed (see SAP’s 1’000 pages Simplification List). Homegrown overlapping of solutions (e.g. ECC, SRM, and Ariba for procurement) have been removed (SRM functionality has been moved to S/4HANA and Ariba respectively).
SAP’s product strategy is clear: cloud first and this means S/4HANA. Updates and innovations will be released in the cloud first. SAP ERP will lag behind.
SAP is supporting different options to implement S/4HANA (system conversion, landscape transformation, or a new installation). At the same time many SAP customers rightfully consider this move more complex than previous release upgrades. This because so much has changed with S/4HANA and much is unknown territory; even for many seasoned SAP experts.
Transition to SAP S/4HANA Roadmap (Source: SAP)
Nevertheless, the question is not if to migrate but rather when. How and where to start exactly still remains a question for many.
An all-in-one go is possible given the many accelerators and modernised tools provided by SAP. Just, this may not be palatable to everyone. Many different topics need to be considered (retention of legacy data vs. full data migration, data harmonisation and process simplification, custom code migration vs. simplification, new UI possibilities, on-premise vs. cloud, real-time analytics vs. ABAP reporting, agile vs. waterfall implementation method, availability of critical skills, etc.).
With enough time each of the above topics can be tackled and explored in various pre-projects prior to moving to S/4HANA itself. Still, the question where and how to start even with such pre-projects remains.
So, how does one best approach the journey from ERP to S/4HANA? An analogy to using a GPS system may help.
In order for the GPS system to find the best route from start to destination a clear enough description of the destination is required. Simply stating: “we want to be on S/4HANA” is as useful as telling the GPS system: “I want to eat Italian”. A more helpful description of where one eventually wants to arrive at would be, for instance, a (high-level) target application and system landscape showing process and data flows across organisational units.
Identifying the exact starting point follows the same logic. A GPS can, for example, use the current location to identify the respective geometric coordinates. Accordingly, for the move to S/4HANA, one needs to understand:
Details of currently used applications (release, licensing, cost of operations, etc.).
Number and location of respective users.
Quality of data.
Use and state of current custom code.
Legal requirements like data protection and retention rules.
In order for a GPS system to propose a meaningful route, existing constraints (e.g. traffic) and preferences (e.g. avoid toll routes) need to be considered. For the move to S/4HANA this might translate into one or more of the following:
What are current and anticipated future market forces?
Where is the business strategy heading to?
Where are buckets of consumable innovation?
What is the state of readiness for a transformational IT project (see my blog on 8 success factors)? How about the support readiness for an S/4HANA application or the corporate willingness to change?
Are there obvious candidates (applications, systems) for early decommissioning? Associated cost savings may provide funding for a migration project.
Clearly, no customer situation is the same and caution should be applied when ready-made answers are provided. Analysing the specific and individual aspects of “where are we starting from”, “where do we want to be”, and “what are our preferences and constraints” will answer many questions and naturally develop a tailor-made roadmap for the journey from SAP ERP to S/4HANA. Done well and with the right people such exercise shouldn’t take long.
Carpe diem – get started now; without haste. Use a proven and structured approach towards unpacking the various critical elements that are needed to plan and prepare for a future that has already started.
Everyone wants every project to be successful. When clients are asking what must be done to ensure success my answer always is: get it right from the onset.
Over the decades of my professional career in IT implementation projects – both successful and troubled ones – I have come to learn the following. Mistakes you make in the first phase of your project can turn out to be devastating but often go unnoticed until later. Mistakes in later phases can lead to higher costs and may need time to resolve but they usually can be addressed within the project to eventually go into production.
Why is that so? Well, compare an IT project to the construction of a skyscraper. Both depend on a solid foundation. You won’t be able to fix the basement once you have arrived here:
One would not be able to go back without endangering the entire project – demolishment or abandonment are the options. In any case most likely the premature end of that very project.
Just like with the construction example any project depends on a solid foundation to be built on. For IT projects this includes (but not limited to) the following.
Stakeholder engagement and involvement
Scope definition tightly linked to the business case
Detailed planning and scheduling of all deliverables needed to complete the project including dependencies and resource requirements (both internal and external)
A proper project management charter outlining specific approaches to scope and risk management, quality assurance, and issue resolution just to name a few
The nomination of a competent and experienced project manager on the client side is obviously one of the first and early steps and, if done well, will ensure this all-important preparation work is done well. In fact, on the other side, this is a good example for what can be done wrong in the beginning but often only shows results and consequences later.
But where to find that individual with the right experience and leadership style to manage the project or program to success on behalf of the client? Outsourcing this role to one of the envisaged, external service providers is a common approach. Just who, then, is managing the service provider(s) and who is coordinating the client’s own involvement? Finding a good candidate from inside of a client’s organization proves difficult when the best people cannot be made available for the project or when it doesn’t make sense to hire someone just for the limited time of a project.
This when contracting an independent project manager on behalf of the client comes into play. Platforms like Toptal are a good place to find hand-selected and competent individuals helping to find the right project leader.
Every top project manager I have come to meet and see in action will ensure this critical foundation building phase of the project is done professionally and to the extend needed to ensure a successful outcome. This is my best answer when being asked for what is the single most important success factor for IT projects: have the right project manager ensure the foundation is fit for purpose and solid enough to carry the project all the way through closure.
Projects should be kept running for a lead in catching up once restrictions are released as well as to avoid a potentially non-recoverable project stop. This is what you need to know when switching your project from an onsite to a remote working model.
Projects can and should be kept running
The current Coronavirus pandemic is already exposing more than a third of the global population to lockdowns, travel bans, and social distancing measures. Businesses are cutting or even shutting down. Individuals are losing jobs. Not only will this have dramatic and immediate effects on the global economy. It will also have adverse effects when businesses are trying to quickly ramp up operations to pre-crisis levels once restrictions are released.
Fortunately, the IT services industry has long established means that can now be used to mitigate the impact of social distancing and travel bans. Remote delivery models have been successfully introduced many years ago. If planned and managed well remote work yields substantial benefits (e.g. travel cost savings).
Switching the services delivery model from a classical onsite to a remote working approach in the middle of an IT project within a matter of days, however, is anything but business as usual. Yet, in many cases, this is almost the only option if a potentially non-recoverable sudden project stop is to be avoided.
The good news is that the required technical infrastructure (internet access, laptops and mobile devices, communication and collaboration applications) is broadly available. So, technically, remote work can be done literally anywhere. The question is more how smooth such a transition can be.
Below are some basic points that project managers and IT executives should look at as a starting point. Some may sound trivial. Some may be ticked off quickly if already in place – the more the better. Other points may have to be added in the context of a given project.
Ensure necessary authorisations for remote access across all project roles are in place
Laptops and mobile devices
Shared document folders
Are there legal requirements preventing individuals (incl. tasks and data) from working remotely?
Existing service contracts
Do long term travel and accommodation arrangements have to be cancelled?
Do service provider’s contracts provide for remote work?
Any changes in available resources expected?
Any changes in deliverables and scheduling expected?
A solid project plan in form of a Work-Breakdown-Structure (WBS) with clearly identified deliverables and allocation of responsible resources is strongly recommended to keep the project under control
All of the above will show if the current baseline can be kept
Introduce weekly or bi-weekly reporting on actual time spent per task as well as an estimate to complete (must not be budget minus actual to date!) to compensate for lack of personal interaction
Use Earned Value Management to track and forecast project performance (i.e. time and cost) tightly and to predict deviations from the baseline early on
A formal and project wide issue log should be available and managed centrally
Team members need to be motivated to report issues early on (praise early reporting, blame late reporting)
Have more team meetings with less participants (at least in the beginning)
Keep virtual meetings short and precise
Be formal in how meetings are prepared and conducted (have a clear goal, an agenda, distribute meeting minutes with action items for follow up)
Make sure everybody contributes actively
Cost implications (e.g. savings targets, less travel, more communication)
Period allocation (will budgeted costs shift to later or earlier periods?)
Actively address personal fears related to health and job security through HR
Be aware of possible psychological effects from social distancing and seek to address those outside the project
Engage individuals to actively contribute through remote working
Ensure people remain engaged whilst working remotely
Consider and respect the consequences from people working in different time zones
How to control working hours (internal and external staff)?
Contact Aurelia Consulting (firstname.lastname@example.org) to find out how to best switch from onsite to remote working for your IT project.
Understand the paradigm shifts of the digital economy and see how to drive your transformation towards an intelligent enterprise powered by a data-enabled learning organisation in a simple step-by-step guide for a data management strategy
Why should you care?
Enterprise data is often referred to as the new currency. Why is that so?
In a global economy an individual customer is often not really known (beyond a name, an address, a payment method, and a purchase history) to the business. This in turn makes it difficult for a company to develop new products or services that meet or exceed market demands.
Now, for a moment, think about that old fashioned, small butchery around-the-corner type of shop. The owner of that butchery knew his/her clients personally, had insight into their preferences, their habits and moods, their expectations, their credit worthiness, and often even understood their entire personal and family background. The better that business knew their customers the better their chances of building long-lasting customer relationships and, consequently, sustainable success.
The latter insight into the relationship between knowing your customers and the success of your business is of course nothing new. Gathering customer information to make better products and services is an old strategy. Only problem is that traditional approaches aimed at gaining insight are costly, time-consuming, and often only based on a relatively small number of customers. This is particularly true for many traditional manufacturers using indirect sales channels or distributors.
Today new technologies like the cloud, IoT, machine learning, and AI enable companies of all sizes to quickly process vast amounts of information and to make sense of it. With that the paradigm shifts from data insight of a selected-few towards data-enabled learning organisations.
With the raise of the internet and social media customers have become much more informed and aware of alternative choices. Despite that there is that one thing that has not changed for an individual customer. It is the appreciation of that warm feeling coming from being known, understood, and be treated as someone special and unique. Why else do we all aspire ranking high in modern loyalty programmes?
The paradigm of the Intelligent Enterprise explains how the best of both worlds can be brought together: reaping the benefits of digitisation (data-enabled learning, speed, reach, flexibility, scalability) plus being able to create a compelling customer experience. For long the successful entrepreneurs understood what their customers aspire to (sometimes even before customers expressed the same) and knew how to best deliver it. This equation is unlikely to change anytime soon. However, in a digital economy, companies can no longer solely rely on a genius entrepreneur but require an all-encompassing, data-enabled learning culture and organisation.
It is exactly for that reason that data in a digital economy is considered to be a, if not the, main asset of any enterprise; small or large alike. Chances are data may soon appear as an asset in corporate balance sheets.
Increasing digitisation of processes, human interactions, and machines are generating data in structured and unstructured formats at an unprecedented speed and volume. This happens inside and outside of individual enterprises. So much so that companies are running out of capacity to store all of it. At the same time many companies seem to understand less and less about their customers and businesses. Astoundingly, this appears to be mostly prevalent in those businesses that are commonly considered being very close to its customers and the market – Medium Enterprises.
Surprised? One would expect the opposite given the advancement of modern technologies and the ubiquitous access to information.
How can companies deal with an ever-increasing speed of data creation taking place at dispersed locations and across multiple applications, systems, platforms, and clouds? Obviously, the traditional capturing, storing, and pre-defined processing of data needs to be reviewed in the light of today’s reality and business leadership’s needs.
An enterprise-wide data management strategy ensuring seamless data access, integration, and orchestration focused on expanding digital capabilities will guide the way from handling (big) data to operationalise data for intelligent analysis. This is how data can be leveraged as the core of an intelligent enterprise.
What are the challenges?
So far, I hear many saying that all of that makes sense: “but our current situation is full of roadblocks …”. And those of you feeling like that are not alone. Let’s look at what businesses see as underlying challenges complicating the intelligent use of data. The same source from IDC sheds some light into this.
Clearly, these issues need to be addressed if companies are embarking on a journey to make more effective and intelligent use of data.
What to do?
Before looking at the how-to, make sure to understand what exactly it is you are aiming at given your specific context. Generally speaking, seamless data access, data integration, data quality, and data orchestration are seen as prerequisites to expand on digital capabilities.
In a digital economy, businesses must move away from just collecting, storing, and processing data in pre-defined ways. Focus needs to be on making effective use, i.e. operationalising data giving way for intelligent, flexible, and spontaneous data analysis driving direct impact on business performance. Non-intelligent, routine data management procedures should be automated as much as possible.
Undoubtably, data is a strategic asset. Used wisely and leveraging new technologies it allows for data-enabled learning across an entire organisation yielding results well beyond what insight from a selected-few can achieve:
monitor and optimise performance beyond financial metrics
drive customer experience
find growth opportunities
identify cost savings
Puzzled now? Asking yourself how to get from here to there? Good news is there is a proven track to follow. Developing an enterprise-wide data management strategy will guide the way.
Elements of a data management strategy
At this point it is important to distinguish between data management and a data management strategy. Whilst both are interlinked, they are not the same. It is the strategy that should drive the operational execution.
Best practices for data management are well established and documented in what is known as the DMBOK2. For those interested in more details please follow this link https://technicspub.com/dmbok/.
Best practises to develop a data management strategy, however, are not (yet) commonly established. Below is what I have come to see working well if one is to prepare for the development of a data management strategy.
Before going further keep one thing in mind. Developing a data management strategy must not be a costly, year-long exercise. Think in weeks, be and remain agile. Go for quick wins. Don’t strive for 100% perfection at the first go. Accept the fact that a good data management strategy will change as often as the business does. Life in a digital economy is changing fast and disruption is becoming more of a rule than an exception.
Step 1 – Align overall business strategy with data management strategy
Naturally, this is the most important step as it drives everything further down but more so because it lays the foundation of how well intelligent use of data across an organisation drives business performance. Done well, both business and data management strategies influence each other.
Think about business asking data: “We have bought this new line of business and want to offer their products to our existing customers. How can we get this done?”
Or, think about data asking business: “We can now predict the likelihood of customers to be interested in our new offering XYZ. Can we monetise this capability?”
Step 2 – Drive organisational change around data
Considering your current maturity of processes, people, and structures versus business ambitions what is it that needs to change?
Ask: “How can an enterprise-wide culture of data-enabled learning be introduced?”
The answer outlines if and what needs to change around data governance, i.e. who is responsible for what, who has access to what, how can confidentiality and compliance with legal requirements be ensured, and so on.
Step 3 – Leverage and manage data for strategic purpose
This is to confirm what information is needed to support both the business strategy and the aim of enabling intelligent data analysis. It is to understand whether it is about master data, transactional data, structured or unstructured data, analytical or modelled data, and most importantly, data quality requirements.
Think of scenarios like
“Our customer R has a positive credit record with our company but when we started to consider external sources we realised she defaulted on two loans.”
“Supplier S is demanding higher prices to continue doing business with us. We have to open up a tender process but need reliable information about product quality as part of our decision making process.”
Step 4 – Integrate different sources and coordinate data for meaningful use
Once data requirements are identified, the next questions are where can that data be found, where should it be stored, and how can meaningful consistency be ensured.
Think of scenarios like
“We know that customer A has different customer numbers in our various divisional/regional systems. How can we achieve an enterprise wide view of this single entity?”
“Different systems in our organisation have different validation means for address data. How can we ensure a consistent reliable quality of contact data?”
Step 5 – Define technology requirements
This is about the variety of different data formats available and how to make sense of it. Data may be provided from relational or columnar databases, all sorts of documents, XML, social media, pictures, and voice. Which technology is needed to make sense of this?
Think about business asking data: “We keep recordings of our customer service centre calls. Can we make sense of it beyond compliance or legal requirements?”
Step 6 – Identify quicks wins for a first implementation plan
With the data management strategy being developed quicks wins should be identified and respective implementation plans should be provided for decision making. This for rapid execution and benefit realisation.
In a digital economy data is the new currency and builds the core of the intelligent enterprise of the future. The ability to make intelligent use of all relevant data, i.e. creating a data-enabled learning organisation must become a mantra for all employees; not just for board members.
Free up capacity of your intelligent workforce by automating routine data management procedures as much as possible. Develop a data management strategy in line with your business strategy to guide your way towards becoming an intelligent enterprise. Aim at quick wins rather than perfection in the first go.
Don’t allow the development of a data management strategy to become a costly and long-lasting exercise. Remain agile. The notion of “nothing endures but change” is old but has never been more relevant than today.
Embarking on a data management strategy will lead the way towards a data-enabled learning enterprise and the intelligent enterprise of the future.
Modern technologies (cloud, mobile, big data, etc.) and methodologies (agile vs. waterfall) allow for faster deployments and unprecedented business opportunities.
Despite opposite promises many of us are observing a substantial increase in technological complexity requiring new and different skills at all levels of involved personnel. In parallel, digitization calls for reduction of organisational complexity. This is not an easy task for historically grown businesses. And all of this needs to be delivered faster than ever before without being granted the grace of a scope freeze. Why? Simply because business keeps changing faster than ever.
Does all of this change the fundamentals of how we run projects? Probably not. But it definitely requires shifting focus from deployment to preparation and planning.
We have seen the same paradigm shift happening in other industries like commercial construction (power plants, oil rigs, airports, etc.) before. Back in the days, construction projects spent most of the time in building with comparatively little time in planning. Market demands for cost control and schedule adherence have changed that.
Looking at troubled IT projects it is safe to say that unrealistic expectations and assumptions regarding time, cost, and risks are the most common causes for escalations or even failure. Combine that with a with “we don’t have time to do a detailed plan – let’s rather start with implementation quickly” you know where you are heading to. A project failing to plan plans to fail is what they say.
The call to action is not just to run good projects but to do it even better. Invest in solid preparation and planning. It is not only the best but at the same the most cost-effective way for your project to succeed!
If you need arguments to convince others talk to us.
If you want to know how get started quickly reach out to us.
If you are interested in a quick health check of your existing planning let us know.