ORIGINAL PAPERFuture software organizations – agile goals .docx

ORIGINAL PAPER
Future software organizations – agile goals and roles
Petri Kettunen1 & Maarit Laanti2
Received: 31 July 2017 /Accepted: 5 December 2017 /Published
online: 16 December 2017
# The Author(s) 2017. This article is an open access publication
Abstract
Digital transformation is rapidly causing major, even disruptive
changes in many industries. Moreover, global developments like
digital platforms (cloud) and IoTcreate fundamentally new
connections at many levels between objects, organizations and
people
(systems-of-systems). These are by nature dynamic and often
work in real time – further increasing the complexity. These
systemic changes bring up new profound questions: What are
those new software-intensive systems like? How are they
created
and developed? Which principles should guide such
organizational design? Agile enterprises are by definition
proficient with
such capabilities. What solutions are the current scaled agile
frameworks such as SAFe and LeSS proposing, and why? In this
paper, we aim to recognize the design principles of future
software organizations, and discuss existing experiences from
various
different organizations under transformations, and the insights
gained. The purpose is to systematize this by proposing a
competence development impact-mapping grid for new

digitalization drivers and goals with potential solutions based
on our
agile software enterprise transformation experiences. Our
research approach is based on the resource-based and
competence-
based views (RBV, CBV) of organizations. We point out how
most decision-making in companies will be more and more
software-related when companies focus on software. This has
profound impacts on organizational designs, roles and
competen-
cies. Moreover, increasing data-intensification poses new
demands for more efficient organizational data processing and
effective
knowledge utilization capabilities. However, decisive
systematic transformations of companies bring new powerful
tools for
steering successfully under such new business conditions. We
demonstrate this via real-life examples.
Keywords Digital transformation . SAFe . LeSS . Agile
enterprise . Systems thinking . Value streams
Introduction
Digital transformations are a cause of rapid and even disrup-
tive change in a majority of companies and future competitive
environments. Fundamentally novel models for organizations
and businesses (like Uber-type) are emerging, and traditional
companies as well must consider their structure and their roles
in achieving new business goals. Both the software producer
organization and the customer viewpoints should be under-
stood via comprehensive sense making. Companies now be-
gin to focus on software – either following strategy, or ad hoc,
when forced by competitive pressure imposed on them by
digitalization.

We view future competitive companies as agile and sus-
tainable, as well as more fundamentally software-based with
respect to both their outcomes (products and services) and
operations. For industrial-age companies such new principles
will require new organizational roles and goal setting.
Systemic changes (digital transformation) are complex to
achieve, but can be steered through by employing holistic
resource- and competence-based views.
When digital elements and data become increasingly incor-
porated, more and more software is included both in existing
and totally new processes in different organizations. These
questions are increasingly imperative for software develop-
ment organizations to comprehend, requiring new capabilities.
Is the only problem we are solving how to achieve faster time-
to-market by improving flow, or are there also other aspects to
consider? In this paper, we disentangle this question from the
organizational resource-based view. Software development
organizations have the added need to not only understand
the new systems to be developed, but also be able to create
* Petri Kettunen
[email protected]
Maarit Laanti
[email protected]
1 Department of Computer Science, University of Helsinki,
Helsinki, Finland
2 Nitor Delta, Finland
European Journal of Futures Research (2017) 5: 16
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http://orcid.org/0000-0002-2928-5885
mailto:[email protected]
and evolve the strategy, software and solutions to create them.
The strategy should impact on organizations, software sys-
tems development and human resource management (HRD).
Agile software methods (typically referred to as ‘agile
methods’ or ‘Agile’) have been utilized (‘agile transforma-
tion’) for a long time in many software development organi-
zations. Essentially, they realize in software development
what agile enterprises in general aim towards. Modern large-
scale agile methods and frameworks expand the basic agile
software development principles to the enterprise level.
Consequently, it is prospective to assess how these methods
and frameworks would support future companies when they
strive to become software-intensive.
Our primary focus is businesses in private sector, but also
many public sector organizations have similar considerations
when they digitalize their services.
Research propositions
In this paper, we operate with a dualistic view of software
organizations, and by software organizations we mean the
following:
1) Software firms / IT companies (or internal software R&D
units / IT departments) with new software production as
the core purpose
2) Software-intensive customer organizations of those soft-
ware producers, including traditional companies who re-
place parts of their systems or solutions with software and

need to understand what challenges that brings to
business
We operate from the premise that increasing digitalization
will cause most – if not all – companies to become software
companies [1–3]. Consequently, they turn into software orga-
nizations. Naturally the timeframes for such transitions vary
across industries, but for example in music and media busi-
nesses, it has already taken place. Future changes for the fi-
nancial sector could be even disruptive in the short-term (less
than 5 years) stemming for instance from the European PSD2
directive commencing in January 2018, while for example the
construction industry and healthcare sectors may expect
longer-term evolutions due to their different nature.
However, even entire current industry sectors and boundaries
(e.g., energy) are currently under digital reformation.
It follows that software use and its production will be more
and more intertwined, making future software organizations
interconnected in complex ways. Moreover, software systems
will be more dynamic and under continuous evolution, partic-
ularly in Internet of Things (IoT) environments.
Following this line of thinking, we posit the following re-
search propositions:
1. Digitalization broadens software use and software use
cases and creates new ecosystems. This will add on to
the complexity of software systems, systems interconnec-
tedness, and the value of software becomes more intrinsic.
& The complexity of the system increases (e.g., IoT).
2. Software companies must be prepared to master such new
concerns in order to be able to serve their customers
successfully.

& Software organizations may (have to) realize digital trans-
formations internally.
3. New kind of structures and roles / competences may be
needed to support agile and flexible development needs
and goals.
& There is a need to organize for (real-time) continuous soft-
ware evolution (architecture, organization).
In this paper, we develop and elaborate our initial ideas
presented in [4]. We compile a set of competence develop-
ment and resource impact mapping grids to address those
research propositions. The key idea is to define what (goals),
why (purpose), and how (roles) future successful software
organizations perform. Our research approach is design sci-
ence. The purpose of this design-scientific work is to construct
actionable artefacts (the grids) for future software organiza-
tions facing digital transformations. We validate them by in-
formed arguments and our real-life empirical experiences.
Different industrial companies can then compare and relate
their situational conditions and transformation circumstances
towards software-intensity accordingly.
Well-known scaled agile frameworks such as SAFe (Scaled
Agile Framework) and LeSS (Large-Scale Scrum) provide
some directions, but not a complete answer. How are SAFe
and LeSS tackling these systemic problems, and why have
these approaches been selected? The SAFe structures are in-
corporated in the grids. This reflects how (if) they currently
provide support in achieving the future performance traits of
software organizations in digitalization.
Drivers and needs

Complexity and speed
Complexity is inherent to modern software organizations.
This stems from two main reasons:
1) Multiple people and roles are needed to create total cus-
tomer value end-to-end.
16 Page 2 of 15 Eur J Futures Res (2017) 5: 16
2) Software product (system) use environments (in particu-
lar IoT) grow larger and more dynamic with many differ-
ent interconnected systems and actors.
Moreover, the software products themselves are often in-
creasingly technically complicated. While complicated systems
are not necessarily complex, their development and manage-
ment may impose complexity on the software organizations. In
particular, if the internal product architecture does not flexibly
support the necessary evolution of the customer value-in-use
for instance because of tight modular coupling, the technical
dependencies may require several different organizational ac-
tors to coordinate their decision-making and consequent ac-
tions in complex ways. Furthermore, software issues like tech-
nical debt and legacy system components may exacerbate this.
In principle, there are different archetypes of software sys-
tems as characterized in Table 1. It is crucial for software
organizations to understand their basic properties to be able
to develop and manage the software solutions accordingly.
Realizing their fundamental competence of is particularly im-
portant for future software organizations in the digital econo-
my of the Internet era [5–7].

Notably, the division (A-C) in Table 1 is in practice not as
clear-cut. Even in a mostly well-defined software project there
may be some less clear (uncertain) parts. Moreover, in large
long-lasting projects, the primary type may even change over
time [8]. This requires additional sensitivity and dynamic ca-
pabilities from software organizations.
Following that line of thinking, it is crucial for each soft-
ware organization to understand the complexity level of their
customer environment in order to be able to develop matching
levels of capabilities to deal with the complexities. Otherwise
there is a risk of producing a complexity gap, which may over
time even cause the total failure of the company [9].
Consequently, the internal complexity of the software organi-
zation should not be excessive, in order for it to be able to cope
with the external complexity with matching speed.
Scaled agile frameworks SAFe and LeSS extend agile
with systems and complexity thinking
Basic agile software development methods such as Scrum
have been in common use for more than a decade [10].
However, when entire product development organizations
adopt them, there are additional needs for larger-scale models
to take into account the aspects of organizational complexity
and speed [11]. The most well-known of such recent models
are LeSS and SAFe.
Organizational complexity, software complicatedness, and
product development speed are interrelated. In general, the
larger required development organization, the more complex
it becomes, which may even lead to a combinatorial explosion
of complexity [12]. Rising complexity of communication
scales with the size of large development organizations, and
so larger software organizations tend to suffer delays in deci-
sion-making. These delays lead to less flexibility and agility,

Table 1 Software solution natures and development principles
Customer
Space Problem
Type
Software (System)
Solution
Nature in Theory and Practice
Strategic Approach
A Well-defined Goals and requirements known in advance,
solution fully
specifiable
• Plan-driven software engineering and management
• KEYS: Time-to-market economically with optimal solutions
Except ill-defined boundary conditions
Example 1: Calculation of interest in banking software
(mathematically defined, ill-defined boundary

conditions such as number of needed calculations per
second or accuracy as number of digits in output.
Example 2: Implementation of a new law, e.g. in banking.
• Optimize for development risk. Example: Implement first
most crucial parts of the law (ones with most penalties).
Implement less risky parts later, closer to deadline in order
to avoid or minimize the risk of paying penalties.
B Ill-defined Success criteria and requirements uncertain,
multiple
possible solutions.
• Agile software development (accommodating uncertainty
and change iteratively)
• KEYS: Stepwise shaping following customer feedback to
converge for a mutually satisfactory solution
Example: developing new type of application • User-experience
driven;
• Example: Measure user retention and service usage and
develop or pivot accordingly.

C Wicked Problem changes over the life-cycle influenced by the
software solution interacting with the users and the
system environment.
• Evolutionary software development with continuous
experimentation and feedback
• KEYS: Continuous value definition and assessment
(assumptions),
core asset development and management, platforms and
ecosystems integration (co-creation)
Example: New product development, e.g., new fitness
device platform enabling customized software updates
• Surveying users and the ways they use the product and insert
new software
Eur J Futures Res (2017) 5: 16 Page 3 of 15 16
preventing organizations from communicating their objec-
tives and outcomes efficiently. This is increased by organiza-

tional and software technical dependencies (new built func-
tionality; technical, testing, defect, integration debts).
SAFe and LeSS approaches differ on this matter. SAFe
suggests a number of roles whose responsibility is to
manage the communication, e.g., Product Owners and
Product Managers who should communicate on backlog
contents at least twice a week. Another example is
Product Integration (PI) planning, where Agile Release
Train personnel gather together to discuss what they
should develop in next 10 weeks time.
This is where the LeSS and SAFe approach differ. In LeSS,
the aim is to scale down and try to manage with the smaller
number of development teams. This way, the approach allows
the organization to emphasize communication while scaling
down the sheer amount of it.
Automation can be used to make communication, and
therefore development faster (e.g., test automation for de-
velopmental software defect detection and correction to
decrease the lead-time from detection to correction, and
thereby reducing the risk for defect debt). In all, with end-
to-end transparency across the organization, the complex-
ities (possibly rigidities) with software and organizational

dependencies should become apparent. The systems dy-
namics for the overall speed can then be realized. The use
of automation, Continuous Integration and DevOps are
largely accepted in the agile software community, and
these techniques are also part of SAFe and LeSS.
So while both SAFe and LeSS approaches pursue the mas-
tering of development speed and complexity, the strategic ap-
proach is left for the company.1 Their answer to different
spaces in Table 1 is similar – scaled agile frameworks can be
used in all three cases. In business environments, software
organizations have multidimensional needs for speed [7, 13,
14]. Therefore, each software organization should understand
what their particular external speed requirements are, and how
the internal speeds contribute to that in total. This is what a
software company does when adopting some of these frame-
works, such as SAFe or LeSS.
Value flow
We maintain that the principal measure of software organiza-
tion is the customer value(−in-use). Consequently, the overall
performance objective of the software development and deliv-
ery chain is to achieve and sustain that value. In business
contexts, this must be done economically considering also

the exchange value and production costs.
There is no universal measurement of customer value,
and even for a specific customer the value is relative and
may change over time [15]. However, our premise is that
the customers will be satisfied when they experience (cus-
tomer experience, CX) value from the supplied products
(user experience, UX) and services considering the bene-
fits and costs. The goal of the supplier company is then to
provide that value, optimized with regard to the economy
of the company. Customer experience stems from the per-
ceptions of all the cognitive and emotional touchpoint
encounters (i.e., products, services, information ex-
changes, personnel interactions, etc) which may then af-
fect their future behavior (e.g., loyalty, repurchasing).
The role of software in the customer value creation
process (value-in-use) varies, depending on the customer
solution type. However, the role of software is growing,
even in many traditional physical products with more and
more embedded software (e.g., automotive electronics),
Bsmart^ devices, and in more general product / digital
service bundles. Software organizations should realize
the impact that this expansion in the roles of software
has in their specific digital transformations in order to

be able determine and assess the future customer value
constellations – which may be radically different from
the traditional ones [16, 17].
The size of the software organization matters [18], i.e.
in a small organization the entire software development
and delivery chain may be performed by a single (co-
located) team. For instance Scrum has only three roles
in order to create flow. There are no separate testers and
coders in Scrum, because everyone does what has to be
done, in order to get the Sprint release ready. In larger
organizations, typically multiple people and different roles
are needed to create an end-to-end value stream like illus-
trated in Fig. 2. For each particular software organization,
it is revealing to map the value stream flow backwards
(upstream) from the focal point of the customer software
use to realize all intermediate steps and exchanges, since
the customer value (−in-use) is only created when the
customer(s) can actually consume and use the software.
Like discussed above, the speed of the software orga-
nization depends on its complexities. Consequently, they
affect the overall time-to-value. It is thus essential to
realize the level of complexity in each software organi-
zation. Unnecessary complexities may then be reduced

systematically (e.g., organizational dependencies of
structural complexity).
Furthermore, keeping the software solution up-to-date and
continuously (even in real time) improved requires looping
flow incorporating the customer use feedback and other po-
tential sources of inputs [19, 20]. Achieving and maintaining
such continuous value flow requires end-to-end software or-
ganizational capabilities.
1 However, SAFe advocates that a company should create an
Economic
Framework that states how a company uses agility to enable its
strategy.
Scaled agile frameworks aim for creating a value flow
Basic agile software development methods such as Scrum have
been in common use for more than a decade [10]. However,
when entire product development organizations adopt them,
there are additional needs for larger-scale models to take into

account the organizational flow aspects [11]. Scaled agile
methods SAFe and LeSS embrace that line of thinking.
Large-Scale Scrum (LeSS) aims towards creating an orga-
nization that is able to optimize Value Flow through that or-
ganization by enabling a number of Feature teams to work
together using the Scrum method. Figure 1 illustrates this.
The Scaled Agile Framework (SAFe) aims towards creat-
ing a value flow and an economic framework for a company.
The key concept in SAFe is the Agile Release Train (ART),
which creates end-to-end value for the customer. For SAFe
transformation, it is essential to identify the value chain within
the company that creates the systems or solutions. The Agile
Release Train or Release Trains are then used to optimize
those chains so that all the people who work in that value
chain learn to work together. In a way, ART is a team of
teams-structure, enabling the people who create the same sys-
tems to communicate and synchronize frequently at regular
intervals. Figure 2 presents such a team of teams-structure.
Organizational capabilities
In sum, we have recognized the following needs for future
software organization capabilities:

& When smart products and services interconnect to other
such entities, cloud services (in particular, data), other sys-
tems and people, organizations need certain new compe-
tencies and abilities to utilize them:
Specific product / service design competences
The ability to combine them (including data analytics)
Holistic system design competence (including knowl-
edge and human factors)
& Business competence must be developed accordingly in
order for the organization to be able to fully utilize the
software-intensive design competences to gain total
large-scale business benefits in new digital environments
and economy.
One of the key consequent questions is how to select and
measure appropriate business key performance indicators
(KPI) (e.g., the contribution of embedded software in the
product sales and export).
& Each software organization should first and foremost com-
prehend what types of software it is developing in what
environments (c.f., Table 1). The competences and capabil-

ities of the organization should then be fitted accordingly:
The assessment of matching speed requirements
Particularly in the environments of the new Internet
era, these capabilities (type C in Table 1) entail new prin-
cipal traits for software organizations. As external systems
complexity increases, which is mostly uncontrollable (e.g.
IoT), systems thinking, analysis and engineering capabil-
ities are needed to cope with it. Internally, there is a need
to organize for continuous (real-time) development and
continuous delivery (CD) with flexible architectures
(technology, organization) guided by the new overarching
software paradigms [6]. Basic engineering approaches
need to be augmented with capabilities to accommodate
mathematical and social complexities [21].
Fig. 1 Software organization design framework of LeSS
Vision of future software organizations

Matching speed matters
There are two dimensions of externally observable speed of
software organizations: outbound and inbound (c.f., Fig. 2).
The former concerns the value delivery to customers from the
starting point (customer order or opportunity identification),
and the latter spans from the input recognition (e.g., customer
complaint or environmental signal) to the information pro-
cessing and responding appropriately.
Considering development and the release speed in business
contexts in general, every feature and product or service has a
window of opportunity – if you are on the market at the right
time, you will generate more revenue than those who enter the
market later. If people are happy with your product / service,
you can use the revenue to improve the service / product and
keep the competitive advantage – it will be more difficult to
enter the market later. Lean and agile methods both aim to-
wards rapid cycles of development, fast returns on invest-
ments, and minimal inventories of work in progress.
Taking the stance that time-to-value (−in-use) is the overall
performance goal, there are different needs and means for
speed in different types of software described in Table 1 (A-
C). Following that line of thinking, Table 2 outlines the key

aspects of speed for each archetype. With type A the main goal
is fast execution based on known specifications while in type
B uncertainties should be reduced as soon as possible, in order
to converge towards an acceptable software solution.
However, in type C there is no definite end criteria and the
software organization must continuously stay in sync (even
real-time) with the software in its use environment.
Consequently, fast software development and release speed
has multiplied enabling roles by providing time-based com-
petitive advantages:
& Facilitating more effective value capture (type A, B) –
potential first-mover advantages
& Incorporating more and faster feedback (type B, C) – bet-
ter responsiveness (agility)
& Supporting continuous experimentation (type B, C) –
more experiments possible within limited time periods
Proficient software organization designs achieve
speed by continuous development flow and avoiding
complexity hindrances

Proficient large-scale agile software development coaches al-
so advocate the following rules in order to gain development
speed and effectiveness. These rules follow the value flow
view outlined in Fig. 2 and the consequent needs and means
for speed in Table 2.
1. Information must flow as efficiently as possible to all
needed people; preferably broadcasted at regular in-
tervals – to avoid communication debt i.e., explosion /
missing information.
& This also applies to arranging regular demos in order to
spread information on the latest updates in the system
under development to the whole organization.
2. New software code must be integrated as fast as pos-
sible and be immediately available to all people –
using automation (and continuous integration (CI)
systems) to keep the amount of currently ongoing
changes in the code small.
3. Testing must be planned and executed parallel to devel-
opment, feedback should be as fast as possible, and the
amount of open defects should be kept into minimum to
avoid the accumulation of testing debt.

4. Defects must be fixed as soon as discovered, in order to
avoid error debt.
5. Architecture should be as simple and modular as possible,
in order to avoid technical debt.
Fig. 2 Multiple people and roles
needed to create end-to-end value
flow in larger organizations
& This enables faster integration (2.) and better testabil-
ity (3.)
6. Keep documentation up-to-date – to avoid documentation
debt.
& This facilitates information flow (1.)
7. Systems that are used to build the systems must be up-
dated to latest versions and kept up to date in order to keep

competitive / (interface) compliant.
Interestingly enough, speed targets can be achieved and
improved at least partially by avoiding delays. Both SAFe
and LeSS promote Feature teams and removal of waste
for maximizing flow. However, in practice the Feature
team composition requires multiple overlapping skills
for the development teams as well as in-depth knowledge
of all the developed code. Thus using only Feature teams
may not be a practical solution.
The Feature teams are a preferred solution in agile software
development for gaining speed in order to avoid dependencies
between components and thus between development teams.
While certain dependencies are intrinsic in large-scale soft-
ware organizations, the key to speed is to avoid unnecessary,
excessive (even combinatorial explosion) dependencies cause
for instance by structural complexities in organizational
decision-making hierarchies. The following are some organi-
zational design patterns to accomplish this:
& Work organized as component teams: The traditional way
of managing work is to split complex solution problems
into (fixed) architectural layers and develop each layer
separately. This may cause integration problems and

non-fitting components.
& Work organized as feature teams: The new way is to speed
up by developing functionality to all layers simultaneous-
ly – and to integrate frequently and manage the technical
dependencies during development with end-to-end real-
time transparency and visibility supported by design and
integration automation.
Key measurements
Is the only problem we are solving how to achieve faster time-
to-market by improving flow [22]? Our contribution is to ad-
vance from this basic question in two ways for future software
organization performance analysis and improvement as
highlighted in Fig. 2. Considering the time-to-market, we are
stressing time-to-value(−in-use). With respect to the internal
development flow we extend outside the focal organization to
the business environment where the customer value is actually
determined, created and assessed in real time.
Following this line of thinking, we suggest two principal
measurement categories (KPI) for software organizations:
1) VALUE ECONOMY:

& Right customer value delivered economically (quality, us-
ability of service / product)
2) REAL-TIME BUSINESS:
& Responsiveness to customer feedback and software use
data
& Sensitivity for new value-creation and business opportunities
For those principal measures we need to define expres-
sive indicators, in order to be able to tell whether the
software organization is really capable of attaining those
performance targets.
A BPeople first^-attitude is characteristic for any Agile
or lean organization. Many organizations, such as Valve,
let employees decide which project they want to work on,
thus leaving the choice of which is the right project to the
employees. Others try to inquire this from the market,
e.g., by releasing alpha or beta releases to specific mar-
kets that forecast the market behavior on larger market
areas. For these reasons it is typical for game software
developers to release in Canadian market before entering

the global market. Even in large companies, the em-
ployees may be in the frontline knowing and serving the
customers they interact with, and so we introduce
Table 2 Needs for speed in software organizations
DRIVERS for Speed NEEDS for Software Competences and
Resources / Roles
A Lean (streamlined) product development and delivery flow
end-to-end • Stable software bases (e.g., manageable technical
debt)
• Efficient development and delivery automation
B Fast absorption of feedback and consequent adaptation •
Flexibility in software technical design (architecture) and
management
• Organization design for rapid learning loops
C Continuous sense-making and action in emergent
environments
with interactions of various objects and actors
• Sensing and responding with intelligent use of heterogeneous
data from

diverse sources
• Continuous software-oriented business processes (e.g.,
ecosystem
and asset strategies)
additional metrics tailored especially for service busi-
nesses (VALUE ECONOMY):
3) EMPLOYEE SATISFACTION:
& How happy the employees are in the current company
& How proud the employees are of their product / service
4) CUSTOMER SATISFACTION:
& Would the customers recommend our services / products
(UX, CX)
& Brand value

Metric 3 leads to the acquisition of the best talent in market
– which in turn will help boost performance as the best em-
ployees deliver an order of magnitude times more than an
average (less-motivated) person, Metric 4 helps in mastering
the networking effect, i.e., be the recommended service or
product vendor. It has been studied that in the software indus-
try the network effect is key to winning over the market [23].
The network effect is one of the reasons why typically one
software vendor gains a monopoly position, along with a sec-
ondary Boverflow^ vendor, while other minor vendors only
receive small fractions of the market [24].
When a market is volatile, it is generally better to use
leading indicators that forecast market behavior, than lag-
ging indicators (REAL-TIME BUSINESS). This is espe-
cially important when a company starts new business or
new activities or when a company is new (i.e., start-up).
When software deliveries are of a continuous nature, an
additional major leading indicator is:
5) CUSTOMER RETENTION:
& How many of the customers return to service
& How often the customers return to service

For a continuous service business it is also important to
monitor the availability of the service. Service organizations
may even use the big data and forecasting to detect errors, e.g.,
if an internet shop is implemented using micro services. And
thus we need additional metrics:
6) SERVICE AVAILABILITY:
& How many customers are currently using the service com-
pared to the typical number in respective conditions
& Service interruptions, speed of operations
Such data could be used even to decide if the service pro-
vider should roll back to previous version of the software.
With DevOps practices more and more companies are able
to have automatic integration, deployment and service level
control. With automation, companies also typically would like
to go for smaller and smaller release sizes to reduce the within
each new release and thus make thousands of releases per day,
like Amazon, Google or Facebook. With these mini-releases it
starts to become also more typical that companies also invest
in automatic rollback of the previous versions, if something
goes wrong with the release.

Notably none of these proposed measures (1–6) are
strikingly new nor unique to software organizations.
However, what is foundational is the realization of new
factors and rules for them caused by software. For in-
stance customer satisfaction (4) has been a traditional
business KPI for years but now the sources of
(dis)satisfaction are often more and more software-based
or software-enabled (e.g., driver assistance systems in au-
tomotive). Moreover, many traditional cost structures may
change radically when physical product components and
manufacturing operations are replaced by software ele-
ments. In particular, the economies of scale are fundamen-
tally different when it comes to software. Also the time
scales may become vastly shorter, and supply chain man-
agement rules change when physical, but connected prod-
ucts can be field-updated with software even remotely and
customer feedback data can be collected from many
sources automatically.
Capabilities
Established organizations base their business typically on one
established business innovation or idea. This is known as ex-
ploitation [25, 26]. A typical established organization can try

to streamline its value chain and cut costs by using lean
methods, yet keeping the same quality as before. Similarly,
established large software organizations can streamline their
development operations using scaled agile frameworks.
Organizations can try to create new revenue streams with
the help of innovation. Quite often bringing new innovations
to market per se is not possible, but market space needs to be
carefully explored before, in order to find out what kind of
products and services could fit in the market. An established
organization may try to create directly radical innovations, or
employ a rapid innovation-exploration cycle with the help of
automated continuous integration and delivery systems in or-
der to explore the market needs and available opportunities.
An established organization may also try to avoid costs by
replacing a part of the value chain with software.
Novel software start-ups typically start from the explora-
tion phase, using lean startup methods or user experience
driven agile software development. Successful software
startups focus on following customer satisfaction and custom-
er retention as key metrics (c.f., chapter Key measurements).
As start-ups grow and mature, the brand value, and the ability

to scale up the start-up-like operational mode become keys to
maintaining successful operations.
Figure 3 presents a summary of these discoveries. In
essence, it is a grid of key strategic capabilities for soft-
ware organizations in different business situations. The
strategic moves are based on certain software capabilities
like described above, and – consequently – possible capa-
bility gaps may prevent organizations from realizing such
moves. It is thus crucial for different companies
transforming towards software organizations to acquire
and develop such new software capabilities in order to
be competitive in the future.
With increased competition, the challenge for
established companies is to move from the exploitation-
only mode to exploration [26, 27]. Buying a few promis-
ing startups and integrating those into established compa-
nies has not been proved to be a good strategy, as most of
these kind of company acquisitions fail. Modern compa-
nies try to implement agile methods to create a corporate
culture within the company that would better support ex-

ploration and software-enabled innovation, but their chal-
lenges lie in what kind of future organizational structures,
ways of working, management and investment models
and calculations could support this [17].
Following this line of thinking, we expect the follow-
ing core capabilities for software organizations (c.f.,
Tables 1 and 2):
1) High-performing (speed) software development and de-
livery engine (technical and structural)
2) Rapid (continuous) innovation with software
3) Proficiency at dealing with software-intensified cus-
tomers / users
4) Scaling with Internet-era software-based systems and
assets
Notably our suggestions in the chapter Key measurements
indicate those traits.
Transforming

Digitalization changes
Digitization, digitalization, digital transformations and the
general concept of digital, are more prevalent and omnipresent
(e.g., cyber-physical systems, CPS). Strikingly, this phenom-
enon does not concern just developed countries and econo-
mies, but also developing areas (e.g., mobile technology in
Africa) – often more fundamentally.
For most companies, if not all, this causes needs for
organizational changes towards software organization to
various degrees. For current IT companies / departments,
this could be developmental or transitional change, while
Industrial IoT for instance brings even radically disrup-
tive, transformational changes to software organization
for many companies in traditional industries. The role of
IT is to be both a driver and an enabler [9].
Consequently, each (new) software organization should
be able to deal with such new factors as digital / (smart)
products / services and digitalization in product market-
ing, design and production (manufacturing). Furthermore,
even fundamentally new, software-enabled business
models based on for example open APIs will be possible.
For instance brick-and-mortar shops and other physical

infrastructure and CDs as software distribution media
have been costly. Delivering digital (or physical) goods
via Internet costs less, and subscriptions can happen more
often (e.g., newspapers) [28].
Table 3 categorizes those traits for future software organi-
zational changes. It follows that there are needs for new com-
petences and resources to develop and implement the related
core capabilities introduced in the chapter Capabilities (1–4).
Digitalization enables
Future software organizations have digital innovation op-
portunities both internally and externally like outlined in
Table 4. However, in order to be able to realize them,
there are needs for new competences and resources to
develop and implement the related core capabilities in
the chapter Capabilities (1–4).
In addition, overall customer / user experiences can be
developed with the guidance of external data and internal
real-time measurements [5]. Customer retention is one of the
key consequent business performance objectives (c.f., chapter
Key measurements).

The meaning of future software organizations
in digital transformations
The overarching consequence of digital transformation is
that more and more software organizations will beFig. 3
Software organization strategic capabilities grid
created and formed in the future. Hardly any industry
sector will be totally unchanged. On the contrary, many
traditional industries are already facing radical changes
with software, and new software-enabled cross-industry
networks are further blurring the boundaries (e.g., smart
energy transition).
It follows that companies in their particular digital
transformations should reflect on themselves as software
organizations. In Tables 3 and 4 we have presented arche-
typal software-related questions to consider. We stress that
each company should be able to give conscious answers
to those strategic considerations in order to be able to
develop the consequent critical software capabilities for

successful transformations. Moreover, they should also
be frequently revisited, because digitalization is continu-
ously shaping competitive environments, while the devel-
opment of organizational capabilities may take time.
Results and experiences
In this section, we present a real-life case of software organi-
zational change. The case is about extreme speed and service
quality needs of the Yle Graphics Team, which reflects many
future software organizational aspects of our present research.
The example organization impacted by digitalization is Yle
Graphics design. They are responsible for providing variety of
graphics like logos, animations, drawings and any kinds of
graphics that are needed in various broadcasted and internet
productions, such as news, television series, webpages etc.
Digitalization has transformed traditional manual work
and brought in many new tools and also new techniques.
The ease of making new graphics has resulted in an in-
crease of graphics in both traditional broadcasted media
and also services available online, thus transforming the
nature and scope of the work.

Table 4 Opportunities of future
software organizations Enabling NEEDS for Software
Competences and
Resources / Roles
Cost innovation:
• Same service or product can be implemented, provided
and serviced with a lesser cost but similar quality.
• Moving digital data costs less than moving physical goods.
• Software component in goods allows reduction of the
production costs compared to physical / hardware components.
• Shared computational services / more IP-addresses
enable to enlarge the networks and computational
capacity – and e.g. new business with shared services.
• Thinking whole chain from production to consumer
some steps can be streamlined for business
opportunities.
• How could software change Your

company (industrial engineering and
operations management) [2, 32, 33]?
• CAPABILITIES: 1) 4)
Business innovation:
• smart products and services
• new business models in digital economy
• What is the role of software in Your
industry going to be [3, 5, 30, 34, 35]?
• CAPABILITIES: 2) 3)
Table 3 Factors of future software organizational changes
Changes NEEDS for Software Competences and Resources /
Roles
Digitalization changes former physical goods … into abstract
form. • What is the role of software going to be in Your
products / services [3, 5]?

• CAPABILITIES: 2)
In physical form, the domain knowledge
has been essential.
Domain knowledge becomes hygiene;
knowledge on meta-level is essential (who
builds the platform).
• What software will contribute to Your customer
value creation [6, 29]?
Old players have a challenge to use
the digital channels.
Automation reduces transaction cost.
Delivering digital (or physical) goods via
internet costs less, and subscriptions can
happen more often.
• How does software change Your demand / supply
chain [9, 30, 31]?

The market could change or extend
because of digitalization.
New players (having software background)
have been able to enter to digital market.
• What software companies will be Your prime
competitors / collaborators and what are their key
competitive advantages [3, 28, 30, 32]?
Managing this kind of rapidly changing work and needs
(customer requests and requirements) is extremely challeng-
ing even while serving only internal customers within the
same company. New requests pop up daily, and changes in
needs happen constantly. Most of the needs have a strict dead-
line, and if the graphics are not available on time of the sched-
uled broadcast or show, the opportunity is lost.

Before lean and agile methods were taken into use (i.e.,
before agile transformation) in this organization, the majority
of the projects were made by one person only, and lasted less
than a day. On the other hand, a small amount of the projects
were repeated on a weekly basis, which continued for years,
like producing graphics for a series of productions.
The challenge was to weigh how much and which projects
could be done with internal people, and where and how there
was a need for external freelancers. Another challenge was the
number and variety of different tools used and new tools
emerging and developing constantly. Designers were familiar
only with their own relevant tools and techniques, and none
were masters of all.
Figure 4 represents a specific Kanban board based on Agile
and lean thinking that we helped the graphics team with to
visually manage and schedule the work assignments. It en-
ables the team to see and discuss all the upcoming assign-
ments and to discuss who are interested in which assignments.
The board brings all information needed to manage the
work together with the people that do the work into one place.
Having visibility and an open discussion enhances coopera-

tion and teamwork. After taking this board into use, most of
the assignments are now done as teamwork, which is more
fun, more efficient, and allows cross-using different tools and
techniques. Because of this change the graphics teams have
decided that they will no longer do any project alone as one-
man tasks but will do all future work as a team.
The Yle Graphics organization is an example of an organi-
zation that has already changed due to digitalization, and can
thus be used as an example of future organizations. Main
existing traits are:
1. It is responsive, flat and cross functional with frequent
communication.
2. Traditional mechanisms would be too slow for managing
it – only visual management adopted from lean and agile
software development culture enables responding to cus-
tomer requests with enough speed – even though it is not
developing software, nor is it an IT organization.
3. Regarding our chapter Key measurements, the key met-
rics are geared towards customer satisfaction – tier 1 (im-
mediate internal customers) and tier 2 (users of broadcast-

ed and internet media and services).
Discussion
Strategic changes cause a need to change value
streams and the organization
Like illustrated in Fig. 2, we envisage that the overarching
organization design principle of future software organizations
is to organize and optimize for developing and delivering
software-enabled customer value (in-use) economically.
Consequently, software-intensive value streams become key
vehicles requiring new software-oriented value stream man-
agement capabilities (c.f., Table 2):
& A fluid organization should be organized around the value
stream.
& An adaptive organization should be able to quickly align
itself along the new value / revenue stream:
Cause minimum disturbance in organization and team
structures and allow the organization to self-morph into
new needed state.
Allow learning of new (needed) competences.

& A flexible organization is extending and relying on 3rd
party suppliers.
Moreover, with such new capabilities, the software organi-
zation can impose new strategic changes with modifications in
the value stream. Value streams may be combined or changed
in particular based on software platforms. New startups and
ecosystems create new value streams, which could build on
Fig. 4 Board for flexible work/teams allocation in Yle Graphics
Design,
following lean and Agile principles
open platforms of incumbent companies (with open applica-
tion programming interfaces, APIs).
One of the key questions of such future software orga-
nization design is whether to base on self-organization or
imposed structures. While traditional organizations rely
on imposed structures, we have had some trials for self-

organization. Organization can be a subject of continuous
evolvement, and people who do the work can propose and
accept changes to structures.
Furthermore, when products become more software-inten-
sive, the value streams are increasingly reliant on data / infor-
mation. That is, when future companies become more soft-
ware-intensive, they will need more efficient internal data
processing and effective knowledge utilization capabilities
(incorporating data science). More input data (feedback) can
be received from the products/services-in-use (even real-
time), and various new external data sources (e.g., IoT) should
be scanned to stay in sync with the environment and its busi-
ness networks. External outputs of the value stream may be,
not only products and service features, but increasingly also
data. All this changes the organizational dynamics of the value
stream towards real-time functionality, as data (information)
transfer can be fully digital.
Insights and foresights
Software-intensification is a megatrend. The use of software
components transforms both the existing products and goods,
but also changes how work is done more cost-efficiently with
the help of software (like in our Yle Graphics case, chapter

Results and experiences). This will lead to:
1. Use of lean and agile software management methods
in other than software organizations due to increased
speed. 11th state of Agile survey (Version One, 2017)
already reported a growing number of non-software
companies using agile methods [10]. In fact, only
36% of all companies were software-only companies.
Also many traditional industrial companies (e.g., au-
tomotive) are increasingly looking for them when
they are becoming more software-intensive [3].
2. More networked organizations for additional flexibility
3. Software is common. Creating new software products or
services becomes more challenging.
4. Digitalization continues and changes former local busi-
nesses to global, increasing competition
Following this line of reasoning, we can elaborate our vi-
sion (chapter Vision of future software organizations) conse-
quently as follows. This puts our stated needs for future soft-
ware organization capabilities into a larger context, thereby
rationalizing them further.

Traditional management methods emphasize quality and
price, and aim towards markets of economy (i.e., the larger
the customer base, the cheaper the single product price is).
Traditionally, organizations are managed as projects that are
measured for being on time and within budget.
When companies face the challenge of digitalization, the
market is being disrupted. This enables new players to enter
the market place. This is visible e.g. when examining how
digitalization has changed the travel business. New companies
that operate only in network have entered to the market while
some old players have vanished. Using software platforms as
a mechanism to offer their service, new digital players are able
to offer better or more focused services with less costs and
with significantly less human workforce involved. The key in
how to be successful in digital business is to focus on having
the right service with better usability in place. The old project
mode is replaced by the continuous offering of the service.
The same trend is visible also with mobility and IoT disrup-
tions as these businesses are also software businesses.
When digitalization has fully happened (like it has in the
travel business today), the value chains are already very cost
efficient with the help of created software. The markets have

been re-distributed, and new digital brands have been created.
New efficient players are able to dominate the markets by
offering services with lesser prices. While at first glance, soft-
ware, internet and digitalization seem to enable globalization
and fewer but global players (such as Amazon offering books
throughout the western world and Google offering services in
multiple areas from data to books and mobile phone operating
systems) it is not yet clear if the future will be dominated by a
few global players only. The internet is also enabling long tails
on businesses, i.e., enabling niche groups to reach special
services and a wider variety of offering than what we have
seen ever before. Current provider ranking services rate com-
panies and their services based on price, but it could be of
equal possibility that we start to rank companies by a multi-
tude of values, and select those providers whose values match
ours. Few digital services, like Zero Waste listing companies,
who offer products that create less or no waste or various fair
trade shops are examples of this possible future.
Figure 5 presents a summary of these findings of how dig-
italization changes businesses and the needed capabilities
within organizations as well as their business models (c.f.,
Tables 3 and 4). In effect, it outlines strategic road mapping
towards future software organizations reasoning our submis-
sions in the chapter Research propositions.

Many challenges lie ahead, as many companies have trou-
ble understanding the actual impacts of digital disruption for
their businesses in the future complexities of the software
world. When software is increasingly embedded and ubiqui-
tous, people connect ever more with systems and with each
other on many different levels (socio-tech-economic-environ-
mental). Moreover, the connections are often real-time
(Internet of Everything, IoE). These trends bring up totally
new opportunities but also challenges for software develop-
ment organizations, which have traditionally designed specific
IT systems and separate software products.
It is hard to forecast where these changes will lead. While
some people state that the future will lead to a singularity of
some rare giant global players, learning the new management
rules may help great local players and value-based economy if
the consumers start to value more than just the price. With the
use of software the whole value chain can become transparent
– and thus the consumers may refuse to buy unethically pro-

duced goods or services. Equally, what will the future of work
in software organizations be like, and what shall next-gen
employees expect from their employers – given the consider-
able lack of competent software professionals?
From our point of view, future research interests in-
clude visualizing software organizations like depicted in
Fig. 2. How can the invisible and intangible nature of
software be illuminated, particularly in traditional compa-
nies transforming towards software organizations (c.f.,
Fig. 4)? Future research will benefit from including the
measurements from chapter Key measurements. Further
cases (chapter Results and experiences) would strengthen
the validation on our design artifacts proposed in this
paper. Future research may also include comparative stud-
ies with scaled agile frameworks (SAFe) [36, 37].
Implications
Based on the projected strategic changes value streams and the
organization need to change, as well as the envisioned core
capabilities (chapter capabilities) for software organizations.
Table 5 suggests overall organizational change strategies for
different types of organizations towards software organiza-

tions, which imply needs for new software competences.
It is imperative to realize that the particular context of the
company affects the nature of the software organization. For
instance media companies (like our Yle case) with new digital
multichannel productions, power distribution companies of-
fering real-time customer web displays of their electricity dis-
tribution situation, and paper machinery manufactures
Fig. 5 How digital disruption changes companies, their business
models
and needed organizational capabilities
Table 5 Change strategies for software organizations
Goals Means NEEDS for Software Competences and Resources /
Roles
• If you are a big company: How to
make your structures lightweight,
and increase flow through the
system?
By fluidity:
• Decouple product architectures and teams.

• Reduce organizational layers and move
to flat organization(s).
• Brake new product / service initiatives into
smaller chunks (e.g., microservices).
• Develop using smaller batches.
• Flexibility in software systems architecture and
organization design
• Feature teams, cross-functional teams
• Unanimous prioritization of work
• If you are a traditional company:
Understand the opportunities of
cost reduction and innovation
By adaptability:
• With the use of software
• With modularity and cross-use of components
/ systems of systems
• With integration of new software capabilities

into existing systems
• Software-based value determination, software as the
key enabling technology (KET)
• Enlarging to new software-enabled business
opportunities,
new markets, new areas / technologies
• Forming new alliances / co-operation (e.g., with
software houses
• In ecosystem (digital economy): By flexibility:
• Build and streamline value streams for cost
efficiency and new value.
• Create efficient subcontracting and supplier
networks.
• Determine the (software) platform strategy
(create platforms and/ or use available ones).
• Data systems (e.g., big data, APIs)
• Value co-creation based on software core assets

• Value creations based on wide offering (ecosystem)
• Value creations through better software-based service
(customization, predicting service interval, informatics,
accumulated data from system or users) with value net-
works
offering remote condition monitoring services may each re-
quire new capabilities and consequent competence profiles
compared to their current organization designs and ways of
working. Notably many traditional competence descriptions
and role titles may have to be specified (e.g., software project
manager, business analyst).
Moreover, there are needs for new overarching and
integrative digitalization competences and organizational
capabilities:
& T-shaped competence
& Bridging capabilities

For example, the Industrial Internet of Things (IIoT)
R&D requires new multidisciplinary approaches combin-
ing industrial automation, computer science, data commu-
nications, instrumentation, mechanical engineering and
process technologies.
In general, ITcapabilities are essential parts of digital trans-
formations [9]. However, we posit that future software orga-
nizations need not only information technology, but also
higher-level software capabilities for deep transformations.
While developmental and transitional organizational changes
could be achieved by merely shaping the current structures
and processes, truly transformational changes require
revisiting and challenging the fundamental business assump-
tions and organizational culture possibly stemming from the
industrial age. Failing to recognize the new software-driven
changes in the business rules, and what level of agility is
needed in different industries may lead to poor competitive-
ness [28]. It follows that agility is a strategic organizational
design decision [11, 38, 39].
Conclusions
In this design study paper, we have examined what particular
capabilities (competences, resources) future software organi-

zations need and why. Based on this, we presented our vision
for such organizations and outlined the transformational path
towards it. The real-life case of Yle Graphics illustrates some
of those aspects in practice. In conclusion we have discussed
what future changes companies should be able to foresee in
order to be able to develop the necessary future capabilities
when most companies become software companies.
Modern scaled agile frameworks SAFe and LeSS offer
certain solution schemes for realizing those future software
organization goals. The essence is to understand what partic-
ular key activities should be conducted in such organizations
and how. That is, rather than stressing certain roles, we elevate
the strategic design of the organization to a higher level, to
comprehend how they contribute to the overall performance
goals of software organizations.
Industrialism created organizational hierarchies and the
benefit of scale. The Internet brought networks, and the ben-
efit of connectivity and digitalization. We refrain here from
presenting future scenarios, but it is striking to compare and
contrast different industries of today. For instance, some me-
dia business companies are currently struggling with
transforming their traditional businesses and operations to
the new digital business models, and many manufacturing

companies and industrial equipment providers are increasing-
ly extending their offerings with software-enabled services.
More generally, deep tech digital increases, as digital work-
forces and digital humanities are profoundly shaping both the
software organization internal, as well as the external custom-
er worlds. Sapient leaders for future software organizations
are called for, like we have aspired in this paper.
Publisher’s note Springer Nature remains neutral with regard to
juris-
dictional claims in published maps and institutional affiliations.
Open Access This article is distributed under the terms of the
Creative
Commons Attribution 4.0 International License (http://
creativecommons.org/licenses/by/4.0/), which permits
unrestricted use,
distribution, and reproduction in any medium, provided you
give appro-
priate credit to the original author(s) and the source, provide a
link to the
Creative Commons license, and indicate if changes were made.

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funding/programmes/programmes-20152017/disruptive-
technologies-and-changing-institutions/ddi

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https://aaltodoc.aalto.fi/handle/123456789/16540Future
software organizations – agile goals and
rolesAbstractIntroductionResearch propositionsDrivers and
needsComplexity and speedScaled agile frameworks SAFe and
LeSS extend agile with systems and complexity thinkingValue
flowScaled agile frameworks aim for creating a value
flowOrganizational capabilitiesVision of future software
organizationsMatching speed mattersProficient software
organization designs achieve speed by continuous development
flow and avoiding complexity hindrancesKey
measurementsCapabilitiesTransformingDigitalization
changesDigitalization enablesThe meaning of future software

organizations in digital transformationsResults and
experiencesDiscussionStrategic changes cause a need to change
value streams and the organizationInsights and
foresightsImplicationsConclusionsReferences
Research Article
Improved Path Planning and Attitude Control Method for Agile
Maneuver Satellite with Double-Gimbal Control Moment Gyros
Peiling Cui,1,2 Jingxian He,1,2 Jian Cui,1,2 and Haitao Li1,2
1School of Instrumentation Science and Optoelectronics
Engineering, Beihang University, Beijing 100191, China
2Science and Technology on Inertial Laboratory, Beijing
100191, China
Correspondence should be addressed to Peiling Cui;
[email protected]
Received 4 November 2014; Revised 2 February 2015; Accepted
8 February 2015
Academic Editor: Mohamed Abd El Aziz

Copyright © 2015 Peiling Cui et al. This is an open access
article distributed under the Creative Commons Attribution
License,
which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.
Double-gimbal control moment gyros can implement the
satellite attitude maneuver efficiently. In order to reduce the
energy
consumption of double-gimbal control moment gyros and avoid
the singularity state, an attitude maneuver path planning method
is proposed by using the improved Fourier basis algorithm.
Considering that the choice of the Fourier coefficients is
important
for the Fourier basis algorithm to converge quickly, a choosing
method of the initial Fourier coefficients which can reduce
the computational time of the path planning algorithm notably is
proposed. Moreover, an attitude-tracking feedback controller
based on the Fourier basis path planning algorithm is designed
to acquire robustness. Simulation results show that the proposed
path planning algorithm can implement attitude maneuver path
planning in shortened time. Meanwhile, the feasibility of the
attitude-tracking feedback controller which is based on the
above path planning algorithm is verified in terms of the low
energy

consumption, high attitude-tracking precision, and the safe use
of double-gimbal control moment gyros.
1. Introduction
High-resolution earth observation demands the satellite to
have the ability of rapid attitude maneuver. Therefore, control
moment gyros (CMGs) which can output large and precise
torque are ideal attitude control actuator for the agile maneu-
ver satellite. The main problem of using CMGs is the existence
of singularity state, at which CMGs cannot produce torque in
a certain direction. According to the gimbal numbers, CMGs
can be divided into two classes, including single-gimbal
CMGs (SGCMGs) and double-gimbal CMGs (DGCMGs).
The singularity avoidance steering law is very important
for SGCMGs to fulfill the requirement of the rapid attitude
maneuver. Compared with SGCMG, DGCMG has more than
one degree of freedom, and its angular momentum envelop is
nearly spherical. Therefore, it is believed that DGCMGs can
implement the rapid attitude maneuver with high efficiency.
Existing attitude control logics with CMGs are composed
of attitude control laws and CMG steering laws [1, 2].
According to attitude tracking errors, the desired attitude
control torque is computed by the attitude control laws.

The objective of the CMG steering laws is to avoid singularity
states. A large-angle attitude maneuver control law based
on nonlinear methods is proposed in [1], and a singularity
robustness plus null motion steering law is designed to ensure
DGCMGs against singularity. References [3, 4] investigate on
the singularity avoidance steering law specially. A modified
singular-direction avoidance steering law of SGCMGs is
introduced in [3]. Kennel presents the vector distribution
steering law for parallel-mounted DGCMGs in [4], which
makes use of redundant degrees of freedom of DGCMGs.
However, when the CMG steering law is separated from
the attitude control law, CMG singularity problem and energy
consumption cannot be considered in the computing process
of attitude control torque. In addition, there exist singularity
states which cannot be avoided by CMG steering laws. To
deal with the above problems, the attitude control and CMG
steering law should be integrated together as a whole control
system.
An effective method of integrating the attitude control law
and CMG steering law together is to plan the attitude maneu-
ver path according to the satellite maneuver characteristic.

Hindawi Publishing Corporation
Mathematical Problems in Engineering
Volume 2015, Article ID 878724, 11 pages
http://dx.doi.org/10.1155/2015/878724
http://dx.doi.org/10.1155/2015/878724
2 Mathematical Problems in Engineering
Recent path planning algorithms mainly include Legendre
pseudospectral algorithm [5, 6], generic algorithm (GA) [7,
8], and Fourier basis algorithm (FBA) [9, 10]. By using an
integral cost function consisting of energy consumption and
time cost index, [5] applies the Legendre pseudospectral
algorithm to the optimal path planning. Reference [6] reviews
key theoretical results of the pseudospectral optimal method
which are important for successful flights. An energy optimal
attitude maneuver path is planned by using the improved GA
[7].
The Legendre pseudospectral algorithm and generic algo-
rithm have many optimal parameters, thus resulting in com-
plex computation. Moreover, the two algorithms generate
time-discrete control inputs, which need to be approximated

by continuous functions after the path planning. The rapid
attitude maneuver control systems of agile satellites are
real-time systems. Therefore, the Legendre pseudospectral
algorithm and generic algorithm are not very suitable for the
rapid attitude maneuver control. Regarding the gimbal rates
of SGCMGs as control inputs, [9, 10] proposes a continuous
optimal path planning method based on the FBA. The idea
of FBA is to approximate control inputs by applying a
Fourier series. The path planning method based on FBA is
advantageous in terms of the computational time, and the
path planning results are continuous. However, the Fourier
coefficient vector is initialized by some random process in
[9, 10], and the algorithm cannot converge rapidly. The
choosing method of the initial Fourier coefficient has not
been introduced yet. Moreover, there exists no Fourier basis
path planning method which is proposed to investigate the
attitude control of agile maneuver satellite with DGCMGs.
Besides, since the disturbances and attitude tracking errors
have not been considered in the path planning, the attitude
tracking controller which can achieve the system robustness
needs to be improved [5, 9].
This paper fills the above gap in the existing literature.
The path planning and attitude control law of the agile
maneuver satellite with DGCMGs are integrated together.

The energy consumption and terminal state errors of double-
gimbal control moment gyroscopes are considered at the
same time. An improved FBA is proposed for the attitude
maneuver path planning for agile maneuver satellite with
DGCMGs. In order to shorten the computational time of
the path planning, a choosing method of the initial Fourier
coefficient is introduced. Meanwhile, the attitude tracking
feedback controller based on the path planning method is
proposed by applying a sliding mode controller. Simulations
are carried out to verify the availability of the introduced path
planning method and the corresponding attitude tracking
controller.
2. Model of the Satellite Attitude
Control System
As shown in Figure 1, the two parallel-mounted DGCMGs
are used as the attitude control actuators. x
�
, y
�
, and z

�
are
unit vectors aligned along the axes of the satellite body frame
coordinate. The orthonormal set of unit vectors x
�
, y
�
, z
�
is
used to describe the orientation of the �th DGCMG relative
to the spacecraft body frame, where x
�
is fixed along the
inner gimbal axis, y
�
is fixed along the outer gimbal axis,
and z
�

is fixed along the wheel spin axis. �
�
and �
�
denote
the inner gimbal angle and outer gimbal angle of the �th
DGCMG, respectively. �̇�
�
and ̇�
�
represent the inner gimbal
rate and outer gimbal rate of the �th DGCMG, respectively.
Assuming that ℎ
0
denote the wheel angular momentum of
the DGCMG, the total angular momentum of two parallel-
mounted DGCMGs expressed in the satellite body frame

coordinate can be written as
hcmg = ℎ0
[
[
[
[
cos �
1
cos �
1
+ cos �
2
cos �
2
− cos �
1
sin �
1

− cos �
2
sin �
2
− sin �
1
− sin �
2
]
]
]
]
. (1)
The output torque of DGCMGs can be obtained by using
the time derivative of hcmg as follows:

Tcmg = − ̇hcmg
= −ℎ
0
[
[
[
[
[
− sin �
1
cos �
1
− cos �
1
sin �
1

− sin �
2
cos �
2
− cos �
2
sin �
2
sin �
1
sin �
1
− cos �
1
cos �
1
sin �
2
sin �
2

− cos �
2
cos �
2
− cos �
1
0 − cos �
2
0
]
]
]
]
]
̇�= −ℎ
0

C (�) ̇�,
(2)
where� = [�
1
�
1
�
2
�
2
]
� denotes the gimbal angle vector
of two parallel-mounted DGCMGs and ̇� is the time deriva-
tive of�with respect to the satellite body frame. C is a 3 × 4
matrix, which can describe the three-dimensional control
authority of DGCMGs. As the singularity index det(CCT)
approaches zero, DGCMGs will encounter singularity.
Considering the angular momentum of each component
in the satellite attitude control system, the total angular
momentum is

Hb = Ib�+ hcmg, (3)
Mathematical Problems in Engineering 3
y1
z1
x1
yb
�̇�1
̇�1
xb
zb
z2
y2

�̇�2
̇�2
x2
O
Figure 1: Illustration of the two parallel-mounted DGCMGs.
where Ib represents the satellite moment of inertia and �
represents the attitude angular velocity. Supposing that the
satellite body is rigid, the dynamic equation is
̇H
�
+�× H
�
= T
�
, (4)
where ̇H

�
is the time derivative of H
�
with respect to
the satellite body frame and T
�
is the disturbance toque.
According to (2) and (3), (4) can be rewritten as
Ib�̇�+�× Ib�+ ℎ0C (�) ̇�+�× hcmg = T�. (5)
Aiming at describing the large-angle attitude maneuver,
the quaternion kinematics equation yields
q̇ =
1
2
[
[

[
[
[
[
0 −�
�
−�
�
−�
�
�
�
0 �
�
−�

�
�
�
−�
�
0 �
�
�
�
�
�
−�
�
0
]
]

]
]
]
]
q = E (�) q, (6)
where q = [�
0
q]� is unit quaternion. �
0
and q are scalar and
vector components of q. �
�
, �
�
, and �
�

denote elements of�
expressed in the satellite body frame coordinate. E is a 4 × 4
matrix associated with the attitude angular velocity.
Selecting x = [q� ��]� as the state variable, the attitude
control model of the satellite equipped with DGCMGs can be
described as
ẋ = f (�) u + g (x,�) , (7)
g (x,�) = [
E (�) q
−J−1(�× J�+�× hcmg)
] , (8)
f (�) = [
0
−J−1C (�) ℎ0
] , (9)
where the control input vector u is the DGCMG gimbal rate
vector ̇�. The boundary conditions of (7) are

x (0) = x0, x (��) = x�, (10)
where �
�
is the desired attitude maneuver time. x
0
is the initial
state variable vector. x
�
is the desired state variable vector.
3. Path Planning Method Based on the
Improved Fourier Basis Algorithm
3.1. Introduction of the Improved Fourier Basis Algorithm.
The path planning method based on the improved FBA
adopts a Fourier series to approximate the control inputs.
The searching methods, such as gradient descent method and
Newton method, are applied to search for the near optimal
Fourier coefficients, which make the cost function of the
attitude path planning converge to its minimal value. In
order to achieve the safe use of DGCMGs, the path planning

objective is to obtain the smooth attitude maneuver path
which keeps the maximal gimbal rate low, avoiding vibrating
motions. Therefore, the energy consumption of DGCMGs
should be low enough to meet the requirement of the path
planning objective. By considering the terminal state errors
and the energy consumption of DGCMGs, the cost function
of the attitude maneuver path planning yields
� (u) = ∫
��
0
(u�u) �� + (x (�
�
) − x
�
)
�
G (x (�
�
) − x
�

) , (11)
where G is a weighting matrix, which should be large enough
to reduce the terminal state errors. The first term in the cost
function is the energy cost of control inputs, and the second
term depends on terminal state errors. If the control inputs
are expressed by an orthonormal basis for L
2
([0, �
�
]), the
search for control inputs can be converted into solving for
optimal parameters of the expression. By choosing a Fourier
basis to describe the control input vector and restricting
control inputs to the first three terms of the Fourier basis, the
following can be obtained:
u =��, (12)
where
�= [0.5I
4

sin (�
�0
�) I
4
sin (2�
�0
�) I
4
sin (3�
�0
�) I
4
cos (�
�0
�) I
4
cos (2�
�0
�) I
4

cos (3�
�0
�) I
4
] , (13)
where � denotes the Fourier base term matrix, � denotes
the Fourier coefficient vector, I
4
is a 4 × 4 identity matrix,
and �
�0
= 2�/�
�
is the basic frequency of the Fourier basis
approximation. Inserting (12) into (11), the cost function of
the path planning comes to depend on the Fourier coefficients
as follows:

� (�) =�
�
�+ (x (�
�
) − x
�
)
�
G (x (�
�
) − x
�
) . (14)
In this way, the problem of the path planning based on
FBA is equivalent to a nonlinear search problem for the near
optimal coefficients that makes the cost function approach its
minimal value.

3.2. Choosing Method of the Initial Fourier Coefficients. The
choice of the initial Fourier coefficients is very important to
make the path planning method based on improved FBA
converge rapidly, which can improve the convergence speed
of the algorithm. The initial Fourier coefficients are computed
by the initial path of DGCMG gimbal rates. Moreover, as
can be seen in (7), gimbal rates can be generated by the
quaternion. Therefore, the choice of the initial Fourier coef-
ficients can start with the determination of initial quaternion
paths. (q
1
, q
2
, . . . , q
�
) is used to denote the initial quaternion
path, where q
1
and q
�

are the vector components of the
initial quaternion and the target quaternion, respectively.
q
�
(� = 2, . . . � − 1) represents the vector components of
the intermediate nodes of the quaternion path. The path
length � = �
�
/�
�
is calculated by the simulation time �
�
and
simulation step �
�
. According to (6), q
2
can be computed

by the initial quaternion q
1
and initial attitude angular
velocity�
0
. To meet the requirement of satellite attitude agile
maneuver, intermediate nodes (q
3
, . . . , q
�−1
) in the initial
quaternion path are produced based on the sigmoid function:
q
�
=
q
�
− q
2

1 + exp� [− (��
�
+ (� − 2) ��
− �)]
+ q
2
� ∈ (3, 4, . . . , � − 1) ,
(15)
where � is an appropriate constant. � and � can be computed
as follows:
f
2 (
�) =
q
�
− q
2

1 + exp� [− (� − �)]
+ q
2
,
Δf
2
(�) = f
2
((� + 1) �
�
) − f
2
(��
�
) ,
� = min (find (Δf
2
> 10
−3

)) ,
� =
� − � + 1
� − 2
,
� = max (find (Δf
2
> 10
−3
)) ,
(16)
where � ∈ (0, �
�
) and �
�
is a constant larger than �

�
.
When the quaternion path (q
1
, q
2
, . . . , q
�
) is obtained,
the attitude angular velocity can be achieved by the time
derivative of quaternion. Furthermore, DGCMG gimbal rates
can be calculated by the attitude angular velocity according
to (5). Finally, the Fourier series shown in (13) is applied to
approximating the evaluating gimbal rates, thus generating
the initial Fourier coefficient vector.
3.3. Search Method for the Fourier Basis Algorithm. The New-
ton method based on the first and second partial derivatives
of the cost function can improve the convergence property
of the path planning algorithm. However, it is difficult to
compute the second partial derivative of the cost function,

and the above choosing method of the initial Fourier coef-
ficient vector has improved the convergence speed already.
Therefore, the gradient descent method which only based
on the first partial derivative of the cost function is applied
to searching for the near optimal Fourier coefficient vector.
The computation of the first-order derivative of the cost
function at the searching point�
�
is shown as follows:
�J (�
�
)
��
�
= −� (�
�
− y�(�
�
) G (x − x

�
)) , (17)
where � is a positive constant and y(�
�
) is described by
y (�
�
) =
�x (�
�
)
��
.
(18)
y(�
�
) has no simple mathematic expression, and it can be
numerically evaluated by integrating its time derivative ẏ(�)

from � = 0 to � = �
�
. ẏ(�) and y(�
0
) are given as
ẏ (�) = (
4
∑
�=1
�f
�
��
u
�
) z + f�+
�g
�x

y +
�g
��
z, y (�
0
) = 0,
(19)
where z is the partial derivative of gimbal rates with respect
to the Fourier coefficient vector. Its time derivative and initial
value are
ż =�, z (�
0
) = 0. (20)
By applying the gradient descent method, the Fourier
coefficient variation Δ�about the searching point�
�
is given

by
Δ�= −� (�
�
− y�(�
�
) G (x − x
�
)) . (21)
Thus, the updating equation of the Fourier coefficient
vector can be obtained:
�
�+1
=�
�
+ Δ�. (22)
The updating operation of the Fourier coefficient vector
should be continued, until the near optimal solution of the
path planning satisfies the requirement of DGCMG energy

consumption and terminal state accuracy at the same time.
Results of the proposed path planning method are composed
of the varying path of the DGCMG gimbal rates, quaternion,
and attitude angular velocity.
4. Attitude Tracking Feedback Controller
Based on the Improved Path Planning
4.1. Model of Attitude Tracking Error. The error quaternion
q
�
= [�
�0
q
�
]
� can be computed by the desired quaternion
Path planning

based on improved
FBA
DGCMG
system
Satellite
system
Attitude tracking
feedback controller
Computing of attitude
tracking error
+
+
Gimbal rate
command
Control
torque

Tracking
error
Disturbance
Planning path of quaternion and
attitude angular velocity
Δu
unorm
Figure 2: Block diagram of the attitude tracking feedback
controller.
q
�
= [�
�0
q
�
]
� and the current quaternion q = [�

0
q]� as
follows:
�
�0
= �
0
�
�0
+ q�q
�
,
q
�
= �
�0
q − �
0
q
�
+ q × q

�
,
(23)
where �
�0
and q
�
have the constraint equation: �2
�0
+q
�
�q
�
= 1.
Assuming that �
�
is the desired attitude angular velocity, then
the error of the attitude angular velocity is defined as

�
�
=�− C�
�
�
�
, (24)
where C�
�
= (�
2
�0
−q
�
�q
�
)I
3
+2q

�
q
�
�
−2�
�0
q
�
×, q
�
× is the cross
matrix of q
�
, and I
3
denotes 3 × 3 identity matrix.
By inserting (24) into (5), the following can be obtained:
Ib�̇�� = Γ(Ib,��) − ℎ0C (�) u + T�, (25)

whereΓ(Ib,��) = −(�� + C
�
�
�
�
) × [Ib(�� + C
�
�
�
�
) + hcmg] +
Ib(�� × C
�
�
�
�
− C�
�
�̇�

�
).
According to the quaternion kinematics (6), the kinemat-
ics equation based on error quaternion can be written as
̇�
�0
= −
1
2
q
�
�
�
�
,
̇q
�
=

1
2
Z (q
�
)�
�
,
(26)
where Z(q
�
) = �
�0
I
3
+ q
�
×.
4.2. Design of the Attitude Tracking Controller Based on the

Improved Path Planning. The path planning method can
acquire the continuous path of DGCMG gimbal rates which
are effective in smooth action. The feedforward controller
using the planning path of gimbal rates directly can track
the desired quaternion path accurately without considering
the disturbances. However, there always exist several dis-
turbances, and the feedforward controller cannot maintain
precise attitude control. In order to acquire the robustness
against disturbances, the attitude tracking feedback controller
is introduced based on the attitude maneuver path planned by
the improved FBA. Since sliding mode controller has strong
robustness and favorable dynamic response performance, the
sliding mode controller is applied to the design of attitude
tracking feedback controller. Moreover, the planning paths
of the quaternion and attitude angular velocity are regarded
as the tracking paths of the attitude maneuver. The objective
of the feedback controller design is to compensate for the
attitude tracking error by adding Δu to unorm, where unorm
represents the planning gimbal rate of the proposed path
planning method and Δu is the added control input vector
which can eliminate errors. The block diagram of the attitude
tracking feedback controller is illustrated by Figure 2.
The sliding surface S is chosen as

S = �
�
+ Kq
�
, (27)
where K is a positive diagonal matrix, �
�
is the error between
the real angular velocity and the planning angular velocity,
and q
�
is the vector component of error quaternion.
In order to verify the stability of the sliding mode S = 0,
the Lyapunov function �
1
is selected as follows:
�
1

=
1
2
q
�
�q
�
+
1
2
(1 − �
�0
)
2
= 1 − �
�0

. (28)
It is obvious that �
1
is positive, and its time derivative is
̇
�
1
= − ̇�
�0
=
1
2
q
�
�
�
�
. (29)

Inserting S = 0 into (29), the following can be obtained:
̇
�
1
= −
1
2
(K−1)
�
�
�
�
�
�
. (30)
Since K is a positive matrix, there exists ̇�
1

< 0, thus
guaranteeing the stability of the sliding mode. The time
derivative of S is
̇S = I−1b (Γ(Ib,��) − ℎ0C (�) ul + T�) +
1
2
KZ (q
�
)�
�
, (31)
where ul = unorm + Δu is the total control input vector.
In order to generate a proper control law, another Lya-
punov function �
2
is chosen as
�
2
=

1
2
S�IbS. (32)
0 1 2 3 4 5 6 7
0
0.2
0.4
0.6
0.8
1

1.2
Q
ua
te
rn
io
n
−0.2
t (s)
qd0
qd1
qd2
qd3
(a)
0 1 2 3 4 5 6 7

0
0.2
0.4
0.6
0.8
1
1.2
Q
ua
te
rn
io
n
−0.2

t (s)
qd0
qd1
qd2
qd3
(b)
Figure 3: Time histories of quaternion. (a) Based on the path
planning method in [7]. (b) Based on the path planning method
in this paper.
The time derivative of �
2
can be written as
̇
�
2
= S�Ib ̇S
= S�(Γ(Ib,��) − ℎ0C (�) ul + T� +
1

2
IbKZ (q�)��) .
(33)
Let
ul = (ℎ0C (�))
−1
⋅ (Γ(Ib,��) + T� +
1
2
IbKZ (q�)�� + K�S
+ K
�
sign (S)) .
(34)
Then (33) can be rewritten as

̇
�
2
= −�S�S − �S� sign (S) , (35)
where K
�
and K
�
are both positive diagonal matrices. It is
obvious that ̇�
2
< 0, and the sliding surface can be reachable
with the control law.
The saturation function is defined as
sat (S, �) =
{
{
{
{

{
{
{
{
{
1 S > �
S
�
|S| ≤ �
−1 S < −�,
(36)
where � is a small positive constant. Aiming at avoiding the
vibrating motions, the sign function in (34) is substituted by
the saturation function as follows:
ul = (ℎ0C (�))
−1

⋅ (Γ(Ib,��)+ T�+
1
2
IbKZ (q�)��+ K�S + K� sat (S)) .
(37)
Then the added control input vector can be calculated by
Δu = ul − unorm. (38)
As can be seen from (37) and (38), the added control
input vector Δu is associated with the attitude tracking errors,
thus enabling it to compensate for the existing errors. It is
confirmed that the added control inputs can improve the
accuracy of the attitude control system.
5. Simulations and Discussions
Simulations for the path planning method based on improved
FBA and the associated attitude tracking feedback controller
are performed by using two parallel-mounted DGCMGs. The
satellite moment of inertia is

J = [[
[
12 0.12 0.12
0.13 13 0.13
0.15 0.15 15
]
]
]
kg ⋅ m2. (39)
Related parameters of the satellite and DGCMGs are
shown as follows: the desired attitude maneuver time �
�
=
7 s, the simulation step �

�
= 0.1 s, the initial quater-
nion q
1
= [1 0 0 0]
�, the desired quaternion q
�
=
0 1 2 3 4 5 6 7
0
1
2

3
4
5
6
7
8
A
ng
ul
ar
v
el
oc
ity
(d

eg
/s
)
t (s)
−1
x
y
z
(a)
0 1 2 3 4 5 6 7
0
2
4

6
8
10
A
ng
ul
ar
v
el
oc
ity
(d
eg
/s
)
t (s)

−2
x
y
z
(b)
Figure 4: Time histories of attitude angular velocity. (a) Based
on the path planning method in [7]. (b) Based on the path
planning method
in this paper.
[0.97 0.26 0 0]
�, the initial attitude angular velocity�
0
=
[1.1 1.2 1.6]
� deg /s, the desired attitude angular velocity

�
�
= [0 0 0]
� deg /s, the wheel angular momentum of
DGCMGs ℎ
0
= 6 Nms, the initial gimbal angle vector �
0
=
[0 0 0 −90]
� deg, and the maximal gimbal rate is 10 deg/s.
5.1. Path Planning Results Based on the Improved FBA. Path
planning results based on the improved FBA are compared
with that in [7]. During the comparison, the related parame-
ters of the satellite and DGCMGs are all the same. Parameters
of the initial Fourier coefficient choosing method are � =
8.05, � = 1.96. Parameters of searching method are G =
diag(0, 4, 4, 4, 6, 6, 6)×102, � = 2.2×10−4. The stop condition

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