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Realizing Value from Digital Transformation: Benefits Management Re-imagined

2022· article· en· W4295769419 on OpenAlexaff
Blaize Horner Reich, Joe Peppard

Bibliographic record

Venue2022 Portland International Conference on Management of Engineering and Technology (PICMET) · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Knowledge Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDigital transformationTransformation (genetics)Computer scienceValue (mathematics)World Wide Web

Abstract

fetched live from OpenAlex

When organizations first harnessed information technology to solve business problems, automate processes and provide information, it could take many months, even years, to deploy an application. This situation changed two decades ago when Software-as-a-Service products, hosted in the cloud, became available. Today, technology has matured sufficiently, and it is possible to install an IT platform to support a global business process in a matter of weeks and to stitch multiple applications together into a reliable and agile architectural foundation. While legacy technology still poses a major problem, technology for new investments is no longer the bottleneck that it once was.This is likely one of the reasons why it is widely acknowledged that achieving digital transformation ambitions is less about technology deployment and more about the ability of the organization to adopt it and adapt to it, and to ultimately create real business value. But here is the conundrum: while the time to implement technology has been significantly compressed, achieving the organizational changes needed to reap benefits still require months and even years to achieve.A weakness in mainstream project management literature, especially when applied to technology-enabled business investments, is the assumption that the project is complete once the software is released, stabilized, and “accepted” by the project’s sponsor. Sometimes, a window of time is allocated to “finish” the project; an after-action or lessons learned report is produced, the project team disbands, and victory is declared. When considering the success or failure of projects, discussions usually revolve around the budget, schedule, the software and its acceptance, but generally not about the changes that the organization has experienced as a result of improved processes or enhanced capabilities or whether the expected benefits were delivered. Despite recognizing that benefits come from organizational changes, project management is still premised around scope, resources and time. This can be because benefits have not yet happened; the nature of most IT projects is that benefits only emerge many weeks and months after “go-live.” Victory is often declared prematurely.To promote the achievement of benefits from IT investments, the concept of Benefits Management was introduced in the 1990’s. Its aim was to focus on what business benefits were expected to be delivered from the investment and to accelerate the realization of these benefits from harnessing the capabilities of technology. This was achieved by identifying the organizational changes necessary to release these benefits, as well as tracking the benefits realized throughout the entire initiation-to-realization cycle. It also advocated that expected benefits should be aligned to key strategic drivers.Since the original work on Benefits Management was undertaken, the context for IT investments has changed dramatically. The initial research was focused on improving the performance outcomes from large enterprise system investments; these systems had an internal organizational focus and took considerable time to implement. Back then, how systems were built was also different, due primarily to the constraints imposed by technology, development frameworks and dominant practices. Technologies like AI and analytics pose particular challenges for managing benefits in that it is difficult to specify them prior to technology deployment. Moreover, today, technology is a competitive necessity; it is shaping business models and customers expect to engage with an organization in a digital way; and systems can extend outside the organizational boundary to ecosystem partners. Speed, innovation, and agility are critical determinants of success in a digital-first world, fundamentally changing how an organization competes. All of these changes impact the nature of projects and how they are set up and run.Although benefits management is an established concept in the project management and technology literatures, it is not well-known as an organizational practice. In this paper, we revisit the benefits management concept, discuss some of the adoption barriers, and suggest a number of ways to adapt benefits management to digital transformation programs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.217
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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